Data_Science_health_medicine_Johns_Hopkins.ipynb

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      "name": "python3",
      "display_name": "Python 3"
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    {
      "cell_type": "markdown",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/felipenufisnor/data-science-health-medicine-Johns-Hopkins/blob/main/Data_Science_health_medicine_Johns_Hopkins.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "id": "qatscdizf92Y",
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          "base_uri": "https://localhost:8080/",
          "height": 218
        }
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "confirmed = pd.read_csv(\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv\")\n",
        "confirmed.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Province/State</th>\n",
              "      <th>Country/Region</th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
              "      <th>1/23/20</th>\n",
              "      <th>1/24/20</th>\n",
              "      <th>1/25/20</th>\n",
              "      <th>1/26/20</th>\n",
              "      <th>1/27/20</th>\n",
              "      <th>1/28/20</th>\n",
              "      <th>1/29/20</th>\n",
              "      <th>1/30/20</th>\n",
              "      <th>1/31/20</th>\n",
              "      <th>2/1/20</th>\n",
              "      <th>2/2/20</th>\n",
              "      <th>2/3/20</th>\n",
              "      <th>2/4/20</th>\n",
              "      <th>2/5/20</th>\n",
              "      <th>2/6/20</th>\n",
              "      <th>2/7/20</th>\n",
              "      <th>2/8/20</th>\n",
              "      <th>2/9/20</th>\n",
              "      <th>2/10/20</th>\n",
              "      <th>2/11/20</th>\n",
              "      <th>2/12/20</th>\n",
              "      <th>2/13/20</th>\n",
              "      <th>2/14/20</th>\n",
              "      <th>2/15/20</th>\n",
              "      <th>2/16/20</th>\n",
              "      <th>2/17/20</th>\n",
              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
              "      <th>2/21/20</th>\n",
              "      <th>2/22/20</th>\n",
              "      <th>2/23/20</th>\n",
              "      <th>2/24/20</th>\n",
              "      <th>2/25/20</th>\n",
              "      <th>2/26/20</th>\n",
              "      <th>2/27/20</th>\n",
              "      <th>2/28/20</th>\n",
              "      <th>2/29/20</th>\n",
              "      <th>3/1/20</th>\n",
              "      <th>3/2/20</th>\n",
              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Anhui</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.8257</td>\n",
              "      <td>117.2264</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>39</td>\n",
              "      <td>60</td>\n",
              "      <td>70</td>\n",
              "      <td>106</td>\n",
              "      <td>152</td>\n",
              "      <td>200</td>\n",
              "      <td>237</td>\n",
              "      <td>297</td>\n",
              "      <td>340</td>\n",
              "      <td>408</td>\n",
              "      <td>480</td>\n",
              "      <td>530</td>\n",
              "      <td>591</td>\n",
              "      <td>665</td>\n",
              "      <td>733</td>\n",
              "      <td>779</td>\n",
              "      <td>830</td>\n",
              "      <td>860</td>\n",
              "      <td>889</td>\n",
              "      <td>910</td>\n",
              "      <td>934</td>\n",
              "      <td>950</td>\n",
              "      <td>962</td>\n",
              "      <td>973</td>\n",
              "      <td>982</td>\n",
              "      <td>986</td>\n",
              "      <td>987</td>\n",
              "      <td>988</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Beijing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>40.1824</td>\n",
              "      <td>116.4142</td>\n",
              "      <td>14</td>\n",
              "      <td>22</td>\n",
              "      <td>36</td>\n",
              "      <td>41</td>\n",
              "      <td>68</td>\n",
              "      <td>80</td>\n",
              "      <td>91</td>\n",
              "      <td>111</td>\n",
              "      <td>114</td>\n",
              "      <td>139</td>\n",
              "      <td>168</td>\n",
              "      <td>191</td>\n",
              "      <td>212</td>\n",
              "      <td>228</td>\n",
              "      <td>253</td>\n",
              "      <td>274</td>\n",
              "      <td>297</td>\n",
              "      <td>315</td>\n",
              "      <td>326</td>\n",
              "      <td>337</td>\n",
              "      <td>342</td>\n",
              "      <td>352</td>\n",
              "      <td>366</td>\n",
              "      <td>372</td>\n",
              "      <td>375</td>\n",
              "      <td>380</td>\n",
              "      <td>381</td>\n",
              "      <td>387</td>\n",
              "      <td>393</td>\n",
              "      <td>395</td>\n",
              "      <td>396</td>\n",
              "      <td>399</td>\n",
              "      <td>399</td>\n",
              "      <td>399</td>\n",
              "      <td>400</td>\n",
              "      <td>400</td>\n",
              "      <td>410</td>\n",
              "      <td>410</td>\n",
              "      <td>411</td>\n",
              "      <td>413</td>\n",
              "      <td>414</td>\n",
              "      <td>414</td>\n",
              "      <td>418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.0572</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>27</td>\n",
              "      <td>57</td>\n",
              "      <td>75</td>\n",
              "      <td>110</td>\n",
              "      <td>132</td>\n",
              "      <td>147</td>\n",
              "      <td>182</td>\n",
              "      <td>211</td>\n",
              "      <td>247</td>\n",
              "      <td>300</td>\n",
              "      <td>337</td>\n",
              "      <td>366</td>\n",
              "      <td>389</td>\n",
              "      <td>411</td>\n",
              "      <td>426</td>\n",
              "      <td>428</td>\n",
              "      <td>468</td>\n",
              "      <td>486</td>\n",
              "      <td>505</td>\n",
              "      <td>518</td>\n",
              "      <td>529</td>\n",
              "      <td>537</td>\n",
              "      <td>544</td>\n",
              "      <td>551</td>\n",
              "      <td>553</td>\n",
              "      <td>555</td>\n",
              "      <td>560</td>\n",
              "      <td>567</td>\n",
              "      <td>572</td>\n",
              "      <td>573</td>\n",
              "      <td>575</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fujian</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.0789</td>\n",
              "      <td>117.9874</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>18</td>\n",
              "      <td>35</td>\n",
              "      <td>59</td>\n",
              "      <td>80</td>\n",
              "      <td>84</td>\n",
              "      <td>101</td>\n",
              "      <td>120</td>\n",
              "      <td>144</td>\n",
              "      <td>159</td>\n",
              "      <td>179</td>\n",
              "      <td>194</td>\n",
              "      <td>205</td>\n",
              "      <td>215</td>\n",
              "      <td>224</td>\n",
              "      <td>239</td>\n",
              "      <td>250</td>\n",
              "      <td>261</td>\n",
              "      <td>267</td>\n",
              "      <td>272</td>\n",
              "      <td>279</td>\n",
              "      <td>281</td>\n",
              "      <td>285</td>\n",
              "      <td>287</td>\n",
              "      <td>290</td>\n",
              "      <td>292</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>294</td>\n",
              "      <td>294</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gansu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.0611</td>\n",
              "      <td>103.8343</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>40</td>\n",
              "      <td>51</td>\n",
              "      <td>55</td>\n",
              "      <td>57</td>\n",
              "      <td>62</td>\n",
              "      <td>62</td>\n",
              "      <td>67</td>\n",
              "      <td>79</td>\n",
              "      <td>83</td>\n",
              "      <td>83</td>\n",
              "      <td>86</td>\n",
              "      <td>87</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Province/State  Country/Region      Lat  ...  3/2/20  3/3/20  3/4/20\n",
              "0          Anhui  Mainland China  31.8257  ...     990     990     990\n",
              "1        Beijing  Mainland China  40.1824  ...     414     414     418\n",
              "2      Chongqing  Mainland China  30.0572  ...     576     576     576\n",
              "3         Fujian  Mainland China  26.0789  ...     296     296     296\n",
              "4          Gansu  Mainland China  36.0611  ...      91      91      91\n",
              "\n",
              "[5 rows x 47 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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        "outputId": "f3e62454-6b9b-4a14-98f5-9d6f20530408",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "confirmed.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(160, 47)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
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        "outputId": "01fb123c-ead6-4c03-acb3-e30f69a9b810",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        }
      },
      "source": [
        "last_date = \"3/2/20\"\n",
        "\n",
        "confirmed[last_date]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      990\n",
              "1      414\n",
              "2      576\n",
              "3      296\n",
              "4       91\n",
              "      ... \n",
              "155      0\n",
              "156      0\n",
              "157      0\n",
              "158      0\n",
              "159      0\n",
              "Name: 3/2/20, Length: 160, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MpYCo-ArgxUi",
        "outputId": "c37c7fca-7817-4334-c35f-4b1d6a632514",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        }
      },
      "source": [
        "confirmed[\"Country/Region\"]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      Mainland China\n",
              "1      Mainland China\n",
              "2      Mainland China\n",
              "3      Mainland China\n",
              "4      Mainland China\n",
              "            ...      \n",
              "155         Gibraltar\n",
              "156     Liechtenstein\n",
              "157            Poland\n",
              "158           Tunisia\n",
              "159                US\n",
              "Name: Country/Region, Length: 160, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d75ezwHnhC-d",
        "outputId": "ca635d59-df00-4a4a-eea9-25275b7752ce",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        }
      },
      "source": [
        "confirmed[\"Country/Region\"].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Mainland China', 'Thailand', 'Japan', 'South Korea', 'Taiwan',\n",
              "       'US', 'Macau', 'Hong Kong', 'Singapore', 'Vietnam', 'France',\n",
              "       'Nepal', 'Malaysia', 'Canada', 'Australia', 'Cambodia',\n",
              "       'Sri Lanka', 'Germany', 'Finland', 'United Arab Emirates',\n",
              "       'Philippines', 'India', 'Italy', 'UK', 'Russia', 'Sweden', 'Spain',\n",
              "       'Belgium', 'Others', 'Egypt', 'Iran', 'Lebanon', 'Iraq', 'Oman',\n",
              "       'Afghanistan', 'Bahrain', 'Kuwait', 'Algeria', 'Croatia',\n",
              "       'Switzerland', 'Austria', 'Israel', 'Pakistan', 'Brazil',\n",
              "       'Georgia', 'Greece', 'North Macedonia', 'Norway', 'Romania',\n",
              "       'Denmark', 'Estonia', 'Netherlands', 'San Marino', 'Belarus',\n",
              "       'Iceland', 'Lithuania', 'Mexico', 'New Zealand', 'Nigeria',\n",
              "       'Ireland', 'Luxembourg', 'Monaco', 'Qatar', 'Ecuador',\n",
              "       'Azerbaijan', 'Czech Republic', 'Armenia', 'Dominican Republic',\n",
              "       'Indonesia', 'Portugal', 'Andorra', 'Latvia', 'Morocco',\n",
              "       'Saudi Arabia', 'Senegal', 'Argentina', 'Chile', 'Jordan',\n",
              "       'Ukraine', 'Saint Barthelemy', 'Hungary', 'Faroe Islands',\n",
              "       'Gibraltar', 'Liechtenstein', 'Poland', 'Tunisia'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YkFdUtqQhbZV",
        "outputId": "4a3a3cf7-3e30-445e-eee7-5402b897d5c6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        }
      },
      "source": [
        "confirmed[\"Province/State\"].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Anhui', 'Beijing', 'Chongqing', 'Fujian', 'Gansu', 'Guangdong',\n",
              "       'Guangxi', 'Guizhou', 'Hainan', 'Hebei', 'Heilongjiang', 'Henan',\n",
              "       'Hubei', 'Hunan', 'Inner Mongolia', 'Jiangsu', 'Jiangxi', 'Jilin',\n",
              "       'Liaoning', 'Ningxia', 'Qinghai', 'Shaanxi', 'Shandong',\n",
              "       'Shanghai', 'Shanxi', 'Sichuan', 'Tianjin', 'Tibet', 'Xinjiang',\n",
              "       'Yunnan', 'Zhejiang', nan, 'Taiwan', 'King County, WA',\n",
              "       'Cook County, IL', 'Tempe, AZ', 'Macau', 'Hong Kong',\n",
              "       'Toronto, ON', 'British Columbia', 'Los Angeles, CA',\n",
              "       'New South Wales', 'Victoria', 'Queensland', 'London, ON',\n",
              "       'Santa Clara, CA', 'South Australia', 'Boston, MA',\n",
              "       'San Benito, CA', 'Madison, WI', 'Diamond Princess cruise ship',\n",
              "       'San Diego County, CA', 'San Antonio, TX',\n",
              "       'Omaha, NE (From Diamond Princess)',\n",
              "       'Travis, CA (From Diamond Princess)', 'From Diamond Princess',\n",
              "       'Lackland, TX (From Diamond Princess)', 'Humboldt County, CA',\n",
              "       'Sacramento County, CA',\n",
              "       'Unassigned Location (From Diamond Princess)', ' Montreal, QC',\n",
              "       'Western Australia', 'Snohomish County, WA', 'Providence, RI',\n",
              "       'Tasmania', 'Grafton County, NH', 'Hillsborough, FL',\n",
              "       'New York City, NY', 'Placer County, CA', 'San Mateo, CA',\n",
              "       'Sarasota, FL', 'Sonoma County, CA', 'Umatilla, OR',\n",
              "       'Fulton County, GA', 'Washington County, OR',\n",
              "       ' Norfolk County, MA', 'Berkeley, CA', 'Maricopa County, AZ',\n",
              "       'Wake County, NC', 'Westchester County, NY', 'Orange County, CA',\n",
              "       'Northern Territory', 'Contra Costa County, CA'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
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      },
      "source": [
        "confirmed.sample(20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>43</th>\n",
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              "      <th>92</th>\n",
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              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>Los Angeles, CA</td>\n",
              "      <td>US</td>\n",
              "      <td>34.0522</td>\n",
              "      <td>-118.2437</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Egypt</td>\n",
              "      <td>26.0000</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Shandong</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.3427</td>\n",
              "      <td>118.1498</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>15</td>\n",
              "      <td>27</td>\n",
              "      <td>46</td>\n",
              "      <td>75</td>\n",
              "      <td>95</td>\n",
              "      <td>130</td>\n",
              "      <td>158</td>\n",
              "      <td>184</td>\n",
              "      <td>206</td>\n",
              "      <td>230</td>\n",
              "      <td>259</td>\n",
              "      <td>275</td>\n",
              "      <td>307</td>\n",
              "      <td>347</td>\n",
              "      <td>386</td>\n",
              "      <td>416</td>\n",
              "      <td>444</td>\n",
              "      <td>466</td>\n",
              "      <td>487</td>\n",
              "      <td>497</td>\n",
              "      <td>509</td>\n",
              "      <td>523</td>\n",
              "      <td>532</td>\n",
              "      <td>537</td>\n",
              "      <td>541</td>\n",
              "      <td>543</td>\n",
              "      <td>544</td>\n",
              "      <td>546</td>\n",
              "      <td>749</td>\n",
              "      <td>750</td>\n",
              "      <td>754</td>\n",
              "      <td>755</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>758</td>\n",
              "      <td>758</td>\n",
              "      <td>758</td>\n",
              "      <td>758</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Latvia</td>\n",
              "      <td>56.8796</td>\n",
              "      <td>24.6032</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Lebanon</td>\n",
              "      <td>33.8547</td>\n",
              "      <td>35.8623</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>10</td>\n",
              "      <td>13</td>\n",
              "      <td>13</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Hunan</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>27.6104</td>\n",
              "      <td>111.7088</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>24</td>\n",
              "      <td>43</td>\n",
              "      <td>69</td>\n",
              "      <td>100</td>\n",
              "      <td>143</td>\n",
              "      <td>221</td>\n",
              "      <td>277</td>\n",
              "      <td>332</td>\n",
              "      <td>389</td>\n",
              "      <td>463</td>\n",
              "      <td>521</td>\n",
              "      <td>593</td>\n",
              "      <td>661</td>\n",
              "      <td>711</td>\n",
              "      <td>772</td>\n",
              "      <td>803</td>\n",
              "      <td>838</td>\n",
              "      <td>879</td>\n",
              "      <td>912</td>\n",
              "      <td>946</td>\n",
              "      <td>968</td>\n",
              "      <td>988</td>\n",
              "      <td>1001</td>\n",
              "      <td>1004</td>\n",
              "      <td>1006</td>\n",
              "      <td>1007</td>\n",
              "      <td>1008</td>\n",
              "      <td>1010</td>\n",
              "      <td>1011</td>\n",
              "      <td>1013</td>\n",
              "      <td>1016</td>\n",
              "      <td>1016</td>\n",
              "      <td>1016</td>\n",
              "      <td>1016</td>\n",
              "      <td>1017</td>\n",
              "      <td>1017</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Toronto, ON</td>\n",
              "      <td>Canada</td>\n",
              "      <td>43.6532</td>\n",
              "      <td>-79.3832</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>19</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Luxembourg</td>\n",
              "      <td>49.8153</td>\n",
              "      <td>6.1296</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Liaoning</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>41.2956</td>\n",
              "      <td>122.6085</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>17</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>34</td>\n",
              "      <td>39</td>\n",
              "      <td>41</td>\n",
              "      <td>48</td>\n",
              "      <td>64</td>\n",
              "      <td>70</td>\n",
              "      <td>74</td>\n",
              "      <td>81</td>\n",
              "      <td>89</td>\n",
              "      <td>94</td>\n",
              "      <td>99</td>\n",
              "      <td>105</td>\n",
              "      <td>107</td>\n",
              "      <td>108</td>\n",
              "      <td>111</td>\n",
              "      <td>116</td>\n",
              "      <td>117</td>\n",
              "      <td>119</td>\n",
              "      <td>119</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>122</td>\n",
              "      <td>122</td>\n",
              "      <td>125</td>\n",
              "      <td>125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.0572</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>27</td>\n",
              "      <td>57</td>\n",
              "      <td>75</td>\n",
              "      <td>110</td>\n",
              "      <td>132</td>\n",
              "      <td>147</td>\n",
              "      <td>182</td>\n",
              "      <td>211</td>\n",
              "      <td>247</td>\n",
              "      <td>300</td>\n",
              "      <td>337</td>\n",
              "      <td>366</td>\n",
              "      <td>389</td>\n",
              "      <td>411</td>\n",
              "      <td>426</td>\n",
              "      <td>428</td>\n",
              "      <td>468</td>\n",
              "      <td>486</td>\n",
              "      <td>505</td>\n",
              "      <td>518</td>\n",
              "      <td>529</td>\n",
              "      <td>537</td>\n",
              "      <td>544</td>\n",
              "      <td>551</td>\n",
              "      <td>553</td>\n",
              "      <td>555</td>\n",
              "      <td>560</td>\n",
              "      <td>567</td>\n",
              "      <td>572</td>\n",
              "      <td>573</td>\n",
              "      <td>575</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>Sacramento County, CA</td>\n",
              "      <td>US</td>\n",
              "      <td>38.4747</td>\n",
              "      <td>-121.3542</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>Contra Costa County, CA</td>\n",
              "      <td>US</td>\n",
              "      <td>37.8534</td>\n",
              "      <td>-121.9018</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Indonesia</td>\n",
              "      <td>-0.7893</td>\n",
              "      <td>113.9213</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Nigeria</td>\n",
              "      <td>9.0820</td>\n",
              "      <td>8.6753</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>San Antonio, TX</td>\n",
              "      <td>US</td>\n",
              "      <td>29.4241</td>\n",
              "      <td>-98.4936</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Taiwan</td>\n",
              "      <td>Taiwan</td>\n",
              "      <td>23.7000</td>\n",
              "      <td>121.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>16</td>\n",
              "      <td>16</td>\n",
              "      <td>17</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>23</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>28</td>\n",
              "      <td>30</td>\n",
              "      <td>31</td>\n",
              "      <td>32</td>\n",
              "      <td>32</td>\n",
              "      <td>34</td>\n",
              "      <td>39</td>\n",
              "      <td>40</td>\n",
              "      <td>41</td>\n",
              "      <td>42</td>\n",
              "      <td>42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Shaanxi</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>35.1917</td>\n",
              "      <td>108.8701</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>22</td>\n",
              "      <td>35</td>\n",
              "      <td>46</td>\n",
              "      <td>56</td>\n",
              "      <td>63</td>\n",
              "      <td>87</td>\n",
              "      <td>101</td>\n",
              "      <td>116</td>\n",
              "      <td>128</td>\n",
              "      <td>142</td>\n",
              "      <td>165</td>\n",
              "      <td>173</td>\n",
              "      <td>184</td>\n",
              "      <td>195</td>\n",
              "      <td>208</td>\n",
              "      <td>213</td>\n",
              "      <td>219</td>\n",
              "      <td>225</td>\n",
              "      <td>229</td>\n",
              "      <td>230</td>\n",
              "      <td>232</td>\n",
              "      <td>236</td>\n",
              "      <td>240</td>\n",
              "      <td>240</td>\n",
              "      <td>242</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Province/State  Country/Region      Lat  ...  3/2/20  3/3/20  3/4/20\n",
              "68                       NaN         Belgium  50.8333  ...       8      13      23\n",
              "43                       NaN           Nepal  28.1667  ...       1       1       1\n",
              "92                       NaN          Israel  31.0000  ...      10      12      15\n",
              "47           Los Angeles, CA              US  34.0522  ...       1       1       7\n",
              "73                       NaN           Egypt  26.0000  ...       2       2       2\n",
              "22                  Shandong  Mainland China  36.3427  ...     758     758     758\n",
              "127                      NaN          Latvia  56.8796  ...       1       1       1\n",
              "79                       NaN         Lebanon  33.8547  ...      13      13      13\n",
              "13                     Hunan  Mainland China  27.6104  ...    1018    1018    1018\n",
              "45               Toronto, ON          Canada  43.6532  ...      17      19      19\n",
              "113                      NaN      Luxembourg  49.8153  ...       1       1       1\n",
              "18                  Liaoning  Mainland China  41.2956  ...     122     125     125\n",
              "2                  Chongqing  Mainland China  30.0572  ...     576     576     576\n",
              "81     Sacramento County, CA              US  38.4747  ...       2       2       2\n",
              "159  Contra Costa County, CA              US  37.8534  ...       0       0       1\n",
              "123                      NaN       Indonesia  -0.7893  ...       2       2       2\n",
              "110                      NaN         Nigeria   9.0820  ...       1       1       1\n",
              "72           San Antonio, TX              US  29.4241  ...       1       1       1\n",
              "34                    Taiwan          Taiwan  23.7000  ...      41      42      42\n",
              "21                   Shaanxi  Mainland China  35.1917  ...     245     245     245\n",
              "\n",
              "[20 rows x 47 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xMxLzhXXhlGX",
        "outputId": "2fe036b3-b550-425f-9a69-7602738bed17",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 846
        }
      },
      "source": [
        "confirmed.iloc[1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Province/State           Beijing\n",
              "Country/Region    Mainland China\n",
              "Lat                      40.1824\n",
              "Long                     116.414\n",
              "1/22/20                       14\n",
              "1/23/20                       22\n",
              "1/24/20                       36\n",
              "1/25/20                       41\n",
              "1/26/20                       68\n",
              "1/27/20                       80\n",
              "1/28/20                       91\n",
              "1/29/20                      111\n",
              "1/30/20                      114\n",
              "1/31/20                      139\n",
              "2/1/20                       168\n",
              "2/2/20                       191\n",
              "2/3/20                       212\n",
              "2/4/20                       228\n",
              "2/5/20                       253\n",
              "2/6/20                       274\n",
              "2/7/20                       297\n",
              "2/8/20                       315\n",
              "2/9/20                       326\n",
              "2/10/20                      337\n",
              "2/11/20                      342\n",
              "2/12/20                      352\n",
              "2/13/20                      366\n",
              "2/14/20                      372\n",
              "2/15/20                      375\n",
              "2/16/20                      380\n",
              "2/17/20                      381\n",
              "2/18/20                      387\n",
              "2/19/20                      393\n",
              "2/20/20                      395\n",
              "2/21/20                      396\n",
              "2/22/20                      399\n",
              "2/23/20                      399\n",
              "2/24/20                      399\n",
              "2/25/20                      400\n",
              "2/26/20                      400\n",
              "2/27/20                      410\n",
              "2/28/20                      410\n",
              "2/29/20                      411\n",
              "3/1/20                       413\n",
              "3/2/20                       414\n",
              "3/3/20                       414\n",
              "3/4/20                       418\n",
              "Name: 1, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o3Kga3RKh500",
        "outputId": "16f77b85-2ac9-4c84-a2cf-24141a2a8d8e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 829
        }
      },
      "source": [
        "confirmed.set_index(\"Province/State\").loc[\"Anhui\"]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Country/Region    Mainland China\n",
              "Lat                      31.8257\n",
              "Long                     117.226\n",
              "1/22/20                        1\n",
              "1/23/20                        9\n",
              "1/24/20                       15\n",
              "1/25/20                       39\n",
              "1/26/20                       60\n",
              "1/27/20                       70\n",
              "1/28/20                      106\n",
              "1/29/20                      152\n",
              "1/30/20                      200\n",
              "1/31/20                      237\n",
              "2/1/20                       297\n",
              "2/2/20                       340\n",
              "2/3/20                       408\n",
              "2/4/20                       480\n",
              "2/5/20                       530\n",
              "2/6/20                       591\n",
              "2/7/20                       665\n",
              "2/8/20                       733\n",
              "2/9/20                       779\n",
              "2/10/20                      830\n",
              "2/11/20                      860\n",
              "2/12/20                      889\n",
              "2/13/20                      910\n",
              "2/14/20                      934\n",
              "2/15/20                      950\n",
              "2/16/20                      962\n",
              "2/17/20                      973\n",
              "2/18/20                      982\n",
              "2/19/20                      986\n",
              "2/20/20                      987\n",
              "2/21/20                      988\n",
              "2/22/20                      989\n",
              "2/23/20                      989\n",
              "2/24/20                      989\n",
              "2/25/20                      989\n",
              "2/26/20                      989\n",
              "2/27/20                      989\n",
              "2/28/20                      990\n",
              "2/29/20                      990\n",
              "3/1/20                       990\n",
              "3/2/20                       990\n",
              "3/3/20                       990\n",
              "3/4/20                       990\n",
              "Name: Anhui, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2SyYtm1AiBYk",
        "outputId": "037623f7-86d1-4ba9-8992-a0134d1d4c1c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 829
        }
      },
      "source": [
        "confirmed.set_index(\"Province/State\").iloc[1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Country/Region    Mainland China\n",
              "Lat                      40.1824\n",
              "Long                     116.414\n",
              "1/22/20                       14\n",
              "1/23/20                       22\n",
              "1/24/20                       36\n",
              "1/25/20                       41\n",
              "1/26/20                       68\n",
              "1/27/20                       80\n",
              "1/28/20                       91\n",
              "1/29/20                      111\n",
              "1/30/20                      114\n",
              "1/31/20                      139\n",
              "2/1/20                       168\n",
              "2/2/20                       191\n",
              "2/3/20                       212\n",
              "2/4/20                       228\n",
              "2/5/20                       253\n",
              "2/6/20                       274\n",
              "2/7/20                       297\n",
              "2/8/20                       315\n",
              "2/9/20                       326\n",
              "2/10/20                      337\n",
              "2/11/20                      342\n",
              "2/12/20                      352\n",
              "2/13/20                      366\n",
              "2/14/20                      372\n",
              "2/15/20                      375\n",
              "2/16/20                      380\n",
              "2/17/20                      381\n",
              "2/18/20                      387\n",
              "2/19/20                      393\n",
              "2/20/20                      395\n",
              "2/21/20                      396\n",
              "2/22/20                      399\n",
              "2/23/20                      399\n",
              "2/24/20                      399\n",
              "2/25/20                      400\n",
              "2/26/20                      400\n",
              "2/27/20                      410\n",
              "2/28/20                      410\n",
              "2/29/20                      411\n",
              "3/1/20                       413\n",
              "3/2/20                       414\n",
              "3/3/20                       414\n",
              "3/4/20                       418\n",
              "Name: Beijing, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_sytBg9EiM9U",
        "outputId": "b1b25d9a-e185-4a52-ccb2-c894d9057181",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        }
      },
      "source": [
        "# valor falso pois o erro é muito grande\n",
        "# não vou considerar essa analise pois tem muito campo vazio (muita disparidade no padrão)\n",
        "\n",
        "confirmed[\"Country/Region\"].value_counts()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "US                35\n",
              "Mainland China    31\n",
              "Australia          8\n",
              "Canada             4\n",
              "Kuwait             1\n",
              "                  ..\n",
              "Oman               1\n",
              "Morocco            1\n",
              "Latvia             1\n",
              "Belgium            1\n",
              "Jordan             1\n",
              "Name: Country/Region, Length: 86, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EisiJz75iatq",
        "outputId": "507e31dc-16bd-4cf5-f493-ce7e653b0958",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        }
      },
      "source": [
        "confirmed_by_country = confirmed.groupby(\"Country/Region\").sum()\n",
        "confirmed_by_country.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
              "      <th>1/23/20</th>\n",
              "      <th>1/24/20</th>\n",
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              "      <th>1/26/20</th>\n",
              "      <th>1/27/20</th>\n",
              "      <th>1/28/20</th>\n",
              "      <th>1/29/20</th>\n",
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              "      <th>1/31/20</th>\n",
              "      <th>2/1/20</th>\n",
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              "      <th>2/3/20</th>\n",
              "      <th>2/4/20</th>\n",
              "      <th>2/5/20</th>\n",
              "      <th>2/6/20</th>\n",
              "      <th>2/7/20</th>\n",
              "      <th>2/8/20</th>\n",
              "      <th>2/9/20</th>\n",
              "      <th>2/10/20</th>\n",
              "      <th>2/11/20</th>\n",
              "      <th>2/12/20</th>\n",
              "      <th>2/13/20</th>\n",
              "      <th>2/14/20</th>\n",
              "      <th>2/15/20</th>\n",
              "      <th>2/16/20</th>\n",
              "      <th>2/17/20</th>\n",
              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
              "      <th>2/21/20</th>\n",
              "      <th>2/22/20</th>\n",
              "      <th>2/23/20</th>\n",
              "      <th>2/24/20</th>\n",
              "      <th>2/25/20</th>\n",
              "      <th>2/26/20</th>\n",
              "      <th>2/27/20</th>\n",
              "      <th>2/28/20</th>\n",
              "      <th>2/29/20</th>\n",
              "      <th>3/1/20</th>\n",
              "      <th>3/2/20</th>\n",
              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>33.0000</td>\n",
              "      <td>65.0000</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>28.0339</td>\n",
              "      <td>1.6596</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andorra</th>\n",
              "      <td>42.5063</td>\n",
              "      <td>1.5218</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>-38.4161</td>\n",
              "      <td>-63.6167</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Armenia</th>\n",
              "      <td>40.0691</td>\n",
              "      <td>45.0382</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    Lat     Long  1/22/20  ...  3/2/20  3/3/20  3/4/20\n",
              "Country/Region                             ...                        \n",
              "Afghanistan     33.0000  65.0000        0  ...       1       1       1\n",
              "Algeria         28.0339   1.6596        0  ...       3       5      12\n",
              "Andorra         42.5063   1.5218        0  ...       1       1       1\n",
              "Argentina      -38.4161 -63.6167        0  ...       0       1       1\n",
              "Armenia         40.0691  45.0382        0  ...       1       1       1\n",
              "\n",
              "[5 rows x 45 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gEK8hkqzi7BS",
        "outputId": "e2da8684-d58e-4fc7-fe41-e0a4e6dd9db4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        }
      },
      "source": [
        "confirmed_by_country.sample(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
              "      <th>1/23/20</th>\n",
              "      <th>1/24/20</th>\n",
              "      <th>1/25/20</th>\n",
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              "      <th>2/3/20</th>\n",
              "      <th>2/4/20</th>\n",
              "      <th>2/5/20</th>\n",
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              "      <th>2/7/20</th>\n",
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              "      <th>2/17/20</th>\n",
              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
              "      <th>2/21/20</th>\n",
              "      <th>2/22/20</th>\n",
              "      <th>2/23/20</th>\n",
              "      <th>2/24/20</th>\n",
              "      <th>2/25/20</th>\n",
              "      <th>2/26/20</th>\n",
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              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
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              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Portugal</th>\n",
              "      <td>39.39990</td>\n",
              "      <td>-8.2245</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pakistan</th>\n",
              "      <td>30.37530</td>\n",
              "      <td>69.3451</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>36.00000</td>\n",
              "      <td>138.0000</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>29</td>\n",
              "      <td>43</td>\n",
              "      <td>59</td>\n",
              "      <td>66</td>\n",
              "      <td>74</td>\n",
              "      <td>84</td>\n",
              "      <td>94</td>\n",
              "      <td>105</td>\n",
              "      <td>122</td>\n",
              "      <td>147</td>\n",
              "      <td>159</td>\n",
              "      <td>170</td>\n",
              "      <td>189</td>\n",
              "      <td>214</td>\n",
              "      <td>228</td>\n",
              "      <td>241</td>\n",
              "      <td>256</td>\n",
              "      <td>274</td>\n",
              "      <td>293</td>\n",
              "      <td>331</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Indonesia</th>\n",
              "      <td>-0.78930</td>\n",
              "      <td>113.9213</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Switzerland</th>\n",
              "      <td>46.81820</td>\n",
              "      <td>8.2275</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>18</td>\n",
              "      <td>27</td>\n",
              "      <td>42</td>\n",
              "      <td>56</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Macau</th>\n",
              "      <td>22.16670</td>\n",
              "      <td>113.5500</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Others</th>\n",
              "      <td>35.44370</td>\n",
              "      <td>139.6380</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>61</td>\n",
              "      <td>61</td>\n",
              "      <td>64</td>\n",
              "      <td>135</td>\n",
              "      <td>135</td>\n",
              "      <td>175</td>\n",
              "      <td>175</td>\n",
              "      <td>218</td>\n",
              "      <td>285</td>\n",
              "      <td>355</td>\n",
              "      <td>454</td>\n",
              "      <td>542</td>\n",
              "      <td>621</td>\n",
              "      <td>634</td>\n",
              "      <td>634</td>\n",
              "      <td>634</td>\n",
              "      <td>691</td>\n",
              "      <td>691</td>\n",
              "      <td>691</td>\n",
              "      <td>705</td>\n",
              "      <td>705</td>\n",
              "      <td>705</td>\n",
              "      <td>705</td>\n",
              "      <td>705</td>\n",
              "      <td>705</td>\n",
              "      <td>706</td>\n",
              "      <td>706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>1035.61502</td>\n",
              "      <td>3457.8300</td>\n",
              "      <td>547</td>\n",
              "      <td>639</td>\n",
              "      <td>916</td>\n",
              "      <td>1399</td>\n",
              "      <td>2062</td>\n",
              "      <td>2863</td>\n",
              "      <td>5494</td>\n",
              "      <td>6070</td>\n",
              "      <td>8124</td>\n",
              "      <td>9783</td>\n",
              "      <td>11871</td>\n",
              "      <td>16607</td>\n",
              "      <td>19693</td>\n",
              "      <td>23680</td>\n",
              "      <td>27409</td>\n",
              "      <td>30553</td>\n",
              "      <td>34075</td>\n",
              "      <td>36778</td>\n",
              "      <td>39790</td>\n",
              "      <td>42306</td>\n",
              "      <td>44327</td>\n",
              "      <td>44699</td>\n",
              "      <td>59832</td>\n",
              "      <td>66292</td>\n",
              "      <td>68347</td>\n",
              "      <td>70446</td>\n",
              "      <td>72364</td>\n",
              "      <td>74139</td>\n",
              "      <td>74546</td>\n",
              "      <td>74999</td>\n",
              "      <td>75472</td>\n",
              "      <td>76922</td>\n",
              "      <td>76938</td>\n",
              "      <td>77152</td>\n",
              "      <td>77660</td>\n",
              "      <td>78065</td>\n",
              "      <td>78498</td>\n",
              "      <td>78824</td>\n",
              "      <td>79251</td>\n",
              "      <td>79826</td>\n",
              "      <td>80026</td>\n",
              "      <td>80151</td>\n",
              "      <td>80271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Oman</th>\n",
              "      <td>21.00000</td>\n",
              "      <td>57.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>12</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>43.00000</td>\n",
              "      <td>12.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>20</td>\n",
              "      <td>62</td>\n",
              "      <td>155</td>\n",
              "      <td>229</td>\n",
              "      <td>322</td>\n",
              "      <td>453</td>\n",
              "      <td>655</td>\n",
              "      <td>888</td>\n",
              "      <td>1128</td>\n",
              "      <td>1694</td>\n",
              "      <td>2036</td>\n",
              "      <td>2502</td>\n",
              "      <td>3089</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Lat       Long  1/22/20  ...  3/2/20  3/3/20  3/4/20\n",
              "Country/Region                                  ...                        \n",
              "Portugal          39.39990    -8.2245        0  ...       2       2       5\n",
              "Pakistan          30.37530    69.3451        0  ...       4       5       5\n",
              "Japan             36.00000   138.0000        2  ...     274     293     331\n",
              "Indonesia         -0.78930   113.9213        0  ...       2       2       2\n",
              "Switzerland       46.81820     8.2275        0  ...      42      56      90\n",
              "Macau             22.16670   113.5500        1  ...      10      10      10\n",
              "Others            35.44370   139.6380        0  ...     705     706     706\n",
              "Mainland China  1035.61502  3457.8300      547  ...   80026   80151   80271\n",
              "Oman              21.00000    57.0000        0  ...       6      12      15\n",
              "Italy             43.00000    12.0000        0  ...    2036    2502    3089\n",
              "\n",
              "[10 rows x 45 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZWSAWTEWjImg",
        "outputId": "a15d4ece-00bc-421c-8b98-f557bf76e412",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 777
        }
      },
      "source": [
        "confirmed_by_country.loc[\"Mainland China\"][2:]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1/22/20      547.0\n",
              "1/23/20      639.0\n",
              "1/24/20      916.0\n",
              "1/25/20     1399.0\n",
              "1/26/20     2062.0\n",
              "1/27/20     2863.0\n",
              "1/28/20     5494.0\n",
              "1/29/20     6070.0\n",
              "1/30/20     8124.0\n",
              "1/31/20     9783.0\n",
              "2/1/20     11871.0\n",
              "2/2/20     16607.0\n",
              "2/3/20     19693.0\n",
              "2/4/20     23680.0\n",
              "2/5/20     27409.0\n",
              "2/6/20     30553.0\n",
              "2/7/20     34075.0\n",
              "2/8/20     36778.0\n",
              "2/9/20     39790.0\n",
              "2/10/20    42306.0\n",
              "2/11/20    44327.0\n",
              "2/12/20    44699.0\n",
              "2/13/20    59832.0\n",
              "2/14/20    66292.0\n",
              "2/15/20    68347.0\n",
              "2/16/20    70446.0\n",
              "2/17/20    72364.0\n",
              "2/18/20    74139.0\n",
              "2/19/20    74546.0\n",
              "2/20/20    74999.0\n",
              "2/21/20    75472.0\n",
              "2/22/20    76922.0\n",
              "2/23/20    76938.0\n",
              "2/24/20    77152.0\n",
              "2/25/20    77660.0\n",
              "2/26/20    78065.0\n",
              "2/27/20    78498.0\n",
              "2/28/20    78824.0\n",
              "2/29/20    79251.0\n",
              "3/1/20     79826.0\n",
              "3/2/20     80026.0\n",
              "3/3/20     80151.0\n",
              "3/4/20     80271.0\n",
              "Name: Mainland China, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "beiHbO2wjRaR",
        "outputId": "0905e40e-8087-458c-dfaa-d093a0c67612",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        }
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# grafico extremamente apertado\n",
        "# estamos sendo longe do adequado ao passar uma mensagem errada\n",
        "\n",
        "plt.figure(figsize=(2,5))\n",
        "confirmed_by_country.loc[\"Mainland China\"][2:].plot()\n",
        "plt.title(\"Casos confirmados em 'Mainland China'\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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VJwNTgOPAs8A3gFdUtQB4xd0Hr9R2gfu7DfglgIj0B76NV4RzGvDtpjcMN87nfY8LpBZg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\nt64AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 144x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "54Y3cU0iIKCL"
      },
      "source": [
        "Nos últimos 20 dias desses dados, DOBROU os casos confirmados\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kYsx3ckgjdRo",
        "outputId": "0f85073c-62ce-4a02-baec-02b13eead9c2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        }
      },
      "source": [
        "# por isso em data visualization é FUNDAMENTAL\n",
        "# estarmos atentos aos DOIS EIXOS\n",
        "# esse aqui esta tentando comparar o crescimento do momento inicial ao momento atual\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "confirmed_by_country.loc[\"Mainland China\"][2:].plot()\n",
        "plt.title(\"Casos confirmados em 'Mainland China'\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vcDgahlQ7x/51R2iMlfPl+G0VNaEJQ0ur6iivqqW0qpay6gPrDdvKfHlZVS17S6vZUVhB\nfln1QTFEGAxKjmNISh8mDkvhwhPSGdKvD0NS4kjv24eBSbH0i48hIqJ3jbnqKZSIiYiIhNlbWsV/\nPtzFv1bu4J1NBbRyntA2MYOEmCjiYyJJjI0iITaKfgkxHD+kL0NS4hjSrw8ZffuQkdKHwX3jiO4F\ndw/2VkrERESk19tXVs1/Vu/i3yt38uaGvdQ7GJmWwHWnjyQp7sAdfmZgmH8/eD203TCgj5+5vWEG\n94Zkq2G9T3SkerAEUCImIiK9VFF5DS+sCSVfb+TspbbeMXxAPF87czQXnZjOcYOTet0UC9L5lIiJ\niEivUVJZw4trdvOvlTt57eM8auocQ/v14drTR/KpE9MZn5Gs5Es6lRIxERHpcapr69ldXMmu4kp2\nFFawq6iS5Vv2sWR9HtW19WT0jWP2qcP51IkZnDi0r5IvCYwSMRER6VaqauvYXVTFzqIKn2hVsquo\ngp1Flftfe0urDtkvvW8cV049hotOTGfSsBSN0ZIuQYmYiIh0Cc45Cstr2OV7snYX+ffiSnYVVbLL\nP2qnoNH0DgBJcVFk9A3dYTg+I5n0vn1I7xvH4L5x+9+TeshDoqVnUSImIiIdqr7esa+8ev+M73uK\nD8z+vqek6qCEq6r20EftpCbGMCg5joy+cUzKTGFw8oEEK90nX4mapFS6Kf3miojIUduSX8ar6/PY\nE/Zcw4blvaVV1B7mUTtp/pE6E4elMLhvHIOS43yi1fConTg9w1B6NCViIiJyROrqHYvX7eGRpVtY\nsj4P50KzwKcmHnisztj0pP2P3UlLimNgcsOyHrUjAkrERESkjfaWVvH48m38delWcgsrGJQcy83n\nZHHJ5KFkpPQhUoPgRVpNiZiIiLTIOceKLft4ZOkWnlu1k5o6x6mjBvCji8byyXGD9AgekSOkRExE\nRA6rrKqWf7yfyyNvbWHtrhKSYqO4YuoxXDktk9EDk4IOT6TbUyImIiKH+Hh3CY8u3cJT7+ZSWlXL\n2PRkfvXZE5g5MYP4GP3pEGkv+tckIiJAaJqJxev38MBrm3hzQz4xkRFcdGI6V047hsmZKZp9XqQD\nKBETEenlKmvqePrdXB58fSMb8soYnBzH92aM4bLsYQxIjA06PJEeTYmYiEgvtbe0igVvbeHRpVso\nKKtmfEYyf7hsIhedmK7B9yKdRImYiEgv8/HuEh54bRPPvJ9LdW09nxw7kGtOG8m0kf11+VGkk7WY\niJnZGOCxsKKRwI+BBb58OLAZuNQ5t89C/4r/CFwIlAOznXPv+mPNAn7kj3O7c26+Lz8JeBjoAzwH\n3OycO3QaZhEROSLOOd7Iyef+1zayZH0esVERfP6koXz5tBGMSksMOjyRXqvFRMw5tw6YCGBmkUAu\n8AxwC/CSc+4OM7vFr38fuADI8q+pwL3AVDPrD9wGZAMOWGFmi5xz+3yd64C3CSViM4Dn2/E8RUR6\nparaOv75wU4eeG0ja3eVkJoYy7fPPZYrph1D/4SYoMMT6fXaemnyHGCDc26Lmc0EzvTl84HFhBKx\nmcAC36O11MxSzCzd133ROVcAYGYvAjPMbDGQ7Jxb6ssXABejRExE5IhVVNfxt3e2ct+SDewpqWLM\noCTu/NyJfGZCBnHRkUGHJyJeWxOxy4G/++VBzrmdfnkXMMgvDwG2he2z3Zc1V769iXIREWmjsqpa\nHl26hftf28je0mqmjezP/35+AmdkpWr8l0gX1OpEzMxigM8Atzbe5pxzZtbhY7rMbA4wByAzM7Oj\nP05EpNsorqxhwZubefD1Tewrr+H0rFRuOieLk4f3Dzo0EWlGW3rELgDedc7t9uu7zSzdObfTX3rc\n48tzgWFh+w31ZbkcuJTZUL7Ylw9tov4hnHNzgbkA2dnZGswvIr1eUXkN897YxENvbKK4spazjxvI\n188ezaTMfkGHJiKt0JZE7AscuCwJsAiYBdzh358NK7/RzBYSGqxf5JO1F4BfmlnDt8N5wK3OuQIz\nKzazaYQG618F/PmIz0hEpBcoKKvmwdc3Mv/NLZRW1XLeuEF8/ewsThjaN+jQRKQNWpWImVkCcC7w\nlbDiO4DHzewaYAtwqS9/jtDUFTmEpq+4GsAnXD8Hlvl6P2sYuA98jQPTVzyPBuqLiDQpr6SKB17b\nyCNLt1BRU8eFJ6Rz41mjGZueHHRoInIErLtO15Wdne2WL18edBgiIp1iV1Elc1/dyN/e2UJ1bT2f\nmZDBjWePZvTApKBDE5FWMLMVzrnsxuWaWV9EpAvbkl/GX5Zs5KkV26lzjv+ZNIQbzhrNiNSEoEMT\nkXagRExEpAtav7uEe17JYdEHO4iKjODSk4fylTNGMax/fNChiUg7UiImItKFrNxeyN2v5PDC6t3E\nx0Ry7ekjufa0EQxMjgs6NBHpAErERES6gLc35nPXKzm89vFekuOiuOmcLK4+dTj99BgikR5NiZiI\nSECccyxen8c9r+SwbPM+UhNjuOWC47hiaiZJcdFBhycinUCJmIhIJ6uvd7ywehd3L87hw9xiMvrG\n8dPPjOeyk4fpOZAivYwSMRGRTvb9p1byxIrtjEhN4M7PncjFE4cQExURdFgiEgAlYiIinej/1uzm\niRXbmXPGSL4/4zgiI/QgbpHeTP8FExHpJEXlNfzgmVUcNziJ75w3RkmYiKhHTESks/zsX2vIL6tm\n3uyTdSlSRAD1iImIdIqX1+7mqXe3c8OZozh+iB7MLSIhSsRERDpYUUUNtz4duiR549lZQYcjIl2I\nLk2KiHSw2/+1hr2l1TxwlS5JisjB9I0gItKBXlm3hydWbOf66SM5YaguSYrIwZSIiYh0kOLKGm59\nahVZAxO56RxdkhSRQykRExHpIL/410fsKankN5+fQGyUZswXkUMpERMR6QBL1ufx2PJtfGX6KCYM\nSwk6HBHpopSIiYi0s+LKGm55aiWjByZysy5JikgzdNekiEg7+9VzH7G7uJKnvnqqHuItIs1Sj5iI\nSDt67eM8/v7ONq47fSSTMvsFHY6IdHFKxERE2klpVS23PLWKkWkJfPPcY4MOR0S6AV2aFBFpJ796\n7iN2FFXw5PW6JCkirdOqHjEzSzGzJ81srZl9ZGanmFl/M3vRzD727/18XTOzP5lZjpmtNLPJYceZ\n5et/bGazwspPMrNVfp8/mZm1/6mKiHScN3L28te3t3LtaSM46RhdkhSR1mntpck/Av9xzh0HTAA+\nAm4BXnLOZQEv+XWAC4As/5oD3AtgZv2B24CpwBTgtobkzde5Lmy/GUd3WiIinae0qpbvPbmSkakJ\nfPu8MUGHIyLdSIuJmJn1Bc4AHgRwzlU75wqBmcB8X20+cLFfngkscCFLgRQzSwfOB150zhU45/YB\nLwIz/LZk59xS55wDFoQdS0Sky/v182vZUVTBnZ87UZckRaRNWtMjNgLIAx4ys/fM7AEzSwAGOed2\n+jq7gEF+eQiwLWz/7b6sufLtTZSLiHR5b27YyyNLt3D1qSPIHt4/6HBEpJtpTSIWBUwG7nXOTQLK\nOHAZEgDfk+XaP7yDmdkcM1tuZsvz8vI6+uNERJrlnOPHz67mmAHxfPd8XZIUkbZrTSK2HdjunHvb\nrz9JKDHb7S8r4t/3+O25wLCw/Yf6subKhzZRfgjn3FznXLZzLjstLa0VoYuIdJxNe8vI2VPKtaeN\noE+MLkmKSNu1mIg553YB28ys4b975wBrgEVAw52Ps4Bn/fIi4Cp/9+Q0oMhfwnwBOM/M+vlB+ucB\nL/htxWY2zd8teVXYsUREuqwl60M989OPHRhwJCLSXbV2HrGvA381sxhgI3A1oSTucTO7BtgCXOrr\nPgdcCOQA5b4uzrkCM/s5sMzX+5lzrsAvfw14GOgDPO9fIiJd2uJ1eYxMTSBzQHzQoYhIN9WqRMw5\n9z6Q3cSmc5qo64AbDnOcecC8JsqXA8e3JhYRka6gsqaOpRvz+eLUzKBDEZFuTI84EhE5Aks35lNV\nW8/0YzVeVUSOnBIxEZEjsGR9HrFREUwbOSDoUESkG1MiJiJyBJasy2PayAGawFVEjooSMRGRNtqa\nX87GvWWcOUaXJUXk6CgRExFpoyXrQ9MmanyYiBwtJWIiIm20ZH0emf3jGZGaEHQoItLNKRETEWmD\nqto63tyQz/Rj0wjNQS0icuSUiImItMHyzfsor67T+DARaRdKxERE2mDxuj3EREZwyihNWyEiR0+J\nmIhIGyxZn8eUEf2Jj2ntE+JERA5PiZiISCvtKKxg/e5S3S0pIu1GiZiISCstWZ8HoPFhItJulIiJ\niLTS4nV7yOgbx+iBiUGHIiI9hBIxEZFWqKmr542cfKaPGahpK0Sk3SgRExFphRVb9lFaVavxYSLS\nrpSIiYi0wpL1eURFGJ8YrWkrRKT9KBETEWmFxevyOOmYfiTFRQcdioj0IErERERasLu4ko92FnPm\nmIFBhyIiPYwSMRGRFjRMW6HxYSLS3pSIiYi0YMn6PAYmxTI2PSnoUESkh1EiJiLSjNq6el5bn8f0\nY9M0bYWItDslYiIizfhgeyHFlbUaHyYiHaJViZiZbTazVWb2vpkt92X9zexFM/vYv/fz5WZmfzKz\nHDNbaWaTw44zy9f/2MxmhZWf5I+f4/fVfztFpEtYvC6PyAjjtKzUoEMRkR6oLT1iZznnJjrnsv36\nLcBLzrks4CW/DnABkOVfc4B7IZS4AbcBU4EpwG0NyZuvc13YfjOO+IxERNrRkvV5TBqWQt8+mrZC\nRNrf0VyanAnM98vzgYvDyhe4kKVAipmlA+cDLzrnCpxz+4AXgRl+W7JzbqlzzgELwo4lIhKYvaVV\nrNxepId8i0iHaW0i5oD/mtkKM5vjywY553b65V3AIL88BNgWtu92X9Zc+fYmykVEAvXaxw3TVmh8\nmIh0jKhW1jvNOZdrZgOBF81sbfhG55wzM9f+4R3MJ4FzADIzMzv640Skl1u8Lo/UxBjGZyQHHYqI\n9FCt6hFzzuX69z3AM4TGeO32lxXx73t89VxgWNjuQ31Zc+VDmyhvKo65zrls51x2WpouFYhIx6mr\nd7y6Po8zstKIiND9QyLSMVpMxMwswcySGpaB84APgUVAw52Ps4Bn/fIi4Cp/9+Q0oMhfwnwBOM/M\n+vlB+ucBL/htxWY2zd8teVXYsUREArEqt4h95TVM1/gwEelArbk0OQh4xs8oEQX8zTn3HzNbBjxu\nZtcAW4BLff3ngAuBHKAcuBrAOVdgZj8Hlvl6P3POFfjlrwEPA32A5/1LRCQwS9blYQanZykRE5GO\n02Ii5pzbCExoojwfOKeJcgfccJhjzQPmNVG+HDi+FfGKiHSKxev3MGFoCv0TYoIORUR6MM2sLyLS\nyL6yaj7YVqiHfItIh1MiJiLSyGs5e6l3aP4wEelwSsRERBpZsi6PfvHRnDg0JehQRKSHUyImIhKm\nvt6xZH0ep2elEalpK0SkgykRExEJs2ZnMXtLqzQ+TEQ6hRIxEZEwS9aHHmt0hhIxEekESsRERMIs\nXreH44ckk5YUG3QoItILKBETEfGKKmp4d2shZ+oh3yLSSZSIiYh4b+Tspa7e6bFGItJplIiJiHhL\n1uWRFBfFpGGatkJEOkdrnjUpItKjOecoqar101akEhWp/6OKSOdQIiYiPVJ1bT0FZdXsLa0iv6ya\n/NKq0HJpNXtLq8kvCy3nl1axt6ya6tp6AM4co/FhItJ5lIiJSI+ybHMB9y7ewCvr9uDcodtjIiNI\nTYxhQGIsqYkxjBmcxIDEGFITYhnUN44Z4wd3ftAi0mspERORbs85x+J1edyzOIdlm/fRPyGGOaeP\nJHNAPAMSQglXamIsAxJjSIyNwkwz5otI16BETES6rdq6ev69aif3Lt7A2l0lZPSN47ZPj+Oyk4cR\nH6OvNxHp+vRNJSLdTmVNHU+9u537lmxka0E5owcm8pvPT2DmxAyiNdBeRLoRJWIi0m2UVNbw17e3\n8uDrm8grqWLCsBR+eNFYzh07iAg9oFtEuiElYiLS5e0treLhNzaz4K3NFFfWctroVP542UROGTVA\n471EpFtTIiYiXVZxZQ1/fuljHlm6haraemaMH8xXzxzFiUM14aqI9AxKxESky6mvdzy5Yjt3vrCW\n/LJqPjtpKF89cxSjByYGHZqISLtSIiYiXcp7W/fxk0Wr+WB7EScd04+Hr57C8UP6Bh2WiEiHUCIm\nIl3CnpJK7vzPOp5csZ2BSaf/D9QAACAASURBVLH84bKJzJyYoTFgItKjtfo+bzOLNLP3zOxffn2E\nmb1tZjlm9piZxfjyWL+e47cPDzvGrb58nZmdH1Y+w5flmNkt7Xd6ItLVVdfWc/+rGzn7N0t49v1c\nrp8+ipe/cyYXTxqiJExEery29IjdDHwEJPv1XwO/d84tNLO/ANcA9/r3fc650WZ2ua93mZmNAy4H\nxgMZwP+Z2bH+WHcD5wLbgWVmtsg5t+Yoz01EurhX1+fx03+uZkNeGWeNSePHnx7PiNSEoMMSEek0\nreoRM7OhwEXAA37dgLOBJ32V+cDFfnmmX8dvP8fXnwksdM5VOec2ATnAFP/Kcc5tdM5VAwt9XRHp\nobbml3PdguVcNe8d6uod82Zn89DVU5SEiUiv09oesT8A3wOS/PoAoNA5V+vXtwND/PIQYBuAc67W\nzIp8/SHA0rBjhu+zrVH51Dacg4h0E+XVtdy7eAP3vbqRqAjj+zOO48unDSc2KjLo0EREAtFiImZm\nnwL2OOdWmNmZHR9Ss7HMAeYAZGZmBhmKiLTRmxv28t0nVpJbWMHFEzO45YKxDO4bF3RYIiKBak2P\n2CeAz5jZhUAcoTFifwRSzCzK94oNBXJ9/VxgGLDdzKKAvkB+WHmD8H0OV34Q59xcYC5Adna2a0Xs\nIhKwqto6fvvf9dz/2kZGDEjgietP4eTh/YMOS0SkS2hxjJhz7lbn3FDn3HBCg+1fds5dAbwCfM5X\nmwU865cX+XX89pedc86XX+7vqhwBZAHvAMuALH8XZoz/jEXtcnYiEqh1u0qYedcbzH11I1+cksm/\nbjpNSZiISJijmUfs+8BCM7sdeA940Jc/CDxiZjlAAaHECufcajN7HFgD1AI3OOfqAMzsRuAFIBKY\n55xbfRRxiUjA6usdD725mV//Zy3JcVHMm53N2ccNCjosEZEux0KdVd1Pdna2W758edBhiEgju4oq\n+c4TH/B6zl4+OXYgd1xyIqmJsUGHJSISKDNb4ZzLblyumfVFpN08t2ontz69iuraen75PyfwhSnD\nNCmriEgzlIiJyFErqazhJ4vW8NS725kwtC+/v2wiI9P0gG4RkZYoERORo7JscwHffOx9dhRWcNPZ\no/n6OVlER7b66WkiIr2aEjEROSLVtfX88aX13Lt4A0P7xfPE9adw0jG6I1JEpC2UiIlIm63bVcJ3\nnviAVblFXJo9lB9/ejyJsfo6ERFpK31zikirVdbU8eeXP+a+JRtJioviL1dOZsbx6UGHJSLSbSkR\nE5FWeSNnLz98ZhWb88u5ZPJQfnjRWPonxAQdlohIt6ZETESaVVBWze3/XsPT7+YyfEA8f712Kp8Y\nnRp0WCIiPYISMRFpknOOp9/N5fZ/r6GkspYbzxrNjWePJi46MujQRER6DCViInKIzXvL+OE/VvFG\nTj6TM1P41WdPZMzgpKDDEhHpcZSIich+NXX1zH11I3966WNiIiO4/eLj+eKUTCIiNDu+iEhHUCIm\nIgCs2LKPHzy9inW7S7jwhMHc9unxDEqOCzosEZEeTYmYSC9XUlnDnf9Zx6Nvb2Fwchz3X5XNueMG\nBR2WiEivoERMpBfbkFfKdfOXsym/jNmnDufb543RxKwiIp1I37givdSS9Xnc+Ld3iYmMYOF105g6\nckDQIYmI9DpKxER6GeccD76+iV8+9xFjBidz/1UnMbRffNBhiYj0SkrERHqRqto6fvjMhzy5YjsX\nHD+Y3146gfgYfQ2IiARF38AivcSekkquf2QF724t5BufzOKms7M0LYWISMCUiIn0Aqu2FzHnkeUU\nltdw7xWTueAEPahbRKQrUCIm0sP984MdfPfJDxiQEMtTXz2VcRnJQYckIiKeEjGRHqq+3vG7F9dz\n1ys5nDy8H/deeRKpibFBhyUiImGUiIn0QKVVtXzzsfd5cc1uLj95GD+beTwxURFBhyUiIo20+M1s\nZnFm9o6ZfWBmq83sp758hJm9bWY5ZvaYmcX48li/nuO3Dw871q2+fJ2ZnR9WPsOX5ZjZLe1/miK9\nx7aCci65501eXruHn3x6HL/67AlKwkREuqjWfDtXAWc75yYAE4EZZjYN+DXwe+fcaGAfcI2vfw2w\nz5f/3tfDzMYBlwPjgRnAPWYWaWaRwN3ABcA44Au+roi00Vsb8vnMXa+zq7iS+VdPYfYnRmCmOyNF\nRLqqFhMxF1LqV6P9ywFnA0/68vnAxX55pl/Hbz/HQn8JZgILnXNVzrlNQA4wxb9ynHMbnXPVwEJf\nV0Raqa7e8aeXPuaKB5YyIDGWZ2/4BKdlpQYdloiItKBVY8R8r9UKYDSh3qsNQKFzrtZX2Q4M8ctD\ngG0AzrlaMysCBvjypWGHDd9nW6PyqW0+E5FeandxJTcvfI+lGwu4eGIGP7/4eJLiooMOS0REWqFV\niZhzrg6YaGYpwDPAcR0a1WGY2RxgDkBmZmYQIYh0KS+v3c13nlhJRXUdv/n8BC6ZPESXIkVEupE2\n3TXpnCs0s1eAU4AUM4vyvWJDgVxfLRcYBmw3syigL5AfVt4gfJ/DlTf+/LnAXIDs7GzXlthFepLq\n2nru/M9aHnh9E2PTk7nri5MYlZYYdFgiItJGrblrMs33hGFmfYBzgY+AV4DP+WqzgGf98iK/jt/+\nsnPO+fLL/V2VI4As4B1gGZDl78KMITSgf1F7nJxIT7R5bxmX3PsmD7y+idmnDueZr52qJExEpJtq\nTY9YOjDfjxOLAB53zv3LzNYAC83sduA94EFf/0HgETPLAQoIJVY451ab2ePAGqAWuMFf8sTMbgRe\nACKBec651e12hiI9yD/ey+WHz6wiKjKCuV86ifPGDw46JBEROQoW6qzqfrKzs93y5cuDDkOkU5RV\n1XLbotU8uWI7Jw/vxx8vn0RGSp+gwxIRkVYysxXOuezG5ZpZX6SLW72jiK///T027S3jpnOyuOns\n0URFaoJWEZGeQImYSBflnGPBW1v4xXMf0S8+mr9eO5VTR2luMBGRnkSJmEgXVFJZw7cf/4D/rtnN\nWWPS+M3nJzBAD+wWEelxlIiJdDE7iyq4+qFl5Owp5UcXjeWa0/SYIhGRnkqJmEgXsnpHEV9+eBll\nVXU8dPXJnJ6VFnRIIiLSgZSIiXQRS9bn8bVHV5DcJ5onv3oKxw1ODjokERHpYErERLqAv7+zlR/9\n40PGDErioatPZlByXNAhiYhIJ1AiJhKg+nrHb/67jnsWb2D6sWncfcVkEmP1z1JEpLfQN75IQKpq\n6/juEytZ9MEOvjAlk5/PHK/5wUREehklYiIBKCyvZs4jK3hnUwHfn3Ec108fqTsjRUR6ISViIp1s\na345sx9+h+0FFfzpC5P4zISMoEMSEZGAKBET6UTvbyvk2vnLqK13PHrtVKaM6B90SCIiEiAlYiKd\n5IXVu7h54XsMTIrjoatPZlRaYtAhiYhIwJSIiXSCea9v4uf/XsOEoSk8MCubVD2uSEREUCIm0qGc\nc/zq+bXMfXUj548fxB8um0SfmMigwxIRkS5CiZhIB6mrd/zg6VU8tnwbs045hh9/ejyREbozUkRE\nDlAiJtIBqmrr+MbC93n+w13cfE4W3/hklqanEBGRQygRE2lnZVW1fOWRFbyes5cff2ocXz5tRNAh\niYhIF6VETKQdFZZXM/uhZazKLeI3n5/A504aGnRIIiLShSkRE2knu4sruerBd9i0t4x7rpjM+eMH\nBx2SiIh0cUrERNrBlvwyrnzwbQpKq3n46pM5dXRq0CGJiEg3oERM5Cit3VXMlx58h5q6ev563TQm\nDksJOiQREekmIlqqYGbDzOwVM1tjZqvN7GZf3t/MXjSzj/17P19uZvYnM8sxs5VmNjnsWLN8/Y/N\nbFZY+Ulmtsrv8yfT7WXSTby7dR+X3beUSDOe+MopSsJERKRNWkzEgFrg2865ccA04AYzGwfcArzk\nnMsCXvLrABcAWf41B7gXQokbcBswFZgC3NaQvPk614XtN+PoT02kY732cR5X3P82/eKjeeL6U8ga\nlBR0SCIi0s20mIg553Y65971yyXAR8AQYCYw31ebD1zsl2cCC1zIUiDFzNKB84EXnXMFzrl9wIvA\nDL8t2Tm31DnngAVhxxLpkp5btZMvP7yMYwbE8/j1pzCsf3zQIYmISDfUpjFiZjYcmAS8DQxyzu30\nm3YBg/zyEGBb2G7bfVlz5dubKBfpkh5btpVbn17FpMx+zJt9Mn37RAcdkoiIdFOtTsTMLBF4CviG\nc644fBiXc86ZmeuA+BrHMIfQ5U4yMzM7+uNEDlJf77j7lRx+++J6ph+bxr1XTiY+Rve7iIjIkWvN\nGDHMLJpQEvZX59zTvni3v6yIf9/jy3OBYWG7D/VlzZUPbaL8EM65uc65bOdcdlpaWmtCF2kXu4sr\n+dK8t/nti+uZOTGD+6/KVhImIiJHrTV3TRrwIPCRc+53YZsWAQ13Ps4Cng0rv8rfPTkNKPKXMF8A\nzjOzfn6Q/nnAC35bsZlN8591VdixRAL34prdzPjDq7y7pZA7PnsCf7hsIjFRrfo/jIiISLNa81/6\nTwBfAlaZ2fu+7AfAHcDjZnYNsAW41G97DrgQyAHKgasBnHMFZvZzYJmv9zPnXIFf/hrwMNAHeN6/\nRAJVWVPHL/79EY8s3cK49GT+9IVJjB6YGHRYIiLSg1joRsXuJzs72y1fvjzoMKSHWrurmJv+/h7r\nd5dy3ekj+M75Y4iNigw6LBER6abMbIVzLrtxuQa5iIRxzrHgrS384rmPSI6LZv6XpzD9WI1HFBGR\njqFETMTLL63ie0+u5KW1ezhrTBr/+/kJpCbGBh2WiIj0YErERIDXP97Ltx5/n8LyGm779Dhmnzoc\nPWlLREQ6mhIx6dWqa+v57X/Xcd+rGxk9MJGHr57CuIzkoMMSEZFeQomY9Fob80q5eeH7rMot4oqp\nmfzoonH0idGAfBER6TxKxKRX+jC3iMvnLiUq0rjvSydx/vjBQYckIiK9kBIx6XU27y1j9kPv0LdP\nNI9ffwpDUvoEHZKIiPRSmh5cepU9JZVcNe8d6uodC66ZoiRMREQCpR4x6TVKKmuYPW8ZeSVV/O26\nqYxK0yz5IiISLPWISa9QVVvHVx5ZwfrdJdx75WQmZfYLOiQRERH1iEnPV1fv+NZjH/Dmhnx+d+kE\nzhwzMOiQREREAPWISQ/nnOOn/1zNv1ft5AcXHsdnJw8NOiQREZH9lIhJj3b3KzkseGsL150+gjln\njAo6HBERkYMoEZMea+E7W/nNf9fzP5OGcOsFY4MOR0RE5BBKxKRHenHNbn7wzCqmH5vGnZ87kYgI\nPTdSRES6HiVi0uMs31zAjX97lxOG9OWeKyYTHalfcxER6Zr0F0p6lPW7S/jyw8sYktKHebNPJiFW\nNwaLiEjXpURMeozcwgquevAd4qIjmf/lKQxIjA06JBERkWapu0B6hH1l1Vz14NuUVdfy+FdOYVj/\n+KBDEhERaZF6xKTbKyir5svzl7FtXwX3X5XN2PTkoEMSERFpFfWISbe1p7iS+1/byKNLt1JdV8/d\nX5zEtJEDgg5LRESk1ZSISbezo7CC+5Zs4O/LtlFbV8/MiUO44axRjB6YFHRoIiIibdJiImZm84BP\nAXucc8f7sv7AY8BwYDNwqXNun5kZ8EfgQqAcmO2ce9fvMwv4kT/s7c65+b78JOBhoA/wHHCzc861\n0/lJD7KtoJx7Fufw5IrtOAeXTB7KV88cxfDUhKBDExEROSKt6RF7GLgLWBBWdgvwknPuDjO7xa9/\nH7gAyPKvqcC9wFSfuN0GZAMOWGFmi5xz+3yd64C3CSViM4Dnj/7UpKfYmFfK3a9s4B/v5xJpxmUn\nD+P66aMY2k8D8kVEpHtrMRFzzr1qZsMbFc8EzvTL84HFhBKxmcAC36O11MxSzCzd133ROVcAYGYv\nAjPMbDGQ7Jxb6ssXABejREyAdbtKuOuVHP69cgcxURHMOmU4X5k+kkHJcUGHJiIi0i6OdIzYIOfc\nTr+8Cxjkl4cA28LqbfdlzZVvb6JcerEPc4u46+Uc/rN6Fwkxkcw5YxTXnj6CVM0LJiIiPcxRD9Z3\nzjkz65QxXWY2B5gDkJmZ2RkfKZ2ksqaOF1bv4rFl23hzQz5JcVHcdE4WV586nH4JMUGHJyIi0iGO\nNBHbbWbpzrmd/tLjHl+eCwwLqzfUl+Vy4FJmQ/liXz60ifpNcs7NBeYCZGdna0B/D/BhbhGPL9/G\nP97LpbiylqH9+vDd88fwpVOOITkuOujwREREOtSRJmKLgFnAHf792bDyG81sIaHB+kU+WXsB+KWZ\n9fP1zgNudc4VmFmxmU0jNFj/KuDPRxiTdBNFFTUsej+Xx5Zv48PcYmKiIpgxfjCXnTyMU0YOICLC\ngg5RRESkU7Rm+oq/E+rNSjWz7YTufrwDeNzMrgG2AJf66s8Rmroih9D0FVcD+ITr58AyX+9nDQP3\nga9xYPqK59FA/R6pvt6xdFM+jy/bxvMf7qKqtp5x6cn89DPjmTkxg5R4XX4UEZHex7rrlF3Z2dlu\n+fLlQYchLdhVVMmTK7bx+PLtbC0oJykuiosnDuGyk4dx/JC+QYcnIiLSKcxshXMuu3G5ZtaXDrFi\nyz7uXbyBl9fupt7BtJH9+ea5WVxwfDpx0ZFBhyciItIlKBGTduOc480N+dz1cg5vbcwnJT6a66eP\n4tLsYZr9XkREpAlKxOSo1dc7Xlq7h7teyeGDbYUMTIrlRxeN5QtTMkmI1a+YiIjI4eivpByxunrH\nv1bu4N7FG1i7q4Rh/fvwi/85nksmD9XlRxERkVZQIiZtVl1bzzPvbefexRvYnF/O6IGJ/O7SCXxm\nQgZRkRFBhyciItJtKBGTVquormPhsq3MfXUjO4sqOX5IMn+5cjLnjRusub9ERESOgBIxOayq2jq2\n76tga0E5K7cVseCtzeSXVTNleH/uuOREzshKxUwJmIiIyJFSItaLOefYV17D1oLy0Cu/jK0F5WzJ\nL2dbQTk7iysJn2Zu+rFp3HDWaKaM6B9c0CIiIj2IErFe5pV1e3hi+TY27w0lWyVVtQdtH5gUS2b/\neKaNGkBm/3gy+8dzzIB4MvsnkJYUG1DUIiIiPZMSsV5iZ1EFP/vnGp7/cBeDk+MYm57ElBH9GRaW\nbA3rF0+fGN3tKCIi0lmUiPVwtXX1PPzmZn734nrq6h3fPX8M150+kpgo3d0oIiISNCViPdiKLQX8\n8JkPWburhLPGpPGzmcczrH980GGJiIiIp0SsB9pXVs2v/7OWhcu2kd43jr9ceRLnjx+kOxxFRES6\nGCViPYhzjidWbOeO59dSVFHDnDNGcvM5WXrMkIiISBelv9A9xLpdJfzoH6tYtnkfJx3Tj9svPp6x\n6clBhyUiIiLNUCLWzZVX1/LHlz7mwdc2kRgXxa8vOYHPnzRMM92LiIh0A0rEuqHy6lrW7iph1fYi\n5r66kdzCCi7NHsotF4ylf0JM0OGJiIhIKykR6+L2lFSyZkcxa3YW73/ftLds/4z3xw1O4onrT+Hk\n4ZrtXkREpLtRItZF1NU7Nu0tZXVY0vXRzmL2llbvrzO0Xx/GpSfzmQkZjEtPZlxGMkNS+uhuSBER\nkW5KiVgnK62qZWNeKRvyStmYV8aGvFI27CljU34Z1bX1AMRERpA1KJGzxgxkXEYy49KTOS49mb59\nogOOXkRERNqTErEOUF/v2FFUwYa8skOSrt3FVfvrRUYYx/SPZ2RaAtPHpHHc4CTGZSQzKi2R6EjN\nfC8iItLTKRE7AsWVNewsrGRHUQU7CyvZVVTBjqJKdvr1HUUVVNbU76+fHBfFqIGJnJ6Vxsi0BEal\nJTIqLYHM/gl61JCIiEgv1mUSMTObAfwRiAQecM7d0VmfXV1bT1FFDcWVNaH3Cv9eWUt+adWBpKuo\nkl1FlZRW1R60f4TBwKQ40lPiGJuezDljBzIyLZGRqQmMGpjIgIQYjeMSERGRQ3SJRMzMIoG7gXOB\n7cAyM1vknFtzuH2KKmp49v1cauoctXX11NTVU1PnqKmrp7beUV1bT239gbKaunrKqurCkqzQe1FF\nzUG9V01JTYwlIyWOUWkJnDY6lYyUONL79tn/PjAplihdShQREZE26hKJGDAFyHHObQQws4XATOCw\nidjWgnJuXvh+sweNijCiIo3oyAiiIyOIj4mkb59okuOiGZmaSHKfqP3rfeP9e5/og8pT4mN0+VBE\nREQ6RFdJxIYA28LWtwNTm9sha2Aiz357OtEREURHGVEREcRERuxPvKIiTLPLi4iISJfWVRKxVjGz\nOcAcgMzMTEalJQYckYiIiMiR6yrX3HKBYWHrQ33ZQZxzc51z2c657LS0tE4LTkRERKQjdJVEbBmQ\nZWYjzCwGuBxYFHBMIiIiIh2qS1yadM7VmtmNwAuEpq+Y55xbHXBYIiIiIh2qSyRiAM6554Dngo5D\nREREpLN0lUuTIiIiIr2OEjERERGRgCgRExEREQmIEjERERGRgCgRExEREQmIEjERERGRgJhzLugY\njoiZlQDrgo6jC0gF9gYdRBegdjhAbRGidjhAbRGidjhAbRHSme1wjHPukMcCdZl5xI7AOudcdtBB\nBM3Mlqsd1A7h1BYhaocD1BYhaocD1BYhXaEddGlSREREJCBKxEREREQC0p0TsblBB9BFqB1C1A4H\nqC1C1A4HqC1C1A4HqC1CAm+HbjtYX0RERKS76849YiIiIiLdWqcmYmY2z8z2mNmHjcqnmdn9Znau\nma0ws1X+/Wy/Pd7M/m1ma81stZnd0Wj/dDP7r5lNNLO3fJ2VZnZZWJ0RZva2meWY2WNmFtM5Z920\no2iLJDN7P+y118z+ELZ/t2uLBmY2zMxeMbM1Pu6bw7Y1tMsAX6fUzO5q4hi3mNkVZvYtf5yVZvaS\nmR0TVmeWmX3sX7M66/zaojVt4ZdPDPs5rzKzuLB63bItjvb3wMx+YWbbzKy0iWN3m38f7dAOMWY2\n18zWW+i785Kwbd2mHXwsrWmLJr8zfZ3e9DvRXDv0mN+JcGYWZ2bvmNkHPu6fhm273Mx+aKHvwpW+\nXd40swmNjvEXM/uEmf2vb5uVZvaMmaWE1bnVn/s6Mzu/3U7AOddpL+AMYDLwYaPynwKXAJOADF92\nPJDrl+OBs/xyDPAacEHY/lcD3waOBbJ8WQawE0jx648Dl/vlvwBf7cxzb6+2aOI4K4AzunNbhMWe\nDkz2y0nAemBco3ZJAE4DrgfuauIYrwBpwFlAvC/7KvCYX+4PbPTv/fxyv6DP/QjbIgpYCUzw5QOA\nyO7eFkf7ewBM88cobeLY3ebfRzu0w0+B2/1yBJDaHduhDW1x2O/MXvY70Vw79JjfiUbtYkCiX44G\n3gam+fX5wEnAqfjvN+AC4O1Gx3gfiATOA6J82a+BX/vlccAHQCwwAthA2PftUcUfQIMN59Dk43Wg\nbxMNWwDENnGMPwLXha0/1vDL2KjeB0CWP9besMY9BXihC/zyHFVb+H8w2/Bj/bpzWxymfZ4Fzm2q\nXYDZHPqHJxl4o4njTGooB74A3Be27T7gC0Gf65G0BXAh8Ohh6veYtmjr70HYtqb+6Hbbfx9H8O9h\nG5Dw/9s5m9C6iiiO/45GwaKSFqtIoxbBz0ipIgmKCz8KBqqWqotCg8QqCK66EEtJkYouQnVRxIVI\nFqIEg0EFwY/a1kWRakWjlVoR0+iitbQYrFILktrjYs4jk/G+j+S9vJv73vnB4907c2aY+b9z5547\nM/eVqauwOlTTwtLKjZlt4xNZOrSyT0TtXQKMA73W5oNE90izWcrsAPUm4J2MutYDI3a8Fdga5e0C\n7mhEm3PfIyYilwHTqvpnkvUIMK6q/yT2ncCDwF47Px+4QVUPJ3Y9hNmzI4SZglOqetayjwIrGt2X\nepmrFsAGwuyGWvlW0mIlIWg4UEGXlDWYXyQ8AXxsxysIg1GJRdn/mApaXA+oiOwSkXEReTYq1hJa\nzNMPytVV2OtjrjpEyykvmG+MicgVlldYHaBmLcqNmWldhdVirjq0sk9A6IOIfAecBHar6gGCPgdL\n98iIeByEMEP2SUa1m2jCeJl7IEaYBvw0ThCRbsKU4FNJegfwNvCKqk5aci9hGjK2uxJ4C3hcVc8t\nULsXgpq1MDYQ9CjRElqIyMXAu8BmVf2LDF3K0MfsiwsR6QduB15qdDubQRUtOgjLUhvte72I3Gd5\nhdeiDj8oRyGvj3nq0AF0AftV9TbgC+BlyyukDlCbFlXGzJRCajFPHVrSJ0qo6r+quprQxx4RuYXs\ncfAeQiC2JUq+nyQQE5FB4CwwspDthsURiM2KREWkC3gfeExVjyS2rwM/q+rOCuUvBT4EBlX1S0ue\nAjotkIPwQx1raC8aQ81a2EbDDlX9pkL5wmkhIhcQBpgRVX3Pkss9raT0AF9Fda0BBoGHoifjY8BV\nUZlF1f+YGrQ4CuxT1d9V9QzwEWHfIRRcizr9oByFuz7q0GEKOAOUyowx4xuF0wFq06LK/SOLwmlR\nhw4t5xNZqOopwv7YPpIAVURWAcPAOlWdsrQlhD1wv0V2A8ADwMZoNm3hxstmrdtG66orsX1RJOu3\nQKedP5xR7kWC852XpO8HLrHjCwnLMZszyo8xe5Ph083ue6O0sPwh4PlW0SLS4E1gZ5KWtcY/QLQn\nBugGRqPzWwnT6dcl5ZYBvxD2CCy142V5930+Wlj7xwl7IjqAPcDaomtRjx8keaeT80JdH/XqAIwC\n90b5Y0XUoVYtqDJmtotPVNKhlXwiaddyZl4ouIjwQt864PPI5mpgArgzKbsWGIrO+4DDwPLErpvZ\nm/UnKeJmfcIy2nFgmvA0vwV4I8rfBvxNeHuh9LmcEHkq8GOU/qSJ/1lUvt/qjsuvtrxrCTMEE+ZM\n/3sJoAhaRPmTwI2JIxZSi6jNd9nv/H3U5udiXczuV8IG1NOm3c3AM8BAZLMHOBHV80GUt8n6PkGY\nds+973Vo0Q/8ABwC373xeAAAAP5JREFUdlhaobWoxw8sfYedn7Pv7UW8PhqgwzXAPiu/l3AjKpwO\ntWpBhTGznXyiig4t4xOJLquAb61fh0yTR4Htkc0w8EfUp68t/VXg7shugrAXrGT3WpQ3SHio/Yno\nnxvq/eT6z/oisg2YUNXReZbvB7pUdaiq8SLHtcimVl1EZDdhGv54c1rWfNpZC78+Aq7DDK5FwHXI\nRkSGgWGdWVotZzcO9KrqdHNaltGGPAMxx3Ecx3GcdmYxbNZ3HMdxHMdpSzwQcxzHcRzHyQkPxBzH\ncRzHcXLCAzHHcRzHcZyc8EDMcRzHcRwnJzwQcxzHcRzHyQkPxBzHcRzHcXLiP8gsV8unKR1CAAAA\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oUNQcGBsmdto",
        "outputId": "bd7b6845-291d-4cbb-e158-5b82d26c22d8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        }
      },
      "source": [
        "# exemplo ruim de manusear o eixo y\n",
        "# aqui a mensagem ficou novamente diferente\n",
        "\n",
        "# esse aqui esta tentando comparar o momento inicial com 1.386bi (populacao da xchina em 2017)\n",
        "# aqui a mensagem eh novamente completamente diferente\n",
        "# e pode ser uma mensagem ruim, ate mesmo errada. poderai ser uma doenca grave\n",
        "# mas ao usarmos o eixo y com a populacao geral, fingimos que ela nao eh grave\n",
        "# sendo que na realidade ESSE grafico nao POSSUI INFORMACAO NENHUMA sobre a gravidade\n",
        "# da doenca\n",
        "\n",
        "# pq? so tem caso confirmado. nao fala letalidade? nao fala incidencia?\n",
        "# quais sao as provincias infectadas? sao de toda a china? e estou comparando com a\n",
        "# populacao de toda a china. errado.\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "confirmed_by_country.loc[\"Mainland China\"][2:].plot()\n",
        "plt.title(\"Gráfico errado. Passa uma mensagem errada, com comparações injustas.\")\n",
        "plt.ylim(0, 1386000000)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jlHF7FeUbWudQAsjYfv5iyg2+19Y2fY7lx4dWo1j2wNcjM++lfBg8nHI2/gWs+Hp9kHIT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\nGLRdIHEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "enyofh-Gm_fb",
        "outputId": "e961c604-9e79-47fc-8b0b-538e8d8500fa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        }
      },
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "plt.title(\"Casos novos em 'Mainland China'\")\n",
        "new_cases_mainland_china = confirmed_by_country.loc[\"Mainland China\"][2:].diff().dropna()\n",
        "new_cases_mainland_china.plot()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1641f2860>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SguWVdExLJiU5/oMHI3vmaPhSROql0e9AZtYJmAg8DOCcq3DO7QCmAo/71R4H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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z51g5cR7pETn",
        "outputId": "6ff52442-ea13-49b6-c7e7-30e0f2baadd9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        }
      },
      "source": [
        "# não faz sentido um gráfico cujo eixo X são categorias não ordenadas com um gráfico delinha\n",
        "# dá pra ver no gráfico que... não dá para entendê-lo.... por isso vamos tentar em breve\n",
        "# melhorá-lo\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "confirmed_by_country[last_date].plot()\n",
        "plt.title(\"Confirmados por país\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Confirmados por país')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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iBcC+wL3AacC1ETEbuDY9BzgSmJ3+Tga+BiBpe+B04EDgAOD0WvCW6pyUW27e5m2WmdnW\nq7uyYWgyu7J+UK1Gk1tlZmNh2EBM0nbA3wDnA0REd0SsAY4GLkrVLgKOSdNHAxdH5kZgqqSdgSOA\nhRGxKiJWAwuBeWnethFxY0QEcHFuXWZm404tWR/oG6LsqbpXzKyIGukR2x1YCXxT0u2SviFpMrBT\nRDyc6jwC7JSmZwDLc8uvSGVDla+oU25mNi5155P1U0DmPDGzYmokEGsD9gO+FhEvBdaxYRgSgNST\nNeb95pJOlrRI0qKVK1eO9cuZmTVFfmiy9uhAzKyYGgnEVgArIuKm9PxyssDs0TSsSHp8LM1/CJiV\nW35mKhuqfGad8o1ExHkRMTci5k6fPr2BppuZbX26ByTrA07YNyuoYQOxiHgEWC5pr1R0KHAPsACo\nnfk4H/hxml4AnJDOnjwIeDINYV4DHC5pWkrSPxy4Js17StJB6WzJE3LrMjMbd/pdvsJDk2aF1tZg\nvfcB35HUAdwPvJMsiLtM0onAg8BbUt2rgKOAZcD6VJeIWCXpDOCWVO9TEbEqTb8HuBCYCFyd/szM\nxqXu3iodk9JZk7VkffeImRVSQ4FYRNwBzK0z69A6dQM4ZZD1XABcUKd8EbBPI20xMyu6esn6Xe4R\nMyskX1nfzKzF5JP1O52sb1ZoDsTMzFrMwCvrgwMxs6JyIGZm1mLqXr7COWJmheRAzMysxXTlrqxf\n6xlzsr5ZMTkQMzNrMd29vnyF2XjhQMzMrIVERN2hSZ81aVZMDsTMzFpIpRpEbBiS9FmTZsXmQMzM\nrIXUkvKdrG82PjgQMzNrIbWer42S9d0jZlZIDsTMzFpIXyDmHjGzccGBmJlZC+kaGIj5rEmzQnMg\nZmbWQmrXC9swNCnAgZhZUTkQMzNrIQOT9SXR0Vaiy0OTZoXkQMzMrIUMTNavTff0RrOaZGZjyIGY\nmVkLGZisX5vurlSa1SQzG0MOxMzMWkjdQKxcco6YWUE5EDMzayG1HLH28oAeMQdiZoXkQMzMrIXU\nAq7OjYYmHYiZFZEDMTOzFjLwrEnIese6naxvVkgOxMzMWkjdsybdI2ZWWA7EzMxaSL1k/c5yie5e\nnzVpVkQOxMzMWkiPk/XNxpWGAjFJD0haIukOSYtS2faSFkpamh6npXJJOlvSMkmLJe2XW8/8VH+p\npPm58v3T+pelZTXaG2pmtjUYeK/J2rSHJs2KaSQ9Yq+JiDkRMTc9Pw24NiJmA9em5wBHArPT38nA\n1yAL3IDTgQOBA4DTa8FbqnNSbrl5m7xFZmZbsVrA1dkvWV++sr5ZQW3O0OTRwEVp+iLgmFz5xZG5\nEZgqaWfgCGBhRKyKiNXAQmBemrdtRNwYEQFcnFuXmdm4Uj9Zv+weMbOCajQQC+Dnkm6VdHIq2yki\nHk7TjwA7pekZwPLcsitS2VDlK+qUm5mNO929VdpKolTakKHhK+ubFVdbg/UOjoiHJD0HWCjpD/mZ\nERGSxrzfPAWBJwPsuuuuY/1yZmZbXE+l2i9RH7IcsS4HYmaF1FCPWEQ8lB4fA64gy/F6NA0rkh4f\nS9UfAmblFp+ZyoYqn1mnvF47zouIuRExd/r06Y003cxsq9LdW+2XqA9ZvpgvX2FWTMMGYpImS9qm\nNg0cDtwFLABqZz7OB36cphcAJ6SzJw8CnkxDmNcAh0ualpL0DweuSfOeknRQOlvyhNy6zMzGle7K\nxoFYe1nOETMrqEaGJncCrkhXlGgDvhsRP5N0C3CZpBOBB4G3pPpXAUcBy4D1wDsBImKVpDOAW1K9\nT0XEqjT9HuBCYCJwdfozMxt3unqr/RL1IRua7Kn4rEmzIho2EIuI+4F965Q/ARxapzyAUwZZ1wXA\nBXXKFwH7NNBeM7NC6+6t9rt0BUBHuUylGlSqQbnkyyyaFYmvrG9m1kIGS9YHfOakWQE5EDMzayH1\nkvUdiJkVlwMxM7MWUi9Zv/a8q+IzJ82KxoGYmVkL6a6XrF/O8sKcsG9WPA7EzMxaiIcmzcYXB2Jm\nZi2kuxIbJ+uXy9k8B2JmheNAzMyshXT3Vja+fIV7xMwKy4GYmVkLGSpZv9vJ+maF40DMzKyF1EvW\nb0/J+t29TtY3KxoHYmZmLWSwm34Dvt+kWQE5EDMzayE9TtY3G1cciJmZtRBfvsJsfHEgZmbWIiLC\nyfpm44wDMTOzFlHLARt4+Ypasn6Pk/XNCseBmJlZi6gNPW50i6O+e016aNKsaByImZm1iNq9JGs9\nYDWdTtY3KywHYmZmLaKvR6yt3K/cyfpmxeVAzMysRWwIxHzWpNl44UDMzKxF1M6KHBiIlUuiJOhx\njphZ4TgQMzNrEV2DJOtDFpz5yvpmxeNAzMysRdSS9TvatNG8jnLJQ5NmBeRAzMysRWy4fEV5o3kd\nbeW+HjMzK46GAzFJZUm3S7oyPd9d0k2Slkn6nqSOVN6Zni9L83fLreOjqfw+SUfkyuelsmWSThu9\nzTMz23oMlqwP2UVe3SNmVjwj6RF7P3Bv7vnngLMiYg9gNXBiKj8RWJ3Kz0r1kLQ3cBzwImAecG4K\n7srAOcCRwN7A8amumdm4MliyPmTXFnOyvlnxNBSISZoJvA74Rnou4BDg8lTlIuCYNH10ek6af2iq\nfzRwaUR0RcSfgWXAAelvWUTcHxHdwKWprpnZuDLYlfUhJeu7R8yscBrtEfsy8BGgdhTYAVgTEb3p\n+QpgRpqeASwHSPOfTPX7ygcsM1i5mdm40j1Usr7PmjQrpGEDMUmvBx6LiFu3QHuGa8vJkhZJWrRy\n5cpmN8fMbFQNmazvsybNCqmRHrFXAG+Q9ADZsOEhwH8DUyW1pTozgYfS9EPALIA0fzvgiXz5gGUG\nK99IRJwXEXMjYu706dMbaLqZ2dZjqGR9D02aFdOwgVhEfDQiZkbEbmTJ9r+MiLcB1wHHpmrzgR+n\n6QXpOWn+LyMiUvlx6azK3YHZwM3ALcDsdBZmR3qNBaOydWZmW5Hu3qGS9T00aVZEbcNXGdS/AZdK\n+jRwO3B+Kj8f+JakZcAqssCKiLhb0mXAPUAvcEpEVAAkvRe4BigDF0TE3ZvRLjOzrVIt0Brs8hVP\nuEfMrHBGFIhFxPXA9Wn6frIzHgfWeRZ48yDLfwb4TJ3yq4CrRtIWM7OiqV1Zv73sZH2z8cJX1jcz\naxFD3mvSyfpmheRAzMysRXT3Vukol8guvdifk/XNismBmJlZi+jurdbNDwMn65sVlQMxM7MW0V2p\nDBqIdbSV6HGPmFnhOBAzM2sRPb1RN1EfskCsyz1iZoXjQMzMrEV0VwYfmuxMyfrZZRnNrCgciJmZ\ntYhasn49tQCtdokLMysGB2JmZi2iq7dKR9vG95mEDYGYE/bNisWBmJlZixhqaLI99ZQ5Yd+sWByI\nmZm1iJ7eKh1DJOuDe8TMisaBmJlZixiqR6yWO+aLupoViwMxM7MW0UiyfpcDMbNCcSBmZtYihrqy\nfmebe8TMisiBmJlZi8iGJuufNdmXrO8cMbNCcSBmZtYiunurQ15ZH5ysb1Y0DsTMzFpEd6XaNwQ5\nkJP1zYrJgZiZWYtoJFnfgZhZsTgQMzNrEUMl6/usSbNiciBmZtYiGrmOmJP1zYrFgZiZWQuoVINK\nNfrOjhzIQ5NmxeRAzMysBdR6uoYbmvRZk2bF4kDMzKwF1HK/Bk3W91mTZoU0bCAmaYKkmyXdKelu\nSZ9M5btLuknSMknfk9SRyjvT82Vp/m65dX00ld8n6Yhc+bxUtkzSaaO/mWZmra0WYA16+QoPTZoV\nUiM9Yl3AIRGxLzAHmCfpIOBzwFkRsQewGjgx1T8RWJ3Kz0r1kLQ3cBzwImAecK6ksqQycA5wJLA3\ncHyqa2Y2bnQPMzRZyx3z0KRZsQwbiEVmbXranv4COAS4PJVfBByTpo9Oz0nzD5WkVH5pRHRFxJ+B\nZcAB6W9ZRNwfEd3Apamumdm40ZN6ugZN1vfQpFkhNZQjlnqu7gAeAxYCfwLWRERvqrICmJGmZwDL\nAdL8J4Ed8uUDlhms3Mxs3BiuR6xUEu1luUfMrGAaCsQiohIRc4CZZD1YLxjTVg1C0smSFklatHLl\nymY0wcxsTHQPk6xfm+ceMbNiGdFZkxGxBrgOeDkwVVJbmjUTeChNPwTMAkjztwOeyJcPWGaw8nqv\nf15EzI2IudOnTx9J083MWlrfWZOD9IjV5jkQMyuWRs6anC5papqeCLwWuJcsIDs2VZsP/DhNL0jP\nSfN/GRGRyo9LZ1XuDswGbgZuAWanszA7yBL6F4zGxpmZbS26GwjE2sslX1nfrGDahq/CzsBF6ezG\nEnBZRFwp6R7gUkmfBm4Hzk/1zwe+JWkZsIossCIi7pZ0GXAP0AucEhEVAEnvBa4BysAFEXH3qG2h\nmdlWoO+CrkMNTbpHzKxwhg3EImIx8NI65feT5YsNLH8WePMg6/oM8Jk65VcBVzXQXjOzQmqkR6yj\nrUSXe8TMCsVX1jczawHDnTUJTtY3KyIHYmZmLaCRsyY7PTRpVjgOxMzMWoCT9c3GJwdiZmYtoNvJ\n+mbjkgMxM7MW0Giyvq+sb1YsDsTMzFqAk/XNxicHYmZmLaChWxx5aNKscByImZm1gO7eKiVB2zD3\nmuxyIGZWKA7EzMxaQE+lSvsQQRhkPWI+a9KsWByImZm1gK7e6pD5YeBkfbMiciBmZtYCuitVOocL\nxJysb1Y4DsTMzFpAd291yER9cLK+WRE5EDMzawHdDQ5N9laDajW2UKvMbKw5EDMzawGNJOvX5jtP\nzKw4HIiZmbWARnrEajlkDsTMisOBmJlZC+iuNDY0CThPzKxAHIiZmbWArkaS9csOxMyKxoGYmVkL\naDRZv1bXzIrBgZiZWQvoqQzfI1ZL1vfV9c2Kw4GYmVkLGEmPmO83aVYcDsTMzFrAiJL13SNmVhgO\nxMzMWkAjV9bvdLK+WeEMG4hJmiXpOkn3SLpb0vtT+faSFkpamh6npXJJOlvSMkmLJe2XW9f8VH+p\npPm58v0lLUnLnC1JY7GxZmatysn6ZuNTIz1ivcCHImJv4CDgFEl7A6cB10bEbODa9BzgSGB2+jsZ\n+BpkgRtwOnAgcABwei14S3VOyi03b/M3zcxs69E9givrO1nfrDiGDcQi4uGIuC1NPw3cC8wAjgYu\nStUuAo5J00cDF0fmRmCqpJ2BI4CFEbEqIlYDC4F5ad62EXFjRARwcW5dZmbjQndvte/K+YNxj5hZ\n8YwoR0zSbsBLgZuAnSLi4TTrEWCnND0DWJ5bbEUqG6p8RZ1yM7NxISKcrG82TjUciEmaAvwAODUi\nnsrPSz1ZMcptq9eGkyUtkrRo5cqVY/1yZmZbRG81iKDhK+v78hVmxdFQICapnSwI+05E/DAVP5qG\nFUmPj6Xyh4BZucVnprKhymfWKd9IRJwXEXMjYu706dMbabqZWcurDTU2fNNvB2JmhdHIWZMCzgfu\njYgv5WYtAGpnPs4HfpwrPyGdPXkQ8GQawrwGOFzStJSkfzhwTZr3lKSD0mudkFuXmVnh1ZLvnaxv\nNv60NVDnFcA/AEsk3ZHK/h04E7hM0onAg8Bb0ryrgKOAZcB64J0AEbFK0hnALanepyJiVZp+D3Ah\nMBG4Ov2ZmY0LjfaIOVnfrHiGDcQi4gZgsOt6HVqnfgCnDLKuC4AL6pQvAvYZri1mZkXU5UDMbNzy\nlfXNzJqsdhbkcJevaCsJyWdNmhWJAzEzsybrG5ocJkdMEh3lknvEzArEgZiZWZM1mqwPWbDmHjGz\n4nAgZmbWZI0m69fquEfMrDgciJmZNZkDMbPxy4GYmVmTdVVGGIh5aNKsMByImZk1WaPJ+rU67hEz\nKw4HYmZmTdYzgh6x9nLJV9Y3KxAHYmZmTTaiHrG2km/6bVYgDsTMzJrMyfpm45cDMTOzJusewdBk\np5P1zQrFgZiZWZONqEfMyfpmheJAzMysyfp6xBrIEWt3IGZWKA7EzMyabKTJ+j5r0qw4HIiZmTVZ\nd2+VtpIolTRsXSfrmxWLAzEzsybr7q02lB8GvrK+WdE4EDMza7LuyggCsbKvI2ZWJA7EzMyarKdS\npb2B/DBIl69wIGZWGA7EzMyarKu32lCiPvgWR2ZF40DMzKzJunurdI4gR6wa0OtgzKwQHIiZmTXZ\nSJP1ASfsmxWEAzEzsyYbabI+4Dwxs4IY9pMv6QJJj0m6K1e2vaSFkpamx2mpXJLOlrRM0mJJ++WW\nmZ/qL5U0P1e+v6QlaZmzJSY53J8AAB9/SURBVA1/IR0zswIZSbJ+X4+YAzGzQmjkk38hMG9A2WnA\ntRExG7g2PQc4Epid/k4GvgZZ4AacDhwIHACcXgveUp2TcssNfC0zs0LrHkGyfl+PmIcmzQph2E9+\nRPwaWDWg+GjgojR9EXBMrvziyNwITJW0M3AEsDAiVkXEamAhMC/N2zYiboyIAC7OrcvMbFzYpBwx\n94iZFcKm5ojtFBEPp+lHgJ3S9Axgea7eilQ2VPmKOuVmZuNGl5P1zcatzU7WTz1ZMQptGZakkyUt\nkrRo5cqVW+IlzczGnJP1zcavTQ3EHk3DiqTHx1L5Q8CsXL2ZqWyo8pl1yuuKiPMiYm5EzJ0+ffom\nNt3MrLX0VEaQI+ahSbNC2dRAbAFQO/NxPvDjXPkJ6ezJg4An0xDmNcDhkqalJP3DgWvSvKckHZTO\nljwhty4zs3FhJMn67U7WNyuUtuEqSLoEeDWwo6QVZGc/nglcJulE4EHgLan6VcBRwDJgPfBOgIhY\nJekM4JZU71MRUTsB4D1kZ2ZOBK5Of2Zm44aT9c3Gr2EDsYg4fpBZh9apG8Apg6znAuCCOuWLgH2G\na4eZWVGNJBDrdCBmVii+sr6ZWZONKFnfZ02aFYoDMTOzJooIeirR+JX1fdakWaE4EDMza6Jaz1Zn\ngz1i7alej3vEzArBgZiZWRPVerZGfIsj94iZFYIDMTOzJuoLxEaYI9blQMysEByImZk1UW1ocsRn\nTXpo0qwQHIiZmTVRT292h7hGk/XbPTRpVigOxMzMmqi7UgEa7xErl0S5JCfrmxWEAzEzsybqGmGy\nfq2ue8TMisGBmJlZE9UCqkYvXwFZ75kDMbNicCBmZtZEIz1rslbXyfpmxeBAzMysiXoqI0vWh2xo\n0pevsC0pIvjSz+/j9396otlNKRwHYmZmTTTSZP1a3VoAZ7Yl/HbZE5z9y2V87Iol9Lo3dlQ5EDMz\na6KRXlm/Vre7tzJWTTLrJyI46xd/pLOtxP2Pr2PBnf/X7CYVigMxM7Mm6trUHDEPTdoWcsOyx7n1\nwdV8/HUvZO+dt+Xsa5e6V2wUORAzM2uiTT5r0l+EtgVEBGct/CO7bDeBt7xsFqceNpsHnljPFbc/\n1OymFYYDMTOzJtrUZH33iNmW8Oulj3PbX9bwntfsQWdbmdfuvRP7zNiWr/xymS8qPEociJmZNVEt\n12vkl69wsr6NrYjgy7/4IzOmTuQtc2cBIIlTD92Tv6xazxW3uVdsNDgQM7OW87O7HuEHt64govjB\nxkhv+g1Z75l7xGys/eqPK7n9L2s45TV79Ht/HvrC5/CSmdvxleuWuldsFDgQM7OWctHvHuDd376V\nD33/Tv79iiWFDzg25azJzjafNWljKztTcikzpk7k2P1n9psniVMPm83yVc/wg1tXNKmFxeFAzMwa\ncuuDq5j35V/z71csYV1X75i8xrnXL+P0BXfz2r134j2vfj6X3Lyct59/E6vWdY/J67WCWiDWXlbD\nyzhZ38ba9fet5M7la3jfIXvU7a19zV7PYd9ZU/nKL5cV/sfSWHMgZmZD6qlU+dLCP/Lmr/+ex9d2\nc8nNf+Gos3/DrQ+uGrXXiAi+eM19fP5n93H0nF0492378ZF5L+C/j5vDHcvXcPQ5N3DfI0+P2uu1\nku5K0FEuIY0gEPPQpI2hWm7YzGkTedOA3rAaSXzgsNk8tOYZLnev2GZpmUBM0jxJ90laJum0ZrfH\nzODPj6/j2K//nrOvXcobXzqT6z78Ki496SAq1eDNX/89X7jmD5sdEEQEn7ryHr563TKOe9ksvvSW\nOX1nEB49ZwaX/dPL6eqp8nfn/pZr7310NDarpXT3VkeUHwa+jthQIoI7lq/hot89wL0PPzUu8gxH\n23X3PcadK57kfYfsMeTZvK/aczov3XUq51znXrHN0dbsBgBIKgPnAK8FVgC3SFoQEfc0t2Vm41NE\n8L1blvOpK++hvVzinL/fj9e9ZGcADvyrHbj6/a/kjCvv4Zzr/sT1963krLfOYc+dthnx61Sqwceu\nWMKltyznna/Yjf94/d4b9QzNmTWVBe89mJMuXsS7Ll7Ev817Af9w0POY3NkSh6/N1l2pjDgQay/7\nFkd51Wpw+/I1XL3kYa6+6xEeWvNM37zdd5zMUS9+LkfuszMv2mXbEfU8jkdZb9hSdt1+En+3X/3e\nsJqsV2xPTrjgZi5btJy3H/S8LdTKYmmVI9kBwLKIuB9A0qXA0cCggdhTz/Rwzd2PjOhFRvrxC7I3\nZW81qAz4qwZI2TpLUjYtUVJWnpVlz0vpEURvtUpPpUpPJbLH3iq91SAiyxFpK5foKJdobxPt5RJt\npVK/FkVk7aq3XRuOL2KoY021mm1TNfLbEwhRKolyCcqlEmVl0yWp7zWzH5dBvR+Z+dcfiYFt3bDu\nxl5nqG0dqiXBhu2pvW4lgtXre3hibRePr+3iibXdPLG2m8fXddFbCXaY0sEOkzuZvk32uOOUDraf\n0smzPRXWrO9mzfoeVq/vYc36blav76art8rUie1Mm9TB1EkdTJvUztTJ2WNHuTRoG9Z3V3imu8L6\n7grru3vTY4WSYHJnG5M6ykzuaGNSZ/Y4ob3ctx+G+h8Nvi/7760f3LaChfc8yiv22IEvvnlfdt5u\nYr/ltpnQzueP3ZfDXrgTH/3hEl7/lRv451c9n5nTJlIuiXJJlLThsbbHa+/f7DG4+q5H+Onih3nv\na/bgQ4fvOeiX5HO3m8Bl//RyPnz5nZx59R848+o/sMPkDmZuP4lZ0yYya/tJzJo2ie0nt9NdCXp6\nq3RXqnT3pr9KlXJJ6bNVojN9xjrKZdrKytoTQQDV6P85K4nss5E+25JGfCzJtr7//6b2/P6V60aU\nqA9Zj9izPRUuu2U5EnX2eb52/8/Jph0Hs/1TjWz/bNhHUfdYtyn7qHa8rVSzz0C1drxNO6t2XC2X\nlDvGwqIHVvOzux7hkaeepaNc4pWzd+QDr92Tuc+bxm//9DhXL3mEr//qfs657k88b4dJHLnPzsyZ\ntd2geyL/FhxsG7ZkCDywDfXeRwPrKn3fDPU/D+CZ7gpru3pZ393L2q4K67p6efSpZ1m84kk+f+xL\nGrq23Stn78j+z5vGl3/xRxavWMOUznamTGhj2wltTOlsY8qEtvQ9tuH9E7nH2v84/11UqTZ2/Kr3\nXVj7Hm0rZd+h7eUSbWX1fe9l38FBb2XDdFdvZcOxordKV3psK6vf8XZyZxuTO8tMaC/3bUOtzdUI\nqtUNbRK5z1w6hgxGrdBtK+lYYF5EvCs9/wfgwIh474B6JwMnA3Q8d4/9d57/5S3eVhs/pk1qZ4cp\nnewwuYMdp3TSVlYWlK3t4vG13axa10V1wMenrSSmTmrvC7o628qseaab1euy4Gxd98jPdJNgUnuZ\niR1tQLCuq8IzPWN7xlxHucRH5u3FP75id0qlob9SVz7dxUd/uJhf3PvYJr3Wvx6xF6e8Zo+G6kYE\n1977GPc9+jQrVq9n+apnWL56Pf+35pmtuofoxTO24yfvO7jh+t+68UH+34/uGsMWbT062kq8as/p\nHPXi53LoC3di2wntG9VZta6bn9/9CFfd9Qi/W/Y4vQM/uAbA5I4ykzvbmDNrKue+bT/aGvyBsHjF\nGj76wyWsWtfN08/2snaMTuYZa20l0dlWoiP9Vaqje7x98HOvvzUi5g4s36oCsbwX7fvSuOzq6xt+\njU3dzNovzXJJqYeo/6/8au1XdDUX5bPh1+PAX5Ed5RJt5RLtZfWbBuit9ZJVs1/0PZVq35lRyv2q\nzUfXketJqT3GEL/XIqCtnG1LKbdNpZKytqZfo/17/6LvtWttqbVj4P7teySG/AXQt1yurRH9XyO/\nvUO9zlDbOpzavqy9Rkli2qR2pk3uGPbXYKUarFnfzap13UxoLzN1UjtTOtuGHPro6q3wZOo166lU\n6+7TssSE9nL2K6yzjc62jRO5K9XgmZ4K67t6WZd6zQbuv4H7bqD8/hm4r3bcpoPnbDNhyO3vv67g\nsae76O6t9v3CreZ+6Q5sU216Smcbu0ydOMzah1epBo8+9Syr13dnB9JyOfV4ZQfU9nKJagQ9vUFX\nJfv121OJ9Fjt613p691mw77LPtfZey37xdvYr/V68tuen955uwlsUyeAGExEsPLpLror1X69CrV9\nnvVg5eoPOE6MVEmiVOrf41U7BtY71lU2MdCp9XjVeuJrx1qJvuPrhl6VrPdsxrSJTBnBMPWT63v6\nDV3mDTweDWVLjHAO1oZ676P8/zj/PTDUdtSOMZM725jUXh72R1ejqtVgXXcvTz+b/fVWq+m9U/uc\nbeg1rf2PB34vlQbZwRt9t/T7foist6ta7fs+7a1mn/NySbSXRbm0obesrSzaSyU627ORqMG2v1KN\nvpGJdV29aXRiQ+9zqdYbnXuv9vt/pLY9/znb1A3EWmVo8iFgVu75zFQ2qIntZV60y3Zj2iizoZRL\nynrMpnQ2vExnW5nnbFvmOds2HuQM9tpTOttG9AU0liSx02Zu0+Yol8QuUycOH9R1ADQe8LQqSZv9\nHhqvtpvUznaTtv73QCsrlcQ2E9pH9OOilZXHeHta5azJW4DZknaX1AEcByxocpvMzMzMxlRL/JyO\niF5J7wWuAcrABRFxd5ObZWZmZjamWiIQA4iIq4Crmt0OMzMzsy2lVYYmzczMzMYdB2JmZmZmTeJA\nzMzMzKxJHIiZmZmZNYkDMTMzM7MmcSBmZmZm1iQOxMzMzMyapCXuNbkpJD0N3NfsdjTZjsDjzW5E\nC/B+yHg/eB/UeD94H9R4P2RaYT88LyKmDyxsmQu6boL76t08czyRtGi87wPwfqjxfvA+qPF+8D6o\n8X7ItPJ+8NCkmZmZWZM4EDMzMzNrkq05EDuv2Q1oAd4HGe+HjPeD90GN94P3QY33Q6Zl98NWm6xv\nZmZmtrXbmnvEzMzMzLZqoxaISTpGUkh6Qa7sC5LulvSFIZZ7taQrR6kNcyWdPcT83ST9/Wi81qaS\nVJF0h6Q7Jd0m6a8bWGZtA3W+IWnv0Wll8+T2T+3vtFFe/xxJR43mOjexHWsHPH+HpK82qz2tppH3\n/BDLfkLSh0ezPVtSOo5+O/e8TdLKTT1OSnrDaH+OthRJMyX9WNJSSX+S9N+SOgZ+jlv9fy7pY+m7\ncHE6rh04Suu9XtLcNH2VpKmD1JuT3lfzNvF1HpC0Y53yd0s6YVPWOYLX3iH3ffCIpIdyzztGuK4D\nJZ01xPxZkr63+a0emdG8fMXxwA3p8fRUdjKwfURURvF1BhURi4BFQ1TZDfh74Ltboj2DeCYi5gBI\nOgL4LPCqzV1pRLxrc9fRIvr2zxiZA8wFrhrD19iqSGqLiN5mt2NTbM1tH8I6YB9JEyPiGeC1wEOb\nurKIWAAsGK3GbSmSBPwQ+FpEHC2pTJbn8xngbkbxcyypPFbfU5JeDrwe2C8iulJAM6IAohERMdQP\nzPz388/qtFFkqUrVEb7m10fUyE0QEU+QHbeR9AlgbUR8cRPXdRNw0xDzlwNv3ZR1b45R6RGTNAU4\nGDgROC6VLQCmALdKequk50u6UdISSZ8e8It3iqTLJf1B0nfSmwJJ/yHpFkl3STovV369pM9JulnS\nHyW9MpX39a5JelUuar5d0jbAmcArU9kHUg/Zb1LPVF/vVFrP9fXaNMq2BVbn9uO/pu1dLOmTAytL\nKkk6N7VpYfoFdGxun9R+Ga3NLXOspAvT9IWSvpb+D/en7bxA0r21Oq1K0lFpu2+VdLakK9P+WCpp\neqpTkrRM0vS0rV+XtCi9R16ffj19Cnhreg9s8Q9cI1Lbj809X5seB31f1ts/qfwASb9Pn4HfSdor\nlb9D0gJJvwSulXSxpGNyr/kdSUdv0Q0fQJkvpM//ktr/K+2H36RjzD2p7GPp/3wDsFduHSelz9Sd\nkn4gaVIqvzDtp9+lz8Kx9drQRFcBr0vTxwOX1GZImpw+tzen/+vRqfwDki5I0y9O+22Scr2tknaS\ndEXaH3fmjnkfTPXvknTqFt3SwR0CPBsR3wRIgdIHgHcBn2fjz/He6fNxv6R/qa1E0tvTvrpD0v8o\nC+iQtFbSf0m6E3i5pDMl3ZOOv5v0RT+InYHHI6IrbcfjEfF/qQ1DfcfVjuc7SnogTU+UdGk6Zl8B\nTMxt52C9VgLeDLwDeK2kCal8N0n3SboYuAuYpez7YZGy3ruB30EfSZ/DmyXtkdbR1xM52GdtrEja\nQ9IdueenSfp4mr4h/T9vTttYe58fJulHafqQ1NY7lH3/T86vU1nM8pv0GbtVo9SLWVdEbPYf8Dbg\n/DT9O2D/NL02V+dK4Pg0/e7aPODVwJPATLLA8PfAwWne9rnlvwX8bZq+HvivNH0U8Ivcuq5M0z8B\nXpGmp5D1/vXNT+WTgAlpejawaLg2jcK+qgB3AH9Ir1HbV4eT/dpTes0rgb/J70fgWLIDdAl4LlkQ\nd2xun8yts9+PBS5M0xcCl6bXOBp4CnhxWt+twJzR2MZR2j+1v7cCE4DlwO6pziW5//PpwKm5ffiD\n3Lb+LG3bbGBFWs87gK+24Hb+pdau1PZjc3WH/KwMs3+2BdrS9GG5/fOOtE+2T89fBfwoTW8H/Lm2\nXJP2z1rgTcBCoAzslPbRzmk/rMtt7/7AErLP87bAMuDDad4OuXV+Gnhfbh9/P+3HvYFlzX5PDNj2\nlwCXp//tHfQ/tv0n8PY0PRX4IzA5bcuvgTeSjQzUjn9973nge7nPSzn9r2v7bzLZsfJu4KUtsB/+\nBTirTvntad5Xc2WfIPvu6SS7gvoTQDvwQrLvgvZU71zghDQdwFtq7xOyO7XUTmCbOorbMSX9D/+Y\nXv9VuXlDfcfVjuc7Ag+k6Q8CF6TplwC9uXoPADvWef1XANem6e8Cb0rTuwFV4KCB7UnvjeuBl+TW\n/bE0fULuvfgJhvmsjfJ7Iv96ewB35OadBnw8Td8AfC5NvwH4WZo+jA3HuauBA3P/o3J+nfSPD14A\n3DRW7/XRyhE7nuwLnvR4fJ06Lyc78MHGQ4M3R8SKyLpF7yB7gwC8RtJNkpaQ/Tp6UW6ZH6bHW3P1\n834LfCn9Mpoa9Ycv2oH/Tev/PtkBebg2ba5nImJORLwAmAdcnH6xHJ7+bgduI/vHzx6w7MHA9yOi\nGhGPANdtwuv/JLJ31hLg0YhYkrbxbkZvGzdHbf/U/r5Hti/uj4g/pzqX5OpfQHZgAPhH4Ju5eZel\nfbUUuD+tp1X0207gPxpcrt77cqj9sx3wfUl3AWfR/zO0MCJWAUTEr4DZynoXjycL2Jo95HcwcElE\nVCLiUeBXwMvSvJtz2/tK4IqIWB8RT9F/GG6f9Kt2CdkPxvz2/yi9P+4hC/RaRkQsJvvfHs/Gw2+H\nA6elX+7XkwVru6b3xDvIvtB/FRG/rbPqQ4CvpdeoRMSTZPv5iohYFxFryY6trxztbdoCfhoRXRHx\nOPAY2f/0ULJA85a0vw4F/irVrwA/SNNPAs8C50v6O2D9aDUq7dP9yVJ1VgLfk/SONHuo77h6/gb4\ndlrvYmBxA00Y6vv5wYi4Mff8LZJuI/seehH9vxMvyT2+vM7rDPVZa4ZGYoT/lvQ+YNvYeGi6k+z9\ncBfZfhuzHOzNzhGTtD3ZG+jFkoIsqgxJ/zqC1XTlpitAW+o+PZcs2l+ubGx4Qp1lKtTZjog4U9JP\nyXrMfqssH2ugDwCPAvuS/Zp8dqg2jWB7GhIRv09dydPJeqk+GxH/Mxqrzk1PGDCvtl1V+m9jla3w\nllfpvfGopEOAA8gOAH2zB1bfci3bLL2ktAFJJfrnk4z0fXkGcF1EvFHSbmRf3DXrBtS9GHg7WXrB\nO0fa6C1sYNsHcyFwTETcmb78Xp2bl9+XY5F6sLkWAF8ka/MOuXKR9WrUu9fubLIetV3GvHVj7x6y\nHv0+krYFdiX7jAxU77Mh4KKI+Gid+s/WvnwjolfSAWSB2rHAe8m+10ZFep3rgetToDJf0qUM/h3X\ndwxg42N4w9Iw7JuAoyV9jGx/7KAsVQdynyNJuwMfBl4WEauVpavkXzsGma65kME/a2Mhv48ga2v+\nfTFcjPBpZekNrwNulHQo/bfrQ2QjDW8n67TZ5BOIhjMaPWLHAt+KiOdFxG4RMYtsWGPgL6obyd4Q\nkPLIhlF7AzyuLAdtRDkckp6fens+B9xC1mvwNLBNrtp2wMPpl+Q/kAWRW4yyM0zLZN3o1wD/mLYV\nSTMkPWfAIr8F3qQsF2onBn+jPyrphelL/I1j0/ot6j7gr1IgARsnU36D7Ffi9wf8qnlz2lfPJ/sV\nfB8bvwda0QNkv6Ah61ZvH6b+UPtnOzYker9jmPVcCJwKkHqJmu03ZHlA5dRT9zfAzXXq/Ro4JuXP\nbAP8bW7eNsDDktrpH6RvDS4APhkRSwaUXwO8L5dP9NL0uB1wNtl+2kH1896uBf451S+nZX5Dtv8m\nSZpMdsz4zVhs0AhdC0xSOisvBRX/RfY+fZTGPsfXAsfWjqWStpf0vIGV0nF3u4i4iuwH+r6jsgXZ\nuveSlB/dmAM8yNDfcQ+w4RiQL/812QlnSNqHbHhyKIcCiyNiVvp+fh5ZL2C974VtyQKzJ9P3y5ED\n5r819/j7Ostv6c/aI8AukqaljpvXDbdAXooRFkfEZ8lGofYaUKUWHwQwnzH8sTYagdjxwBUDyn7A\nxsOTpwIflLSYbBz2yaFWGhFrgP8lSyK8hiyYGolTlSVALgZ6yMaDFwOVlKD3AbJfI/OVJWu+gMZ/\nZW+OiSk58A6yfI35aYjg52RDtr9Pv5guZ+MDzQ/I8nruIQs8bqP+fjyNLMfsd8DDY7MZY6Zv/6S/\nMyM7c+w9wM8k3UoWTOW3u3ZiyDcHrOsvZF/cVwPvjohnyYZz91YLJ+uTve9fld6XL2eY9+Uw++fz\nwGcl3c4wvWdp+O9eNt6PW5SkNrJfs1eQfWbvBH4JfCQNyfcTEbeRfZbuJPtf548V/4/sLKnfkuVl\nbjXSEHS9y/GcQRacL5Z0d3oO2dDzORHxR7ITp86s82Pu/WTDYUvIhmz2TvvvQrLPyk3ANyLi9lHf\noBFKX4BvJPtBtZQsx+pZ4N9p8HOcflB8HPh5+i5YSJZnONA2wJWpzg1kuVijZQpwkdKJAGRDXJ8Y\n5jvui8A/p89tPgH/a2Qnt91LduLRrcO8dqPfz0TEnWRDkn8g+y4aOLQ9LbX//WTB6kBb9LOWjuf/\nSZYP+XPSiTsj8OFcjLA2rSPvq8C70nF4d/r3uI6qLXZlfWVnUDwTESHpOLLE/aaelbU1kjQlItZK\n2oHswPmKel9ORZPbbgHnAEsj4qw0by5ZUu8rc/UvJEsovbwpDd7Chto/I1jHJLLcwf1S7lBTSNoX\n+N+IOKBZbTAz21K2ZE7Q/sBX0xfFGrLEahu5K5VdtK8DOGM8BGHJSZLmk2337cD/QHbKMtlQy9Y2\n7DTa6u6fRkk6DDifLKBtZhD2brIz4lrlEgpmZmPK95o0MzMzaxLfa9LMzMysSRyImZmZmTWJAzEz\nMzOzJnEgZmZNIem5yu6b9ydl93K7StKeo7j+VyvdY24Tlt1Z0s+V3Y/vmXSZhHuU3ZNzuOu6DbXe\nb0gasyt0m9nWx4GYmW1x6ezpK4DrI+L5EbE/8FFG91ZDrwbqBmLpWmVDmUd2bSeAP6XbUL2Y7D6f\nb9nUBkXEu1rkYrlm1iIciJlZM7wG6ImIr9cK0gUlb5D0hXShxSW1i3Wm3q0ra3UlfVXpfn2SHpD0\nSUm3pWVekO4y8G7gA6k365WSLpT0dUk3AZ+XtFTZFftRdgeGZbXnZIHY1fkGp7s23AzMSMuUU1tv\nkbRY0j/l1nWupD9IWph6+o5N865P171D0vGpvXdJ+lxu29ZK+ky68PSNyq5ybmYF5UDMzJphH+pf\nFfzvyG4Bsy9wGPAFSfWuhD7Q4xGxH9mVxz8cEQ8AXye7LtqciKjdsmcm8NcR8UGyu1PUrj93GHBn\nRKxUdiudvQb2XCm7jcqBwM9S0YnAkxHxMrKbkZ+k7H59f0d2k+G9yW6dttENkiXtAnyO7H6Gc4CX\nSTomzZ4M3BgR+5Ld0uakBrbfzLZSDsTMrJUcDFySbvv1KPArsiBnOD9Mj7eSBUGDyd+P9ALghDT9\nj2y4tdOBZLdqqXl+uiXZo2T3nlucyg8HTkjzbiK7MffstA3fj4hquuDydXXa8TKyYdmVEdELfIfs\nHpEA3WS3KGtke8xsK+dAzMya4W423NS4Eb30P15NGDC/dh+4CkPfMaTvvp0RsRx4VNIhwAFsGIo8\nkg29XrAhR+z5wP6S3pDKBbwv9bjNiYjd0z1jN1dPbLjS9nDbY2ZbOQdiZtYMvwQ6JZ1cK5D0ErLb\nn7015V9NJ+sluhl4kOwmz53pFl+HNvAaT5PdzHko3yAbosz3lB0K/GJgxYh4HDiN7KQCyJL5/7l2\nFqWkPSVNJrvp8ZtSrthOZCcNDHQz2Y3dd0xDoceT9f6Z2TjjQMzMtrjU4/NG4LB0+Yq7gc8C3wUW\nA3eSBWsfiYhHUu/VZcBd6fH2Bl7mJ8Aba8n6g9RZAEwhDUum4O/ZiHh6kPo/Aial9X0DuAe4TdJd\nZPf3bAN+AKxI874N3Ab0u39nRDxMFtRdl7b11oj4cQPbZGYF43tNmtm4lc5gPCsiXpmevx2YGRFn\nbuZ6p0TEWkk7kPV+vSLli5mZ9ePcAzMblySdBvwzG86cJCK+PUqrvzINoXYAZzgIM7PBuEfMzMzM\nrEmcI2ZmZmbWJA7EzMzMzJrEgZiZmZlZkzgQMzMzM2sSB2JmZmZmTeJAzMzMzKxJ/j9JZbe/COGO\ncAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xhMANfODq0pF",
        "outputId": "75dec2fc-4b25-4fc7-c98e-221b310a0aaf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        }
      },
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "# 99.99% das vezes não devemos usar grafico de pizza e torta\n",
        "# \"se o nome do gráfico tem comida no meio, não use\" (boa pratica)\n",
        "\n",
        "# 1. muitas categorias inviavel\n",
        "# 2. poucas categorias, a comparacao eh de area!!!\n",
        "\n",
        "\n",
        "# ah, mas cai no 0.01% que eh pra usar torta/pizza\n",
        "# não, não caiu. pense novamente. se acredita que sim. pense novamente\n",
        "# se acrdita que sim, assuma os riscos\n",
        "\n",
        "confirmed_by_country[last_date].plot(kind='pie')\n",
        "plt.title(\"Confirmados por país\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UkUm4IYBsJNcdwEsi8idcVNIHcEMR/YAVInIUcCkwW1X3SXwqIo8A71XVnQdr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\nqmGpSZKqYalJkqrxf8qODGuwJHRQAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4KEqaX9nr5lU",
        "outputId": "b01ef5b6-e18f-497c-8469-05b87d10d4a7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        }
      },
      "source": [
        "# melhorando, mas ainda não ideal\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "confirmed_by_country[last_date].plot(kind='bar')\n",
        "plt.title(\"Confirmados por país\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fmZmZ2QJhRAFZRFwLTGiYtHXDvAHs17KeE4ATGtKnA+uPZFvMzMzMXm48Ur+ZmZlZxxyQ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\ngg==\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fKlZ1QgJsobU",
        "outputId": "5618efd5-d93b-4869-810f-c540302e405a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        }
      },
      "source": [
        "# melhor, mas ainda não ideal\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "confirmed_by_country[last_date].sort_values(ascending=False).plot(kind='bar')\n",
        "plt.title(\"Confirmados por país\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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PlvUcCRzZkD4D2GAkeTEzMzN7rvFI/WZmZmYdc0BmZmZm1jEHZGZmZmYdc0BmZmZm1jEH\nZGZmZmYdc0BmZmZm1jEHZGZmZmYdc0BmZmZm1jEHZGZmZmYdc0BmZmZm1jEHZGZmZmYdc0BmZmZm\n1jEHZGZmZmYdc0BmZmZm1jEHZGZmZmYdc0BmZmZm1jEHZGZmZmYdc0BmZmZm1jEHZGZmZmYdc0Bm\nZmZm1jEHZGZmZmYdc0BmZmZm1jEHZGZmZmYdG1FAJulGSVdIukzSjJK2oqTpkq4r/8eUdEk6WNIs\nSTMlbVhbz5Qy/3WSptTSNyrrn1WW1fzeUDMzM7MF1byUkL05Il4dERPK+72AcyJiPHBOeQ+wFTC+\n/E0FDoUM4IC9gU2BTYC9qyCuzLN7bbnJT3uLzMzMzBYy/06V5bbAMeX1McB2tfRjI50PrCBpVWBL\nYHpEzImIe4DpwOQybXREnB8RARxbW5eZmZnZc95IA7IAzpZ0saSpJW2ViLitvL4dWKW8HgfcXFv2\nlpLWL/2WhnQzMzOzRcLiI5zv9RFxq6QXANMlXVOfGBEhKeZ/9gYrweBUgDXWWAM3NDMzM7PnghGV\nkEXEreX/ncApZBuwO0p1I+X/nWX2W4HVa4uvVtL6pa/WkN6Uj8MiYkJETBg7duxIsm5mZma2wBs2\nIJP0fEnLVa+BLYC/AdOAqqfkFODU8noasEvpbTkRuK9UbZ4FbCFpTGnMvwVwVpl2v6SJpXflLrV1\nmZmZmT3njaTKchXglDISxeLA8RHxG0kXASdJ2g24CXhXmf8M4K3ALOBhYFeAiJgjaT/gojLfvhEx\np7zeAzgaWAY4s/yZmZmZLRKGDcgi4nrgVQ3pdwOTGtID2LNlXUcCRzakzwA2GEF+zczMzJ5zPFK/\nmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1\nzAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZ\nmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccckJmZmZl1zAGZmZmZWccc\nkJmZmZl1bMQBmaRRki6V9Ovyfi1JF0iaJennkpYs6UuV97PK9DVr6/h8Sb9W0pa19MklbZakvebf\n5pmZmZkt+OalhOxjwNW1998CDoiIdYB7gN1K+m7APSX9gDIfktYHdgReDkwGDilB3ijgh8BWwPrA\nTmVeMzMzs0XCiAIySasBbwMOL+8FbA78osxyDLBdeb1teU+ZPqnMvy1wYkQ8FhE3ALOATcrfrIi4\nPiIeB04s85qZmZktEkZaQnYg8FngqfJ+JeDeiHiivL8FGFdejwNuBijT7yvzz03vWaYt3czMzGyR\nMGxAJuntwJ0RcfGzkJ/h8jJV0gxJM2bPnt11dszMzMzmi5GUkL0O2EbSjWR14ubAQcAKkhYv86wG\n3Fpe3wqsDlCmLw/cXU/vWaYtfYiIOCwiJkTEhLFjx44g62ZmZmYLvmEDsoj4fESsFhFrko3yfxcR\nOwO/B7Yvs00BTi2vp5X3lOm/i4go6TuWXphrAeOBC4GLgPGl1+aS5TOmzZetMzMzM1sILD78LK0+\nB5wo6WvApcARJf0I4DhJs4A5ZIBFRFwp6STgKuAJYM+IeBJA0keAs4BRwJERceW/kS8zMzOzhYqy\n8GrhM2HChLjrP/eZ+/7G/d/WYW7MzMzM2km6OCImtE33SP1mZmZmHXNAZmZmZtYxB2RmZmZmHXNA\nZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2RmZmZm\nHXNAZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2Rm\nZmZmHXNAZmZmZtYxB2RmZmZmHXNAZmZmZtYxB2RmZmZmHRs2IJO0tKQLJV0u6UpJ+5T0tSRdIGmW\npJ9LWrKkL1XezyrT16yt6/Ml/VpJW9bSJ5e0WZL2mv+baWZmZrbgGkkJ2WPA5hHxKuDVwGRJE4Fv\nAQdExDrAPcBuZf7dgHtK+gFlPiStD+wIvByYDBwiaZSkUcAPga2A9YGdyrxmZmZmi4RhA7JID5a3\nS5S/ADYHflHSjwG2K6+3Le8p0ydJUkk/MSIei4gbgFnAJuVvVkRcHxGPAyeWec3MzMwWCSNqQ1ZK\nsi4D7gSmA38H7o2IJ8ostwDjyutxwM0AZfp9wEr19J5l2tLNzMzMFgkjCsgi4smIeDWwGlmitd4z\nmqsWkqZKmiFpxuzZs7vIgpmZmdl8N0+9LCPiXuD3wGuBFSQtXiatBtxaXt8KrA5Qpi8P3F1P71mm\nLb3p8w+LiAkRMWHs2LHzknUzMzOzBdZIelmOlbRCeb0M8BbgajIw277MNgU4tbyeVt5Tpv8uIqKk\n71h6Ya4FjAcuBC4Cxpdem0uSDf+nzY+NMzMzM1sYLD78LKwKHFN6Qy4GnBQRv5Z0FXCipK8BlwJH\nlPmPAI6TNAuYQwZYRMSVkk4CrgKeAPaMiCcBJH0EOAsYBRwZEVfOty00MzMzW8ANG5BFxEzgNQ3p\n15PtyXrTHwV2aFnX14GvN6SfAZwxgvyamZmZPed4pH4zMzOzjjkgMzMzM+uYAzIzMzOzjjkgMzMz\nM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOzjjkg\nMzMzM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOz\njjkgMzMzM+uYAzIzMzOzjjkgMzMzM+uYAzIzMzOzjg0bkElaXdLvJV0l6UpJHyvpK0qaLum68n9M\nSZekgyXNkjRT0oa1dU0p818naUotfSNJV5RlDpakZ2JjzczMzBZEIykhewL4VESsD0wE9pS0PrAX\ncE5EjAfOKe8BtgLGl7+pwKGQARywN7ApsAmwdxXElXl2ry03+d/fNDMzM7OFw7ABWUTcFhGXlNcP\nAFcD44BtgWPKbMcA25XX2wLHRjofWEHSqsCWwPSImBMR9wDTgcll2uiIOD8iAji2ti4zMzOz57x5\nakMmaU3gNcAFwCoRcVuZdDuwSnk9Dri5ttgtJa1f+i0N6WZmZmaLhBEHZJKWBX4JfDwi7q9PKyVb\nMZ/z1pSHqZJmSJoxe/bsZ/rjzMzMzJ4VIwrIJC1BBmM/i4hfleQ7SnUj5f+dJf1WYPXa4quVtH7p\nqzWkDxERh0XEhIiYMHbs2JFk3czMzGyBN5JelgKOAK6OiO/XJk0Dqp6SU4BTa+m7lN6WE4H7StXm\nWcAWksaUxvxbAGeVafdLmlg+a5fauszMzMye8xYfwTyvA94HXCHpspL2BWB/4CRJuwE3Ae8q084A\n3grMAh4GdgWIiDmS9gMuKvPtGxFzyus9gKOBZYAzy5+ZmZnZImHYgCwizgPaxgWb1DB/AHu2rOtI\n4MiG9BnABsPlxczMzOy5yCP1m5mZmXXMAZmZmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZmXXMAZmZ\nmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZmXXM\nAZmZmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZmXXMAZmZmZlZxxyQmZmZ\nmXXMAZmZmZlZxxyQmZmZmXXMAZmZmZlZx4YNyCQdKelOSX+rpa0oabqk68r/MSVdkg6WNEvSTEkb\n1paZUua/TtKUWvpGkq4oyxwsSfN7I83MzMwWZCMpITsamNyTthdwTkSMB84p7wG2AsaXv6nAoZAB\nHLA3sCmwCbB3FcSVeXavLdf7WWZmZmbPacMGZBFxLjCnJ3lb4Jjy+hhgu1r6sZHOB1aQtCqwJTA9\nIuZExD3AdGBymTY6Is6PiACOra3LzMzMbJHwdNuQrRIRt5XXtwOrlNfjgJtr891S0vql39KQbmZm\nZrbI+Lcb9ZeSrZgPeRmWpKmSZkiaMXv27GfjI83MzMyecU83ILujVDdS/t9Z0m8FVq/Nt1pJ65e+\nWkN6o4g4LCImRMSEsWPHPs2sm5mZmS1Ynm5ANg2oekpOAU6tpe9SeltOBO4rVZtnAVtIGlMa828B\nnFWm3S9pYulduUttXWZmZmaLhMWHm0HSCcCbgJUl3UL2ltwfOEnSbsBNwLvK7GcAbwVmAQ8DuwJE\nxBxJ+wEXlfn2jYiqo8AeZE/OZYAzy5+ZmZnZImPYgCwidmqZNKlh3gD2bFnPkcCRDekzgA2Gy4eZ\nmZnZc5VH6jczMzPrmAMyMzMzs445IDMzMzPrmAMyMzMzs445IDMzMzPrmAMyMzMzs445IDMzMzPr\nmAMyMzMzs445IDMzMzPrmAMyMzMzs445IDMzMzPrmAMyMzMzs445IDMzMzPr2OJdZ+CZsuZep899\nfeP+b+swJ2ZmZmb9uYTMzMzMrGMOyMzMzMw65oDMzMzMrGMOyMzMzMw65oDMzMzMrGMOyMzMzMw6\n9pwd9qKNh8MwMzOzBY1LyMzMzMw6tsiVkPXj0jMzMzPrwgJTQiZpsqRrJc2StFfX+TEzMzN7tiwQ\nAZmkUcAPga2A9YGdJK3fba7MzMzMnh0LSpXlJsCsiLgeQNKJwLbAVZ3mqnBVppmZmT2TFpSAbBxw\nc+39LcCmHeVlnrQFa/2COAd4ZmZmVqeI6DoPSNoemBwRHyzv3wdsGhEf6ZlvKjC1vF0XuLa8Xhm4\nq2HVbelexsss6Mt0/flexst4mefmMl1//qK8zIsjYmzLOiAiOv8DXgucVXv/eeDz87D8jHlJ9zJe\nZkFfpuvP9zJexss8N5fp+vO9TPvfAtGoH7gIGC9pLUlLAjsC0zrOk5mZmdmzYoFoQxYRT0j6CHAW\nMAo4MiKu7DhbZmZmZs+KBSIgA4iIM4Aznubih81jupfxMgv6Ml1/vpfxMl7mublM15/vZVosEI36\nzczMzBZlC0obMjMzM7NFlgMyMzMzs44tMG3I5oWkpYHdgJcDS1fpEfGBzjL1HCNpw37TI+KSZysv\nzwZJzwceiYinJL0UWA84MyL+1XHW5jtJrwLeUN7+KSIu7zI/CwNJewI/i4h7y/sxwE4RcUi3OTMY\n/P0t7xcDlo6Ih5+Bz9qA/Im/+r3n2D7z971flXNpfM+0c+d3vrsk6WPAUcADwOHAa4C9IuLsp7Gu\nV0TEFfM5i/OFJAGrRcTNw87ctPzC2IZM0snANcB7gH2BnYGrgROAHwAvA5Yke2w+FBGjy3KNB1LS\nWGB3YE0GB6l3AV8DHgF+A7wS+ARwA/BV4MVlfgEREWvX1vl6YHxEHFXWvyzwEeaxB2kJDg4FVomI\nDSS9EtgmIr7WM98Y4F5yuJDeg3ofMAP4MbBPRHyuZ9lvNaT9vrxcGpgAXF6285XA9eRYcW1mAp9k\n8P5cNSJe0bB9SwDHArvyNINsSS/oWeYfkg7us8hawLbVxbus42IySBkD/JkciuXxiNi53wVV0uuA\nyyLiIUnvBTYEDoqIm8p6R9f2ARExR9JSwH/Rc75FxL4N2/bJftseEd/vN72cL/XPeRv5Kxi/Ku/f\nARwWET+oLTNkf5b0ZYA1IqIakLntM9/ZbzpwKnBsROw8zHwj1hZktu1r4KKIOLNnHf8dET+S9DZ6\njjXwzoh4dc/8l0bEa8rrIcs0Hc+e5fueO8MsWz9GiwG/iYj1+sxfz98yJfk7TfNGxJw+69khIk4e\nLq3P8mOA1SNiZu19YzDS5zwcEhABewD/GREPlnmWBc6OiM1qn13tg08xcI28szePEfHK2jJLAi8t\nb68FvgC8qXz+GeTvL18PfLfPZu9Ew/0qIj4m6YPAx4DVgMuAicBfI2LzWh4a90MTSZsx9LpybG36\nsiXtwT75read54KPEpDsDKwdEftKWgN4IfCTiHiVpC2BDwFfBo6LiA1Hku+ez/gTsBRwNPmQdF9J\nfyfwLeAF5L2qui9X9/+tgdPr1/3aOoech+R9v4onlirre6xaX1luyDVR0hVN97qRWFgDsksj4jWS\nZkbEK8tN/U/kwdwROJkMInYBXhoRny/LtR3Iv5TlLwaerH3UlyPi1ZLeAbydDDLOLev4RO/8EXF3\nWd/e5fPXjYiXSnpRydNRZJm/0IAAACAASURBVOCxeHl9QkTc1+9EkvRH4DPAj2sX/zuAN0bENeWG\n8xvgVcATwHnAo2RwCvBu4H7yAjQaeHn1Jajtz5lkgDkkD8Bvgb2rQLZcDH8N/L7Muxnwu7KqNwN/\nIS8uR/Tsn2OA70fE3F4n5an2FPJns0bTftGaSEOgDbwX+B7wIvLC+uKyzMslHUZeNH9ePm4H8rdR\n/0peEFYBfkkGyNdIuiQiNpT0P8AyEfFtSZeV49/4AFDyNrPs+1eS59XhwLuA44F9yrGovmQREWtL\n+g0ZJPeeb+czNNBfHjiIdu9naABO+ZwjS76uBKqL0LbkDfGh2jH4a/kebdNnf25N3nSWjIi1JL26\n7IujGXreLAX8jJbzIyLeLuk8YPOIeLzk44qm7ahtzyvLg83nGHozPpV8oBoSZPbZ1/8FfCkiflc+\n/7MlfzcBzyuvDwe2By4kf2/3lVEumJJGATPLvvlRyzKnN+yb+g2i7dz5IPDN3u0sx7TxGAGzgP9p\nulk35O+L5Hl5d8OuHkee60NWQx6fJxquH9V3Z3xTvoF/ANuQ5/TFJd9/Jr+PQ4IR4MCmbSz7em+G\nBkTnAes0BMyXVWk9++Bk4K3A4+S187iyyM4AEbFXWeZN5HXrxrL9q5Pfo/HApSXAWAW4BGgr6Qng\nNU33q4iYWM77jYHzy7VmPeAbEfHOlmMd5LWvV/W9m1H2ZXWuR0R8VNIryAffFcu8s4EpEfE3SafR\n/BC/AXAmeQ+prntvIs+dNj8r+2jziHhZCXTOBpYq234Q8IeIOKV2Hz8OeElPvncC/tnnc/4L+AB5\nXb+QvJ8eCmwdEVc3LSDpp+Qg9HOv+yW9MSgGliPvMSeS3//3kyPtf6ks13ZNvAf434i4qE/+m8U8\njCK7oPwBF5b/55InzcrkU8qMkj6zNu+lPctWF41Z5E3zLeRTatPnXFn+H07+tBNkSdEFw+TvMvKk\nv7SWVs/TusD+5MX/eOBW4GUt67qodzvIyL0KpqeSwdEoMmB5sGkdwIfJL9JDZAlW9XcD8NOyP4bk\nodoHLfvlbLLkq0pflRxL7pKGZVYkvzgfLe/HlnztX9++aj8BS5AXKciLzDrApWU7dy3H8HJgpdqy\nbwaOKK/PBxavff7c9ZX3o8nA7Hzyy/cPYFJ5//IyzxUjyNsl5f9XgN2qNOA6YOWWY/q3lvRryBvM\nC8p2rQSsNMy5tlLtbxzwcWDfMu2qhvmvIKtyqvdL17az3/68mAwOL+1ZV+N50+/8KK+PLcf/y+SD\nzn7l79vl7xXlb//aOXI2+cR+NfBG4Egy4JkJPL/2Oc+vHau2fb1yOdZvAL5OXqSXrC1X/V+WfFj7\nDnBSOUcmldff65m3d5nWfTPMuXNe+YyZ5E34q7Vj2niMyGvhA8A5ZCn5NGBav/y15OnFLX9TyKDx\nDuDg2t/RDFyPG/Ndy+sHyRJ6yjxXkOffZSVtPTKo7nceXkGWCF5e3q8CTCcDvA1r27ER+aBBn33Q\ndK28pPb6YvKhunr/UrLGpZo2mrzOXzPMd7TxflXSquv7ZWTQAgPX19b90PI5V1PuCw3T/gK8ufb+\nTeTDEeQD3/HA1uXvp8AhZNB2HM3Xvf3IUsnlyn74cDnW1Tldv05cTgZMZ5PXxeeV5S5uyzcD512/\n68EoMjC7tazjYbIku9+x6L3uTyUfWJvOwyp/V9SWr29X2zXxGrJw5O8MnOcz++Wr+lso25ABh5XI\n+8vkhWdZ8qL2nlLEfJmkbwO30dNxISKuk/Ql8iZ/MFmXPVbS16JEvjXTJF1DBkAfLk/ojwK/l/Qd\n8qA9Vlt31a7q8YgISQFzSyEor0eRB3w9skr0cmAysDdZutfrLkkvoTzBKH/3819Rjj6wJXBiRDwJ\nXC1plKQ1YqB4f42yf44nq0xnAnvV1v9AZDXan6P5yWKmpMPJLynkU9LM8nr1iLitNu8dwBrAicrf\nHT2ltn+eAP4TOLOUGG4L/CgiqtKfqq3WvaUU7nYyMAEgImZJGlW28yhJl5b9cLekxSQtFhG/l3Rg\nWWQM+eWrql+WLWnV+u6X9Auy+ubj5NPYqcA5EXGlpLXJQHe4vD0g6fPkk9R/KNuuLEF+Gdvar/xF\nzdXn90VPNVpFI6y6Bg5UVr9+BfirpPUj4qra9KOACySdUt5vR97Qof/+/FdkaW79swK4o+W8gfbz\nA3L//J38fi5Hnh8Ab49SElzsJekS8pxdKSKOkPSxiPgj8EdJF5E3xXrp15MlDVr2dUTcVUogfkte\nWLcv39lHyiwPl/P0bjKQ/Bx5If9wmT6dfFCDvD40LdNv38DAufM+4A21c2eZiDhHkiKrL79aO6Zt\nx+ijfT6nN38rAauqpZ1oNLQPlXRZeflmcn/N3QaytoA++V5c0qpk6d8Xa8s+GhGPSkLSUpEl1euS\nbcHazsOqnecTyuYAd5IlV+8DTpb0T/LYv5As2WnbB3cDS0h6XUT8uWzjZgy+XywRtaqoiPg/SY9I\nWgH4SdkPD5I39mo/NVV3t92vAG4p6/t/wHRJ95AP6tD/+1h9Xr068+9lu+vfucrzI6K6nhERf6jd\nlzaLiI1r855Wvlc3kNXodzdc97aJiFfVljlU0uXAo+UeV92vxpIlZrsBryYD0YclrUQ+WAP8rTff\nMdDk4y0N14OrlDVDbyO/h1tHxCXlPnVcmVa/L/+q9rr3uv8OsnRu9/J59fPw7hJPXC7pGyV/o2p5\nabsmbsnTtFAGZBFRXQj/CNTbbZ1JfqE+Ql4kVicj6Gr6K8mToPdAPgh8UdKnyJtvVTw/mXwyvi8i\nnpT0MBlIVNWBE+rZAqp6/5Mk/RhYQdLuZNHqTyQdQD6BnEMWS19Y8vUiYFdJOzH0RNqTHFxuPUm3\nkl+SWeULcgd5gfx0LR93AedJ+nvZjrXIJ5llyIvIkHp5SSsCMyT9nLwwPFabvCt5E/pYeX8uGRgA\nnCPpLAZXj/6WfBKGvABVliZvaIcB3y/74GYNtDfqd9F6uCXQvlvZJuJc4GeS7mSgOH9/4FJlWzgB\n/0E+sVNuxLuSpW7HAptExJ2Snkc+aRER1zNwk+uXt3eTVZm7RcTtJQD+DvlU9BdJFzD4mH4UeD3w\nfkk3lGnV+XZGn0D/J5Sq65I2U9LxkuqDKS9GnpPV9/pYMii7vedzdgVeV+bZNSIuLa/v7bM/r5T0\nHmCUsmrqo+RT92NN5005d9vODyJin3IsBrVpkfSOPjfJKjC+rdz4/kmWvP6Q9iCzd1+/vKRX27Uk\neQ3ZXvkA9Z1yg/wOWVoVwOGR7U4OZeDcr/t10zLA6D77ptof7wE+0HPu/HcJzq5T/oLJreQ5By3H\nqASobXrzN5qsCvtew7wBbK72ZgIrkefRemXea6NUO5PnQlO+v0SWnJ8XERcpH3auAxZrCUaW7HMe\nzmgKiMp61yNrHyj5qnfIaTpGxwKHSFq+bNM95LW6MkNDH0anRXbs+JGyOnx0DLSHa6y6joG2hIPu\nVwAR8Y7y8qvlWrU8WY0Kfb6Paq7OfAS4StKFDD7ftgGul/RlBqpn30vWKgEsq+aH+O+R3/Om695D\nknYmq/OCrGJ8iPwungK8QNLXyz47hAzGANbuCWAgSwzb8q2G68EaZG3JFyLikdp6RpHnxBb1XUxp\nyiBpW7Lasfe6P428th7J4PPwIwzEE58ia9e2r6278ZpYCyYHtf0biYW1DVlro2j1aXisbI91BHBy\nz4FE0vsi4rietLmNdp9GHt9Cnhgiq2mmS9oVOClK+53avEeRT8b1C0iQgc32EXFSeZpZLCIekLQp\n2bZhLHBAVUoi6a3kk+L7yQsm5IXpUUm/jmy7c0NZt3o+q+mCHjFMo/oSUFWNqc+NiFNa5juKgXYK\n1WdX+ej7OZJeTF50liAD7eXJL/ltZIll1ZB0ebJtYNWW74VkA3bIaubbS/oxZNH/ubXPeC15bqwU\nEasoG4l/KCL26Lf9ffJ8IVmFcwUD7beIiGPK9jQ5uiEtImJzSRdFxMYa3JD8MvImUnmCbO/y3Yi4\nVtIssjpwUB6AW8iqnvp35x/lHGvcnyVY/SIDF7uzyA4vTQHK3OPZdn6UB4rjyIAK8kFiF/ICdmT5\n7Lk3yfLg9HayKnB1MlgYTVaBTVOW9ry+rOtPVZDZZ19H9GkcXZZdiix9foda2rhFrQF4bZmly5Pz\nUf32TS1/4yPit2UfVyXoVwMrkFVDywPfjojz244RebNo7dDUlL9htn0GDe1xyf3/Y7I0pnrg+1BE\nnClp47Z89/us8nlvZCAYWYIMLhaj4XtdW2ZNsiH/4WrpSFIvHWnbByUgo3eflPn2pHZekc0Qvlib\nZxSlg4oG2ohV/3cjr8VN18SlIuKbyofhpnzPGeb7eDlZAPDbyHZY1YP5txvW9cfyQLlP2ZYo27JP\nRNxT7hs/YvAx3QP4A7B7RBzYu86y7w8iH+yCrDL+eETcWALjSWVd7yNrCpYmq5FnlvRXkk2MXluO\nfdM++KOkjWi5HjQt04+ko8m2Y0N6sEqaFFm6O/c8rD1otK2vfk0UeU3cr7xvbAM5bB4X0oCsraHu\n/9HQyK5E2sOts6mXxTZkcfSvomdHqU+vKklrAbdFxKPl/TJkVdONksYx0Gi7Wq61i7OkGRExoSft\nkwwOaoJSMhYRN2geeqwMR9kT7KsNeV67bZmy3HoMbtz7VvKppsozZBuFlSPiALX0JoxhehEOk4cR\ndydXlmRtTz4BVwHPzRGxekvevkE2Cm7z937BvBp64UbEDX3mP5N8Ujs5sgH19mSp3FZ9lvlrRLy2\nJ+1/yOrxOxio2ovewOKZpuxI88Uo1SjKBtTfiNIrru0m2bKuiWS7mwfK+9Fk260LavP0Pq2eHrWe\nUJI2j4jfNdzYVyB7L1/MUJtFxAnzEgz05Ht3sg3LihHxkvKU/aOImNRvuZZ1NQVQb4mI97Tljywt\n+k5E/Ki2nurBbUZETKiCizLtUrKk/e0RMaukvYTcl/16eNYfxmDg4fPTDbMvRp7jb+5Zx3qRVUm9\n1awfIgPE/2lYVwA/bTmukNezxWnp7VwFRJHNJKrg6yjy5vrNErCdRLYh+qqkCyJiU0nnA+8kq8M+\nwUCpVN17ImLdtgfkEVxfq+NzOdlp4ClJl8fgasRhKUs0J5Lnd3UMNyzXpRFfk9sCy5rDGdo57KsR\nsX3/xeauf+71oDyY7Ucet1EMlPy/gPbe8KPI4PXNNCjTq4fUH5Dn06k0P4T1HRKqJVh+b0TsNtx2\nLpRVluQ4H5N7E5XtFTYhI3si4jJJa7U93TJwIA+muZfFxmQJw5PKtiXV/MfT3KuqcjLZu6zyJNm+\n4RzyonlVSXsJWf24Q1P+Iqu3fivp02Rvwapk7QUMtImorElWu95JHtdBPW2oVVX2BCo7kVVKjXkg\no/0hPUrLehp7h5JPaVuQX/CzyDr1u8hqiroXA++WdBvZjqjXDsD3G45fb7XTIJG9U9t6zrRVx0RE\n3Kyhxem05O2bEbGPpP3IkrrjGHiSXZVsNzMVOI3BxfBzVOuFS17glwB+Wp5U9yarVyFLLfctQUlT\n1fV7oe/DwaWSju/JwxfIhspzSxuUPR6R9ACD93O9t+90YIcYPA7XiWQVfttFsF839MY2Leop/S7H\n43URsaWkH9B8jr6BbOtSeZAsudtQ7b0SZ0jaOAZ6Qr2R7A26dcP6o6WkpSrpalxGWZ3cb9iAPcnr\n1QW19y9Qc6+310XESm3HCPi/GNrO8hv98kcGRW9Wlrh/qJQIjCvT25oJPFAFY8X1ZNBKS74hS/Mr\nS5MPzSeT15Sm0vobJC3fE4x/imzn01TN+t2oDRNRJ2kf2o/rW8iSnYsZ3Eyjcg7Z7rUaImIZsrpr\ncWXbvzeTYxUeUKY3Vl1HqZ7vsQ9ARKzVkOdhv48MVGf+iYHqTCnbfg0pJW37/pbv1Q/Lw2M1VMzE\n8nlN170qj71DRVX3j3op5twaELLt39x2nJG9O7cabjtbrgcfI/f9FfWCEg30ht+SwcNhEdnk6KmG\n86r3IfWpsj2/JgPqVsp2vZ+mJ6BnBG3/Wte5kJaQHQb8IHoa6ko6P7Ircb1aZybNX8a6X9PS9bjl\n83uLppclv5hvKNPndreuLXM5eTF6ZUQ8VtK2jojTJE1p+pzI6q2mUpPGJ6jylHIr8LxoObANgcpm\n5EXpmKb5gT0iYtOmCcoqsSHdjEsA9Wqyx82rlA16j46IIY0dS55/2/TUIWnViLhN7dVOH6QhGIqI\nr6h/d/Km0oTPke1H/pes5vxYmbYz2TP0ABo0PZWWYz26YfaIHLrgMrIzySU95+l1ZAPX6li8D3hV\n/TxUreq6vG9rt7KbmqvMJpON7Z9omNZKDdX3yhKTWbQPCdJ4fpRlTyFvWvU2LRuRN73e0u/1y/Y0\nfk+ATzR836rvZuPTKlnVsg7ZVuQhWkoK+wRA1f8VKM0KGraxdbiUMr0qUam6/29CHsOm0h6iTzsx\nSeeSwcPhZOPr24D39ysx0cBwFZ8lb3o7AP+vpLU1E/gUGdSeVLZ/B/Lh8ASyRPxPw+VbWSpzXtTG\nCOuZfir5/ZhO7aGrPKD2zjuicfpqgWp92b9FxAZty2rwsBnV9ekE8nrxY/K6eUT5nEt6lq1XXa9N\nVu9NJPfZX8lz9voy7zzVmpRlmqozdyWPx5Bhn9q+v+W8+y4tNUF9Pr9xqKiI+GXL/CeQx7LeHm/Z\niNhpmM9pqg37cNmup3rmbRwOKyImlumN5xVZe7NpDK0SX4YsIQ1lSfC65Nh2T5Tpl5NVvb2FFd8i\n27F+k2wfdyewcdv5XrewlpC1NYq+SH0a2bWR1NjbR5o7yN1aEbGfpNXJ0o+2XlWV2ZK2iYhpZf3b\nkiVEj5MXuMcAIuK08r8tGGp8guoz7xxJj9Le0wYy0KgClTfXApXGPEh6mdobmrf1InukPJE8IWk5\n8gbRFlR9FVhN7QO5fpTcd0NG0ae9p89XaO/BVeW/tzThE2QJxTgyqD2bDEafVHa2aAzIaGnc2u9G\nSHsv3JdExH/V5ttHA73bBpWEaaAkb7Paw8E+kr5X9g0RsSs9JB0B/EHS6Qw+nt+XdFxEvK9n/irt\nKQ1u+Pvisr3rRMQOkrYtDxDHM3BT7tfL8ANkKUFV8vSnkvanaCj9LnlsO0e3lfRRBtqz7cFAg+W2\np9XGnlANN/i9KTeEiLisYRFKQDMkIKP/voHsJfoFYBllm9M9gNPqAYx6BlItafXqlcr7GNqh6Z1l\n/voo6T8hSxP3opRMRY65V42ltWJJq66Zj1BKc8q6liZLEqp2P7PL/61zsSG9fpuMp/TWawpGyHOi\nt0RyIzVXO25S/vfrzQpZ6vYbsqbhdyXwaOvtXHlI0oblWvc9slH7C8kOQ/eQAej3GOgIMSR/ku4j\nb9AHMVDisiMZ2G0q6Vtk546q1gSydPXPZDV8Y1Vw5GDCLyzbP4esidil4bp2KTmId9v3F7La95PA\nE+X+Ud1Pq96HazI4WPwA+dA/dzBxtVcpV/p1DuttwrEysFxkE44htWHl4eMMZZvweslm3576NJ9X\nkMNpNDWN+BPZc355spT1EvLY7VKmPxERQ9rQlvv9I+T3sAqWm0pJh1hYA7K2djOzyUZ2j5HVilXD\nY2BuUWxTz6Fz1Nzb5xDKIHdknfWDZC+SaRpaNP2TWj7+myxG/l/y5L6ZPIjfIqsAzmHwibQfDQNe\nRjbmXoI8katqrD+Qg8QO+Ukf5dM/tPdYgZZARe2DblZ3/qYepW09My8t++dIcniR+xlcpVv3EBlw\nNbXRqZxLDgtQDTJ4EXkRa+vpA/27kzdVxywTPSPHK9vP/Rn4czmW9WrjKih9D3mxPYiBxq3vKcu3\n/cRKYy9cctiW10dEVWXxOkrwr/bBR1sfDjS07Q5kyeWp5Pm/ZM+0QY1OJS1OllpBfq/OKxdBkdWE\nU8lzF5ovgo3nR0T8KiLuoWGoBklDbpJqrwqrfJBsdvClMt85JW9Vvpp6Jbb1hJpQ/k4r799ONkT+\n73KTvL58xnkx0Du1qVkBDH+D2Ius0ryCvCmeARwu6Q/0DKSqHJbmkxpavULJzxGRQ8g8Srn4l0Ds\nILIR9EHKUdJXIoO34xjoMUdkp4ItyEboVSl37z6/jyzB/VJvaUJZ5nXKqrEqwKpu7GN71nU78Lm2\nYISsFu39Lr6JDPraBhse7oa3Hnks9wSOkPRrsspyyIN9rZT04wweSmMMOeBp27VqN3Lg0aoq/k3k\n8XsFueKqVPqnkj5TXm9HNiEYUmUq6dp6ENUz7YPk8ftdydsPyF6ubcM+tX1/iYjGqkkNlIL9lp7m\nKmT17Fsjourl/cmyvsaeu5FVygfQ8GCroU04liRL0l5Hc9D8dfJevDSDr2H9esP3e6D7DxoeUsma\niIeVTRMOjYj9VXtAJocH2YPBwzsBfK4Eq09RajvKuT7o13Aa8zLCEsoFgqTRkeOINDUgXIz8baym\nhqLV8o09h6KM5F/mqff2OT+y+L5eBTqoikp9ei1paJf+tiqXncmL+afJYG4KMDsiPqfsdr0Eg6ux\ntiV7ytWtSA4D8ANykNNBqqduZVXRruTFZnPySW8J8gLamIeWPFc3/IaPGtSLbB2y+u4Yhl7gqzzv\nEmXU5JbPaRxFn7yYNfb06Vl+UM+Z8nR4B/llrqpjtoyeXjC1z/09Q1UXmbY8703DiOJRGrGquRfu\nq8i2flWPojlktdPlaqkmJwPUH5C9mn7IQLuVL0uql7YtTT6h/zN6qn6U7WG+QFYXVmOniSzRPSwG\nfuliZbLaBfK7cVe5MfyS7DV1FOUiGPkTRE3nxySyqrzNOuWvfpN8Hhm0vpMsoaiqPXYiS+E+0bCe\natuez9Aeez8lS9mb2pbdDbw1Bv8Ez+lke77Pkg9VkOfeyRHxNbU0KyA7fjTumz7bX696+SBZOrZ3\n7bjPorl65ZIYOoJ+bxVO0yjpjR1fyg39SfLBFvK6+Tzy+vM4GQSfGTGoDc81NLc3fX5LUHEttSYc\ntfRBv+LQM+1scoT528r7VcneyR+mT7VgzzrGlHl3pmcYirL9N9XmXYLaUBrkedTWw78qpbqjLLsu\n+VD/NzLwrPL2bmBMZFXimWTbriE/ZaQsCXoN+eBVfxDcpuy7zWKgR/lKZb6XM/i69sOI+HuZZ8j3\nt6RXD/u9Do6epgC1vD1ADsD8GLWhoqKnV29t/tbOYWppwlHO2asYej0YHxHzNJxEWWfbL0m01VC9\ngywhPJjsbfo31X4Wqc/3/t6G7+LczjF987iQBWTDDd1wZ5T64pblW3sONRUNK3vebUaOpryhshTp\nbPIpaA8GuhCfR0bQVa/KEf9WYZn/4ojYqCdf1TAHTW2UrmJwKWEAd8fAz+GsQlZLQrYnGvJ7bWW+\nevD51z55mKff6Ss34nPJ6qeqN1ZvlWVvnhtL6CJLCS8l9/cBZM/CK9Xn98KUVTqtxf2SJpFP1Y8o\nh7vYjAxQ609vo4F3RLaBW7v3wl6lqf13UDcmfxan/hMrP42ItzTutMHrHl22/f5a2oURsYkGenDd\nXbZxndo8/R4ODiSfYu8iz9dBykX+m/WHk57lq+r7Qb9RF2UsvZHSQBf3xuCK/NmcISLiJvX0OFZW\nFb6LvPk2dopR8++0fotsS9fWtuwVUUqgyz69nLzWPBIDbYqWIUf2XpenqeEmVZUoPUQG68eQPVEv\nqt2gfk/2nqzasexElsi+nsHVocsBT0XEpPJ9HAesRZ6To8iS9kNp+R3FlgDvErLE9HpypPONyara\noyMHTb0gGtqbtn1X24IRSceStRjTGByIfF/S1RHxstq8i5Ejrd9HPpBUY97tSP6U1Ka1ed9IBkOT\nyZL7n0fEL9X+m5lNPyh/Hhlg9bad+p6kqyJi/drn3cBAE4gXMfingKIEI78kj8mgWpNy7r6RBpHD\nQfwFeFMM/PTYkuQQR4OauCgHUT6olv+m4Pu02iJLk9WgF5PjDP4lBkrBRkQNvfzJB77GnxusXduq\nB+D6z7k1NXX5PNne7ezyeSNtR3geWbpcjQe6K1kK9pWm5SRtThZQ/Dkivq5sC/jpaBkKSdKHyfvU\n2uQQIpXlyjre2y+fsJBVWUbE28v/xnZVkg5VDvJ2MoO/yFW9cVvPobai4YMZPMjd9mS1yLFke4zq\nB5nfQ1YB7FDen8pAQ8S5X7I+EXoVMPUOeAnZw/Mltaectclqx8Z2cZLeRVal/oFSlC3pMxHxizJ9\nPzJY+ksMbqvSOOim2qvKqvYkQ3qRkU/VbwB2KTfuGeQYVD9synPxM7KE7m3USujKtI+RX8JTojaK\nftvnR/bway3uJ0tGD5U0h3zyeoosJawX3d/PwCCAv2BwLz7Ic2wj8lg3FetvEENHFN9c0v20G8vQ\nHkVV8HuaGqrJ6zeNiHhM0vMk7RERh/Ss+zjyYvwwzdUKlCf2tqFC6tX3+5Ln/y+VJX27MPTh46PD\nHJ/vxeDhXE4rAdcnoLEqEeD5PcHxHPIpfUbT9hRvYWhVwVZkO76mtmU/IweZPbXMuzV5Pk8iA8bK\nUuSNFuV4RJ8kxz+cqhxg+loGfpS6Lkq+p5ENwptKlDaneSBVyGCoXr0yhiwRv4bBx/UBBn5Ro22U\n9J/R0J60LDNK0iYxMHj1xsCoiAhJ90bETiWI/Smwh7Lt5rVqaG8KXKLBPVorD9PchKP3Vxzq2gYb\nfmMMHkeyXi2IpBvJYXdOAj4T2QZrG0nXMbSUtCop371+zYocs2vtaB9P6g/KqtDqh9b/RpZifwb4\ndTQPuVD9zNUQJfB6MUPHqYPsTFOdp0HWmoyugpMYGJri/cBB6tPrPCIGdXpTtpU+sMz/BUmNpWBN\n1wry4bT3dymDPr9CQnMTjsPLdjQ1LXgvMFXS42Rp7VLlM35Fns/V/tyawU1lBv2SRLmevkHSa2h+\noNuGgapxynVnD7UPkfMA2SnsTTT8Gk7Ltg+yUJWQ1am5MeiQRszUqtDUXFX1Q7I6oa1ouD7I3TkR\ncXXvk1BZ99w0tfTeIkrRZgAAIABJREFUaYvQy+e2DXg5qeTv+pKHF5OjqzdVo1EujG+JUiqmLMH5\nbZRSNuXgtG8gS/keKJ97LvnlGZIH4GvR0qNU/X90W2TAMolst/F4vTSnId/9SgkbG94O8/mtxf21\n5V9EBl2fBl4UEYMeUMqxfzk5jMdnapNGkxf1l6uhR21Z9hDyqXBHsmfag2SJyq5qHypjE5rH1zsA\nmBgRfynrrvfgaurRW1VHVT0Eq5KX24HbI6KxiqLtol0vMVFP9X3Zt+fTPABuv+NzNfC2GOhpthZZ\ntfs52n9YejI59Ef9u/Ah4I9RSqdr2/JpMqh/CXnzqixHVm2/kJaeUJImMPBLBpsx8JNPG5M9tIIM\n9C6M7LX783LMdon8WauPkFV6jYMkk+24NiGvv409mNsoq8KHiD5tqMp3cUjpJlmdtbGyymjTEtBf\nWfb1xmQb0GXJfX0/A72a9yXbRd1BBpXTyIDvT+S5MChr5LEc0qOV9geDqt3NoCYfte15BwNtai8h\nq5Q/Rza/qNqTzq0WLMv8R/T0XCzB2ERaxotStqPr/UH52WTw13Q9ElnyWw0k+2fglyWIbWtPWpVu\nVcH73F8YUJ9x6nrOgw3IavE1GGgn+3/kderJMn9rr/OW7biy9x7XM09bgPf/2zvvuDmq6o1/TxKS\nQKiBAAImFOkISC/SQaUIiiggCGJDRan+UEQFxEJVmoogIkiTIk0BQQgQOiQkJPQqKCpN6QJJzu+P\n5867s7N3ZnffbLLvJvf5fPbzvjv1zuzMveee85znvA9lRXth+2OQMRktN2gRCkdYHpWtiRnFoc/f\n3msZ6PMhjbxNw/c70G9zKTK0hoX7+5XCob6OJqAHEueuTnbRCIqUjKFh+2gZs5aMMm+h4OVA+yAe\nxzOoA786fK5qYb8DYstQxlDDx2sFTJdAD3v2OQ8NkNkx1kdqzdn3M1DYo3iuWLHS8S20exh64VYn\nFKCt2HZy4fug4rKwfPHw4DxLqEdXcry7w9+7wn0YBjzhuUKrFIrPotn9Xciw+wwydppdY1a09i/I\nS/YhJK4K6ujvQS/KArl9qop+V/2me6K09TvQYHIo8pocH56pm8LnAWQMvxz+Zp9TEH8DlDSyXZNr\nWxp17Nn3SZFtJlFSCDt/rbHfG2qFecPz2lAQPrf+NiScXHashiK72XMQjp0VDx6FPA4NheRb/H0+\nFp69mxE/6xmU+TiJioLK4flbI3yyYswPUP8+fgoZYUsjT8qY3Gdk2GZEuJ4hyHDbP1zTI4Vr2Lvq\nE7a5r/gbxX7jwnF/iLL1jkeTo7Vyn+PQYDoXCmW9iAyFquNtgJJd3kBeg2nAa2Hdr9DE8+HwfaGw\n7eVItuNINCm7ErimcNwFqH/nHkOk6aUibfh2SdvGxD5h3dzkCniHZauFZ+tv4TMeWDW3fjE0od0h\nrH8KebqLn6dy+zQ8p9QKhU9Coau63414QfmXw/19lEjh6HBtW4f/syLaRyCi/79R//Ev4NKwzebh\nGm4Jv8HTwKZh3UQ0yNcVry5cwzzhnJsjgyjf360FDAnbVRUxP5VasfjTUB9xXu5ZWQ8ZwJvm2lZW\nGP4SJD1UvNdjI5+bwrpjI9sfm/ttGvoD1Id/Pyx7f2jjo+TGR9RXPJr7vi6aYCwVfoc/ovfmgMK5\n10N2wVaxT8U7+DR6FmPP41Nl++U/PRWyzCGamWJmS6GHK5vdjkM3OyPA743InHl83ksU1a1E1Rx1\nlHeYWRYOG43c9Vlm0hDishxvWKTWm9V0ajZEXoY+Qqop7JPnq40zs9O94BHI4bqIS7/PVWxKElgl\nXNM45CGagIyTmLRDWZ0+KM8iuxcZVMuH8/zLzF7y6lIUPzKlFx9CzUN3EIDLG7cC8iiON2WQ/q7i\n/Hh1bb+TUEjkdGCsq4LC9ShkugO1kOm9rsSKDd39zpJjlbr1i17c3Cy9LDt0Spk3EIVqPkWjVtB1\nwB+Cyx/kMbo7nC+Wgv5flDXawM+hWiokC98vZvXh+6XCTP5PFARwqf59rgsz/ozn94jLQ/NjrxZV\nXJtaeHQNTebZA/itKTsxK569ubv/3cy+h7yC75gy9VY3s3O9xguan1pGJRToC14hSZPDuyZOmYdj\nHoMy3qJCtu6+v0srb2xYVMxgHunuhwZP0DPI63IrCsONQhOIIk1gfuKljkDer7VMXExcobehXlFH\n0czqeDVWk1lZsfD85XG6mf2MRmHjaEarmX2cUFkFWMZCZRXksTzY66s4nAlsZI2UjOnAoR4oGUVY\njSM6yuq5RvMjKYiympkQLyifZc/FztXn0UKe2SVRH7MoNT7pPhb4pGG3E4GPeCj1F/q5C9Fz/o4r\nCSk7/hBqz1hW6m1edx8d+ujJiLeblwfK+pKqrPN8yH8qcKG7317hBduSQl+BfpPNkPEcy/KPhWsz\nlNEKvk1ctuYSlE1cVD84F7jH6mva/i7Xhixk/ga5aJopmnFybrt7zOzXZXZBHlbPrz477F/Kr26G\nXjXIniKn55XD2YjvkXG59kRaLL9FYZNlwkCUYTsAa+T1ZAbUCxRUzcP2Y/rZ7kXRjGZ/9CBtiQb+\nC9AD1aBTQ3O+Wh3c/f9Mse3MbX4GegkzLIw8A/9FXJaX3H2qmZVJO2SyBpeZ+BF50ng0zdhDFlkw\nsPYK7V0UzYYbEEIBy7v7n1DIruHldZGGv4c6j1OQwbegmX2ucP75I78n5Awld1/EzFZFA8ePg2Gw\nnLt/xESCvQVpRGUv8CfN7EGUrXcd8lQe5O7neXnKeFlK/62US2VcQ3kafplW0II0DhrZAB8LCY1B\nZPEYP6e003b3802VMLLw/Sdc4fv9UGd8ODXjwxGxtTINHRnsK6LOLDOuqgoq/54IP8Xdzw1G4u/R\nu7JpbhJ2GbCOKdv3DOQFusDEvTkKdezTc/fz76hocF2oG4XoYsbVsmjSdh3wfjM7Hwm07kq59l62\nb3SQMrMp4d/tUSbnqzmDKONa5icOL6KZe5kG1XvhHcsG81HIGHnEQ+JLZAKTv/bh4XwPA1daYzWL\nV9F7uTnyGn0mLP9caMfviGe0/o/GyirLojBbZqzioYpD+Ho4Ci3XUTJM/KoY/oaeuyE0ckQzWZm8\nXlTfYBoMm7OQx8ipDyfGOI51lRfc/fGwXaahmOeTvj/sM5fn6i6Hfm6u8PUWi+jUhXWZlt5VYb9J\noS880BrlgfaoMr5d9IK6sGn4G9WsDOvq+gpk4P4TeVvz2CQsLxovhGMvjQqOP5DbJ6MVQLw/GO7u\n+0UmGD82JYpktXP38Zo0DdYon7Mk8raODGNbZmjPB7xiksk6gkLSjbuvEI5Xxa8u4+JWoqc4ZLkZ\n55JEMlNQR1zk00xEhMdlEF+kjmyH3M1R1XIrZDRF1kezc1pdn9uuISXWQnalNeGr5ZbtHZvNh5f7\nXC8oIpvZyuiFPggZaMWyRouEv0fE2uwVdfrM7KvopVgXJQeMQzO36yv2ucfd1ytZtzqa0WyPXv6z\nXMWml0Acp7YM5NApboxmdJugax3p7qNM3sVTQrsvdXE3Jrp4F59EA9PBKEkh4+XFyK1nEknpb9Ku\n6HV4E2HjmQGLFNm1SP1N9A6u5yGFvo3jH0FEFgQZGGUFlR8mzk85Cxlq+6BB5WRUyeMXVq9G/7a7\nnxo68nmBDYvttpLMNkTQzjAcTYhGesjQMhHlNwjtvqvqfpjZnu5+npVnhy2KZvdvowF+QUQKX99K\nuJZh26hSv8kbuysKYZ1Dzbu5J8pEjPZLhTYPQ3SCSSi0m/fAv0bw9Lr7yMJ+E8M9iWW0rurxyipP\nEqni4KHIu9fXIB0U2nRz7rTD0cRhgtdkZsa0+x6ZPHPnIC+lISPqDEQ6j3Eci5UXhoTruI1yPulv\nkSGQV7Af7Ep8GYQSMvLFq3/j7l48V2jvW+4+jxXkgbyWGdwgKOzuz5Zc597AiV7CMSzcp82Qp/Mr\neQMorPsgMuL+QaPxcj+aoDWMyx74VhavSLA3ei+K6gdRtYRcW06m/tn9QjjuBugZyozNLCFmMvJG\nFzNDM1mTMimicyjh4pa1LUOvecgy1+p44pkpq5rZntRu+O5IWiHjImwY2acBuY6ymNGU4QniM75V\nw/5RIqJJh+xwGpMRrjWz71BPSL3GpLc2xcw2cPe7wrHXJ55VdoApzHRG7jpGoDDTc7llOyAjZFPU\n0d+EjKXfFu7B2eHfWNmpVcxs6cjyDEMRKfJerw5T5lElvnoqeom/6+75Gp4vA38Os8im8iI53Jb7\nnOYKbe1gJSFT5I2FiMfCyt36ZV7cLCzxK1RwfrVgcO7oQeU8Nvs2SSRMdGWH7YkG15MQT6Ihc9eV\nUl9WVHorNEGpkxcJ51mD2gxzXM4YO4JI/U30LrxFDhWGRnaun6EOuSGM40EGJaA4wZhCvArFZOBL\nwVB7OrwjWZbZeyZpiL2oPctzoUH/rcJxcGW2tSIbc5LJY/gDq4WGs3aNDs/SmyhhpJhV/YfwN+pd\ndffvmLLAX3VVingTTSqhFgYuZmR/HD0TZ6LndCnEpavybn6TiDfQc4kvOcwTjjnC3dfNLb/aask3\n+1hc2Hguj4eh77NIZRXk1TuKxioOEKdkXOON0iYLov40w1umDNBVkYHTtzy/G7ksQuLhxInIYCka\nl1Du0TrdFSI/3VQtYH6vVV74GvKsZUTwcajvxFUa6EzqRcczPGeSl/Aw6T4Ahck3RIZLVsh6cGh7\nmaDw6iXXeSHwrDV6zJ+3Rh3QyeE8DQavu08OY8UYj1QUcdFFSmkFsf7AzF4mrn6wp5Vn1oN4v7Fn\nd/FgaNZ5ic3sNQ/VdEqQ0YaKotxVnsVK9JqHbBQwyt0fKixfFRk+86DBdEP0sN2B6sI9RDxbovgC\nZseLeoUCHHV0DTM+r2XnlNXP+zDK1qvLSKM2u8vamI8JLImMjTq+Gor1e26WPBK5oM9z91PCvboG\nZYb2zT6C0ZN5rJ7PLW9ZO63i/syFBoxomSHP6WpFjjk2stirZhUWr3OGu0ezt8I+g4Hj3P2QwrKq\nepXHUO6xiGYvod+yTF/oFvQc9PEUTGGq71KeYfhAON7qiBfxGxQaGkyJtk6YSBSVwz3cq6koTLo3\nNRHiA1DaejYQfhIJw55q5fU3n0SD3Njcda5HjrdYROiQM+2h8WjWnM2giwXj85y8sSibr6EKhYnD\nNdpz4Z/QxlVQaO9Od7/QlM35GTSjPhuFl/JG823Uc5Q2Qb9VXoduEDJOvxY8UHchY+iBsM9qSBtr\nJWR4b0eLYsuhzXvFlrtCszvQmA39D9S3PBM2XRx5CH9qZmu6QoGxcktR+aBglOaV+gcjz8LRyMj4\nqNe0ukajrLiVTR7Md5EXA5T1uDcyjhsyWpFH73DqPUBHezk/Nrs/eUrGOHdvyGYNRsoUDzpxVuOI\ntiN8HYtcZF6oScCHXKHILJoR9WihKExUM7HJdZZVS7gPGW1Honto6Hn+A3p/b3f3Y03h3wNDnxMV\nFK64zrplVvOYZzSL/Bjl6Hl8zuM1lp9AjpH1LaKjGPqWddDYcw2iFRxExFjO/V2PRvWDysz68Hw2\nPLvoGbyAGk0kO0cmeVLMDH0g7P99GkW5zwS29RY8izH0mkF2EfBLb0xf/hTwKXf/bGSfHVzcpP6c\n79PufklxGcomWif2UoZt7outR67YD+eOtS56iP8Vvu+NjKJngCNdtSmb8VD6ZiWmUNy1qMPeCc3M\nikkMZddaNG7Wokbij+FkCkaMmV3r7tua2XNEXlp3H11x/irx1TL9tre8ojhwxbnudPcNC8tKQ6Zh\n/UhqHot50Cz3X1bzDtS9fChTrggPg2q2Tz7cUBracRXWzkJvPwD+4e5nmYQ63RXCyitIZ2GtonL4\nYihLbhmk2D88LM/a8wAK42WcrbxAY1S8ERkcGdl4KqGUkzchw1uFLEjFPmXhxPkJ5HB3X8YCOdzj\nnp7sWPcg46s4OTqYiGwM4ltmmIre0RPc/VEz+yPK+How7LMK4iKtiN6lQV6Qcgn/Z8k8dery1Dyz\nEAm/Fa7jFGTIHuS1dP/sfkxD2aw/I5KcVBhwF0GDZsYzy/c7U1FFhKlmth0iqj8ZjrMMMtJuRv3i\nDywnbBwM4BcoCUMXrqWyRFZuYF0c8WunIy/8vwr7DkbCshdnk1GrltUpE4aNhRO3Q79ry4Wjzewc\n5Im/N7csZmzlr3V1K6+W8C/gw17QD6uCVdBvSq5zMI18sKxtsaoLF6KsyTMLy7+ESPtTKK8oEqUV\neGMx9FiFnjyiRq/XqtSUPbunoGelThTbzMbRCHf3TYPxXSZFFK2G4+7bNWl/zxlkdUrdueWPoGtZ\nsbB8H1R3bbl+nq9MrfoVNOM7BpHk615KM/sr8Rnh91EYNfOanIAMr3NN5SsuQh69NYGV8x1wWaeR\nW5+Fp+ZDHfCN5Fz2HjhfVtOmAoUW50KziWfzxo2Z7evuv7YK3aNmRkw7KLnXWSdapt+WeQLKigOX\nnetXyPOYFxDeB7ncG0KmVu2xKCtF9ZeiMWxBNdtEPP0GCn+uZWa7oJn1qDJD3+RVuy6ca1P0TE1C\nfIe8ts4/gGPcfUVrVA43lOo/jynxYXfquXKT0XOcVZwYjga8D5p0vZZHnetPUQjpTfSs/g11cKOR\n1+m77v6eNQnN5tq1NLkwjpVwXWK/Qdh+fLj3N+cM3FfdfYGKgW9ascMP+0U5Sl7h4bCI7qDJ45nV\n2/s3BV5i2OYumqjLh+0WBC5y948FA+eb1DzZWyEPwY6FfQajqgzbooG2zztiIisfg/qxoxFXaxH0\nTu3lyoAtLTQfBp+Mq/No7nkpfYdL7ts6yCjPriUj7v+JkhJZ1ljDcTNk/OaV0acCf/NaYgdmdpeL\nr5bniF6DfqOoxlW4zv3IeeOQd/pVCqW4XJPnssoL79KowzYEGcv7hWPn+XLuClvH7ufzyKjYj5oH\nZ1s0Ef8smnDVweVBPgsZknX0G1f1g9h1/hJ54rKJ9XBkwDzq8thnxvUy7n60KWz/O/RMZbU+10Fj\nzCc9OB1y97UvOcxUEeck5Kn6uLs/nX+nrEajOBIZ9vk6zn1eMxdNo5JuEHt2TXViN6ZNxIzGyDYN\nXNzK7XvMIHu0aHSF5duhOPeq7v54WHYYekC3zb+YLZ5nWzQT+gw1vgdoJr4KCv1kM749w/LzvZ6I\nWKyfdz6aDa+EwhnTkRfrCheB8xfIhX5kOEZGJG9JGM/idQMzuOfqS+b2sdCGDRAPpS3jxsx+joyP\nmBGzACJa543IOyLHaEV8NTPM6rxAKGuzWOesbuZf0u7YvfoYEjHNw12iqKfmlpV6LCxSB7WwPiP7\nLovIwRshA+5p9JycRYmhH7wCn0UG0jiTu31zxF18GIVRjw7nP87d7zJ5oUZTUw7/FJr5fgmFBd6k\nXoT4YBTKqUsbd/eTQvvz4o3LhLbHPDNvufuBVhKaDcZZWf28NWjkuqxCYygTagPeQ95IDn/I3Vex\ncg/zvsjLdTX1IcvDUFg4z1GajLQPj6C+XNoPXdyoP6CB6KLcPosgz8YPEH+tTvA5tLE0maewrC/8\nFoz1s6h59s5DXtRiliRm9pi7r2CN5ZbuQ4bQAug53DY8LyshyYMPFY0BE8d1r3BP6yIHJsmV62l8\nh89HA3L22xXDTv8kTuG4rDjxtlrUIVbD8Y5wbxZHoSwneM5y+8dCvSOR0RDzSA9GyVB1Rc5jyAZ0\nK6/lOW9sP5dafMwTlHmMJqFqAflqCVei8eBgajzJD6DxahT1JfWy89xSNbEOxx6KvIrTkaESqyO6\nFvB1d/9SmNROR0r/K1sts/NQFLIHjXMLxs6bO/8frYRW4Aq7ltIoIu0rSqJsgsaQS3PbxMo6rY0m\nAFdQ3xdEEwTc/SfhWCcgr3afFJE1KdvXDL1mkP0ZqUtfU1i+LSKBjkSDyJfQi7m9u/+nH+dZA838\nj0XCn6BZ18+pt86BvrDc/9As7fvIQ9CQ0l40KMMsek1XKOARlKVya7YuDFxRPpoHvtqMIngQMqNm\necSVyWunrUd5+Zso7wt1xAcjL1SeY7V55Pw7od9sR+oTNV5HXoE7rFFh+R/IaPkIEfhMzkoMHovL\niEuP7IxIputTUlswd5wRKJz1eu5709BOG+00ZIRls78+5fCKfdainp9zf+hk/pp/pk0q5ysUjxW2\nfcTdl7eS0GyYaJTVzxtNCdelos1nIY/wd8L17o9CBF81s229ULLFlAUc4w5ls+wGjpKZ3UDQAgvL\n90BaZ1ub+Gtfp16h/Zfot5zHI4WjQzuOJaIuj3gwjvqaQcggvcTF86urF2lmV6AB4dzCsfdEdSJ3\ninhHDkEZdLHakM+jZ7VYaH5u4HhXea2isfZkuDel73DJ9d/mOQpHbnm0ikMY+GM1HG9GVQUaPGde\nSFYqnOdZl4ZXGfWktMh54TjPufv7i79NybYjkFGxu7tvb6Iq7Ofut4f1GyFazppWXi3hQZS4cS0i\nkH8Ridae6CV1i3Pnb6h+YEoOKYby9i2+N2HbyS6PebRyR2Qy0bajoLB/lEaBjP/MO5dVnjiT6io1\nUdkc4sk1Tk3+A9RHbY+MrX3C8bIC61Op9duO+LQtZS8X0WtZlgeirLrPUO8W3RDJESyGXs470ItU\nSQ6twEOowx1KLbtnNFIx/q4HLZo8wkC0GjJG/m1mC3hjkec7zGwVryUlXIgyc15CHrVx4VgfQG5x\niAvjRQswtwKrz7wbFM75LjIkYvg98hx9lFz5G6BKR2ky+l3udIm6rkpO3ycPd78SaRs1E19t0G/z\nEsHJZrB6AeFhiCM0hdo9z7fvZ8VlaMa/KXLpF8mtQ8KntLZgGMDuIiRXoA4WVwZlNst/BRFOnzGz\nmAE1TzhflDzv7jsGY+lS4FIT12hTYFNr1JECzeyzmd2EwrGmmdn0wjPtMcMubJstf8nMlgvtxBSa\n/WfYrqx+nhH5HZrgmyjc8Q56p/6CnhOA75vZO+5+UzjPocAWXlIPN2A8Urn/q6k26HxIffzo3DY/\nMrNdw7W8jX7rumQSCxwxU+ZbneBz2CTT69q3cP7h0CcYXAy/nRy8HdeH6/0VcIKZfYH6PnFuarqG\nz4bP0PAxaoNQPmsZxE9aCvF7+gbLMPBmHJviA/SaK1O29B22esmURcL5jzAJVRfliw5C2e35Ell/\nMXlwYzUcH0Cetg95wXOGDJoyLBoMlHHEhWGfolxEOY/seR9r8VqeU9Bg/lnUj16GDCCQMfVbU0QB\npA/5hXCee4EPZuu8FuIbiby4x6LMw7VcWlwbm3Tw6kKmYZKxGurLR4ZjvIQ8ng+i53YLd38irFsO\njbN9hjoaK9aiViA9qm1XvMFewQnNYCWhXleCgFHvbZyGJvobUhOGfT3c00EFg/Tl0O4M6xCRzWkV\nYQJ1XfbdIxqUYRJ8C61nL9ehpwwyl9DeB9GDnblFb0HGRDY4DkMhpRfCzXEvZFG2gOPQrGSMN4Zj\nTkAGQrFt04BJpvDWdsDkMKvOv+AboGK6+RDb3OGY1+celEFokIEKocx+Ij8QZuTkbXOziqJx8wF3\n/7SZ7eQSELyAmuG4GMooXMJF5l8FvSj/c/e3TSrOQ10FwRtCzQVUia+WKSxHw7nUigOX4WxqAsJf\nDuf8PhLhbYDFCcMnovDW+8tmQlZfGHhu9Fu/jjwe6yOX+vHh3jyAPBj5Wf6pqNJEw6BiZi8iOZNx\nKFMwP0hea43iuPOhDvM9pCZeN6gGQ6qqIPsb1D/Tg83senev81KaPDNZ6Hc/FBJbycz+gbywexLH\n39F9vZOI1EyJYZytewsZZIdHVu+Iqk38HwpLr0SQkLB4+CKrb1dUW7/ezHZDngiQF3Rxqxe0rGsW\neq7KBJ9pYhT2IUzG9nD38xFx+XNoMMoGwBeRJz977q9x9xv7GlILS2Whsx8Ah5h4gXPnnhVD3J7p\nwTtTvJ7Y//nv0XcY3ce8ZMpQ5Gl8Gv0ec+WuxV3e97oqDsj7OR+1wuMZsiLwK6B3K8PraECuwkvI\nC3ggEWFY6ouc93FlC5ParA+H8LtSE2ZeCGnKZV6TcxEFoa8Pc/fxSBS5z+gK79AEK8jHhInUx5Fz\nICvPl/e+lhWrJ2wfrX6Aks3y9V6fQvcvb3BMRf3TZeF7VrmjKD0RhSn0eHY47pnIuPuOS5uyqt1n\nIwM8T6N4yyPCsDRKouxG/YQ1KptjLXJdUd+wVG6/H3rQIQzfByGj9/tl96EZeipkOatgLYRjmuy/\nd8mqm2MLvSLEZh0KY5nZ+939uZJ1O6BOJ2bcvOnKrrsVhWX+hciSy5rI6WcDh7uI58OQYfw04s0c\ngsI4ryD9oo9VtC8mvvosMrjLMIZ+hHMtXpA7WiQ8rMtn901FRtmuoVOoI4Hn9qkqDDwEhXE3Q/dn\nYWSQbU4JPyZy/MGIYL87Gvj+jPg/D5Zcw8LIAN01XMMfEMH8v7ltStPGC8+0o8Fmf2QUNnhm3P0f\nuePWhWbDsnxZoUGIIvAMjQLFWRuOilxTTIswv0+Wlbco8oKOB77g7m7l4YtNCWrrXgvFTEaG2whk\nODh6Bt7K7ZdNEA3xlA5D9R5LOWLWWBbtHmSsLIZCfzcgo/ZbKLFgJ5OEwCreur4fRe8IMkT2KntW\nwj51mYFmNo0aIb0Yzhzu7nOVvMO3hmuLSaYMiz3bYX2DseyFsGxh+3ORsVr0nD0Q9m0w6E2l7zah\nNmmaB4myvl7Ybl40YEcFwsPxGzxBZjYdTZg+7+5Ph2VPeU4aomRS+x1338vivK8j0ERlKvWGsSFh\n1KiTxeLhxGcIWcWoL704HPPTKMnr62XXG/ZfiYL0RMW2WXLSRxFf7HvA711hz8pQrxVoFGiCtBEF\nYdgwBuxMrnSiu1+RO85YIrI5aEzt47qG/nkimrzmJ+LvQwXZM07t2cBjLnmZYej+3e/uR1oFn7EK\nySCLwAIZth/rSkXpbAbJfq3C4mKgr6KHeBt3f6aw/T7o5XiDuHbanWhWtDoyvvrKI1mBI2TKQB2U\nN2zMbCv0wP/M41PRAAAgAElEQVTZK1TrLei0mEIYl7oyvZ6gJnAYw4leIT9Sca4bw7XkBYS/hjxN\nS1M/CGSD+oeQZ/bTyOC8zN1PKw5cuXNMJDKwu/gXbyFu3c/Q/c4MsCg/xitS6sN2w8I1HI9I46fl\n1sVCRe+h2ePBiEt1J40aVaDBajE0CflFON49iDzsYd+XqXlmHsp7ZszsJyjBIKsbuRBwiLt/r2Dg\nTQWe8cCjaRVW8xJeSMRLSP0AOpTaIOaIhxhT/Y+qrRcNq0hb8s/HcyhZYGEiHDEPoT8zuxh5DDJe\nWsa3+Ska6BYN13SAu08M+1yBuKaVXKFC2+5Ak6a8d+QnVc+VidNazAz0qvtQ8g5PQjUZY5Ip4xEv\nragrWVYia39TZmZMXPsy4vgutUzHutOgsP8EIpOm0I62DNmIcbUz4nytiLxOF6G+c0xun+Kkdgga\n1PujW3YMMhyKulkTgoepWP3gy8gbX4afosnA0tTf621ocyyzmpr9yahPuzz3jsXaPRRFlD6A+sqz\nvJaUUqw8cRhyWkylMZyecbsPp9ygPiE2jhGElQOmEsRrc9dkiKI0GWkpXuPuJ1lJJrBX8Bkz9FTI\nchbiITPbqzgjs/pwTAxXoIcEM7vM3ft+UG8eEorC6mUqMmTigId4QbsLGTBFMdDxqPO501TgupiJ\nuhnK9mzgqnnN23QLqk+Yx5vB85K1bwTyoPUhP0A3wdVhEHgb+FqY9bzsFUXCzay/4dwvoHDgz0Pb\n70Aen2fQQJqFT5YKs9TdUWf8BzSJyXPn1gf2MLO6gQvp6UQLA4fjfRh5R74UZtJPUc6PKbv+YYib\nsjvqNLMwQrb+CBpDRZcjz8s2yGgZj7hbh3khw9bMXkG/e97AHYqykuYFzg6DV1mnvq27fzf74got\nbIcmAJei0Pa0cK6TTSGIP9D4vJfxLxan5iX8LPVewrLahtm1XUJc9f8Wi6ith843n+b/fmRwr0bh\n+UBhja9SGxzyHDFHAwjAal4vS/I68tD8Ohg1/0Rit3ku7ILAI6ZySXXiuBWXO8LLa0OW4aNN1scQ\ne4f/B1xiysRc0OQ5/gIKW32dRgqHoxBmGdfnfCKZmV7jk87jCmFnaPCsZgiTpo1prD2ZoSrMF8Pv\nCMZV+H4VmiAtZ/L47Q7MFYywy11VVRZx94tDX4wrwWsRKxR3z8G9nsuYRzFkCrqfW6J7fhT11Q/W\n9Iqkt2BMn47EbfPC2/0Zy8abxHmXAQ4z8TKz3y/W7lVQPzUOZY6ujELLscoTq5Z55yzH7fYSzUoz\nq+O6orHgEXd/smT7fPb8ycCvUSLPrWFdf/iMOnbykDXCzJZED+7bNAnHFPbLZ5zE0pkrlYRLjnk0\n4tdcgB6+3dDscQJSCt+8sH1MDPRc1BlkMfqGTFQr107bghIFfzNbGxkBq6H4/HroAe2rAJCHV/CA\nQlvLxFeLwrBD0IxqBerlRcYgT9z46Amqz93gNrdayOGLXiO8FkMOZbIK+yGC7l6ID/h15EE6PLfv\nSqizOQIZs0XOAlAarjsX3fdrUCbblMg2fer6yNDcHhnVn0O6ONmMs0+sNHKMt9x9ntz309z9G+H/\nu9x9g5Lrz8JS62azShOP7r7gRbkL2NoDB8bkyTuOmrFSvAdVoetmXsJYrdGjiIcvPkFNbR2kJ/cb\ni6f5v4ImAw3Ph4lPsmGV18/MzkPe1aws2iOIDrBX+B7Todqs8UjV96fEO7K21wpOl+1XLKM1qWr7\nsE/+HR4BzBfe4bxkyl/c/YaKd+cEJDpdNJax8szMDREXaV5X5uQaKFOwNOxmTbyhFg/zlXrgrSKr\nOLfNIKSuv5uLK3cz6l9vCN7DDZDR+cvC4Ueg53Jhd4/KaPQX1qhtl2FJL9eQa2ssC9e9JvCUu/83\nGClLeq2EVHH7vMTREPRe5DN729Uq3Bc9V5nBk9fgXJN6GaJFUF9UZqx+HBrCxX3NQP1M25EO6DGD\nzFpQN+7w+bakJBxTsn1fB9rBzjTWKWRcjdi6mBjogy79oPsR7+dyZLF/xmuijmXaaedTUZ4ovCwr\noofyBsS1iKbxxQyLXDurxFeLwrA3IFXorxaO8UEUiokqWFfMOkH8kynUstdA3sX10Cz6OhRy+I0X\nyNgWL7r9N8oLA1+GvE6ZXMA41OFkv0Vxlh+7lunUOsJi5+CuUkN96vrUOFrvQ544z22/grsPKznP\nu+4+tGTdk14humxm30a/VxaK2we4ygtFj8O2o8O6KI+v4hxFL+FVwG+zSZOV1xotPosbI2Heg8J+\n+dDsoSi7upjm/zTyrkSfj9ikrND2h9G7kw0kY6jPVHPE1apLTrLWam3mz7NQuN48D+fIJt6RdvSf\nDnX348L/RY2yn3jOS2qhIgDqZ6JhL4tzfdzFoduKenHtDN9GxPKrvKB5V3GNx1ExaWrXkC0xro51\n92i/H/ZZC3nrs0ntKGAXr4kkz0cb0hYmCYu8RFFULDaDix9a1LbLyPzroIn55dR7Y19pdSwreJNi\n20+wOI/uWq8P7ebH1nxdzmjliWYI4+JOSG0/q+YwAj2Xj1ExjiF6T91loMSaFdEkbU0ifEZ3/3zT\ndvWYQZb9QEV140y87x6UCpxxL/qbZdnf9lURX7NBMp95FyWRFo55JzJEMnG7XZAbfYPioBa2j4mB\n/h15ReZGRtcwxCPKP8zz547RV0alqlMzyTcc7+6nh+8TUEmeHZrerMZjlYqvWkEY1hSuGRSbvVkJ\nyT6sOySyOJt5vg91Pk9Sn/G1ZXhRd0IDwZbI43i5u19vubCgS4RzCaQZ1aD8bKFUFjIO7kcdfF+p\nLPRCtzXLr4LVq+v/GsksXElj0e5TUG3OWNmT7wM/iqzbF80Cd2/Shm3RbwkaqP4Slt+OtHomhO8P\nA/919w2tEO6vOHYrXsJorVF337nwLt4J7OPuj4T9JqLfel5q3MkyInH0+UDGeJ1wZKFtZR4iIJ7s\nYy2IX3YCVlFGK7JtdCIaDJIbwqehIgDibTboNRUG++wad3N5Vs+jXlwbNOit6jlvVzhOJZ/USmpP\nZr9VwZCdF4X47yNCi3AJnFYaVxXtyE9qH3VVuRiJOJ57oPf15CoDOhzndBSq3wKFGXdBHKyHifMs\nM9HYorbd09BQ+i63S2O9yoo2ja1YnfWvMR7de9SyZvPjqaE+e5T3U5+x0L77qdkRGQ5GBt94D9zN\nwj6xZIuRyPi9Gf32DahySOQ36rkPIj0Wl01AM/+Vu92+inZ/GbgXeDJ8Xx5lp1TtsywKN72ErPCr\n0Us2N6pnVtze0Iv48/DZhWB4lxx/g/AQ/RG5oKcgHtgLSCYgS6+O7fsI4s1k/KT7Y79NP+/Vgiis\nBvLmDQpt/AYKiT5ast8TLR5/PsRlehoZ8U+jWojN9lsIZU/eGL5nNSjvD98vRryvydSyvLLP24hA\nDMrmex4ZZEcjg/tulKF3f+58U2bwPm6DBvATUFJHbJvFwj2+mZqe1i3ImFg1rBubW3dzWLfYDLRr\nXWT8jkOq9+8A64R1LT1DaEB+PXxey31eR9pYIAMq+52Ghf8fpPFdfIDcu4hCidn/d6GB8So0ufkx\nEo38dNXzEdqRSY30tQuF4kGdeMOnyTVPAhbNfR+FMjBj214d2hz9NDnPZJQ9mX0fDkwu2fb+kv/v\nQ33yp1H4Z4OwfCXUV9wa7smNuXZdGbb5UHhun6EmtAnl7/2lyGCegEJR30JGemzbFSuue+OS5UeF\nv2dHPlcBi4f1Q5DD4CakW9ns99wPWLDw/NyA3o1vo8lZq+/UA4W/mcbax5BRdz9BHqWw32eRAbIh\n4kBnn+GRcxTftYZ3rh99QfaO5p+diRXbjwWG9OM8O+c+uyBx8TsRHegxav3b/5BD417g0DaOPxI5\nEfrVJ7p7z5L6zcw29np140Go3llp6u0AwH6EzDuIkkgb4CLtlxWRvS2yvRPEQFts02nUyqjcRK2M\nymNolv80sI9JpLFYnugtd9/VJLY5Ds16i96X/uJNakkERWHYaUSyqoJHp5I/Fpl5ZqKKKyIjsDL8\n45qlnhE+AO+6u1tNDPV/oa1b0xhev9ZDeS2UJXSGu18GXBY8Mu+4+3NWL9xa1OVpC+5+A3BDLlQU\n2+bfwEamzNrMG/pnD2KqYV0+fJ9f1wCLJ6JAzhvr7vcGb1Ume3Cuu9+XNanFaxvUfCv+bqqscAW6\nD/9B4eS6dxH9Zn3vogeeXMAobyQSfyLW10SejwaY2Z+QLMR4Gj0RTmPyTB7NxC/zOCH83ZlIbciK\nc0Bc/+mskm295P8haJC+xKTZdBeAuz8SnvG8XpOFc3zWxKUrS6Ipimtn+Criry6JMmivpxZJKeJh\nUybnft5YReFUM4uW2jPJrCzhjWWdJlDL4twIkfq/iZ6vM8zsK7Hjhb7gyx4ymMOy/5jZ1qgf+R5w\neK4/aBbxyUR+3wqe+peRoPF1SKMr41nebGZ5nmVM285Rf1gMOT7uBSpOB1CXHBY8qw3i0FbTZXuK\nNrUKA2IanDuhsXItr/FZT0LvyqboHT2uxev4gXav063sg89uwrA55NWNDT1EpwGjTXXl6mpSeSis\nPQDwjpdn3kURQiNfppFUHy05YUq1bidsO8Qlzke+00Qz7ycRP6e0eaEtx4VO6RJqKeJtweLiqxeH\n49cJwwbOweUmzkZDIduKcxyPBqeYqGJ/stcALrb6DLKMBH1zaP+F7n5/OP90MxviItNvhTwpGYYA\nT4TJhZvqFx5AqIrQDqyieLQpe/i62H6ubLJoiCEYYFUp8vltY6VIsrYdmvv6CQ98IzNbw8zeQQNb\nUay06vlt1pbseTgyhE+yWqPj8u8iojs01NcModl7wrEeIWRZm9mCZna4u/+44lpjmZnv8xDS9xaF\nYQsoil/uSnm1hltCO04sGBFXm+pZlsJVVulmaryzfbLnOII1wu9l1P92mW4bNFYEcFe4LC8XMgZ5\n1HbwWpLEQYX9YuLa2QSxru6klWeSPog8nRPC+3BXfjfkKSqTU/l15HiDYxMtk6TQUlQb3oPNzMJE\nOiOrP+SFWsUt4k9h8nE88hQ68Btrko2N7v2yXiOhL44M2/PC75O1e36aZC/3EwcjL+NyJirDKOJl\n6bJ+pVh5AlqYxHlJ1YDgFMnzEV9A3v+3Q5/UKh5G8lAn5JblubpN0VMcsiKsVm6iqpSQlxkvsxrW\nhERass8dyPtUJNVHdXdM2l0fb9VTWMH/mBDOUzobMrOPu/vVue9jUEmjaJmkJu3I80Yy8dVzUOik\nDD8nV8i2ymsTzjGdclHFQajCQh28SXZfOG5ZBtlu4TM36twXQCneLyGe31rBu/YBdK07oVn+1uFY\n16Nss1doA9ZC8eh2jtdJlD1vse8zeJ7hyGvSoGMU1hffxQNRosXj1EpHrY0GgYdQKOkK9Dv+EHkU\nLnT3hqoduXOUFWAulkqqgwdeXcVxd6ZQa7PJ9qW1ISPbVt63dmDlnNpB4fvj1Dxh30ITkN2oSKKx\nOO9uMXSfHwhG9qLo9/y8uy8RaVemh7Yp8gSeg3iS00O/ty4lossmzayszRmX7HY0wSutSVxxj45H\nhmhm6O0LPOfuMb5rywhG2HBqnLYqnmWdtp1JI/DzaJKbN9xfB37XaQdHaOs0cjw65AmOGkNWSBwp\nW5ZblxehjuFFNJHPqj58HBmIJyLjumjox5ILR6Ln+yIP6v1W0Gwsa1/dsXvRIAs/YIMUA+KA3F7Y\nduPism7B6kmkEFLqm+xTqiBfsv3tHiGUV2xf1mnOix6k/4vtF2bQN3quWHY4XsOyNtpSFF9dB3Xa\npYTU/pyncM6VvEbkHub1wn8bFGbP/T3Hh5AGzeposHkfIoRnhOkVEFekYSA2swM9KEO3cb6+Z8Ya\ni0c/hkJ2Y2isGzfTYRXSMMXvM3iePyDuVqZj9Le88WQlhG5EiM68Ew+isFrGp/tY+ExEZb0q1bet\npAAz8lyWwd19yzaucxAqVH1+xTYZFzRfG3JfDwkWhW2L9+0Zdz+w1fa02OZKORmrSKLJHSMr8fYF\nZFA/hpKVfokiBOciUeKYdEZ+UrAgyqgbjTxsfyxMEurkVFD1kSIWQN6R4kRrR2S8Rx0CrgzDQcgI\n60t8QUZov6gK1ljh4Hc0z8a+GfVNddEB4JyyiX8/2pV5i5d1SSaNRry7e2ITsarJWT+23zv39SjE\nl+uDqyTgOtQU/m/3Gn0idrzipMBRePh6lHzyXNhuIvpdR1DTbKxErxpk1xGRYgD2aOeHmlUws51Q\nGZWY2vmhXpEhZWY/QuVzrmnxXCcjvsgMhW3N7J+Up/4OQd6psUgaIu/Svs7bU3BeAXV4eXHNb7n7\nGGuzPFB/MKMeGysJEaMZ07Zoxr8VCmFe6Cqm3k77nnX30W3uU3VN/0OzwaLHdYYzljrQtk56yCp1\njMLyUQDu/mLFceoy9Uz8otHu3lBIObLv3ZRkZvbjeuZHnKglKSmr1GT/YeRqQ1Z4H5retxmFmX2C\nJp6w3LYLEUp+ucqOFevXLo2I/iuFQf4xRMwv5ZLGDP8waP8YlR9a2JrIqUSOuQGNE627kKd/Kppc\nTkL9w+pIj2/DZveqHVhFhYMm+21WWLQNer7WIc6FasbVip0j5i2+Celhnocm4vlx5PTiOGLK2N4O\nZYv/IbdqfiQkvB5NEJkEdqyCjhX0HK0NzcYMvcohW8pzdRFNooAbAaOsviDr/OiF6DYORR1Qhjq1\nc6oJ+AcA3zXFst+Dppya+ZGXK1/02anpCbWKf3pJ6NGkUTQedYp5r85riMvXDh5Bs+UG3kiYJTYj\npM4orOT/2PcYjiMXIjaFL3dHHJV70GDzlayTnsH2tYoyTo+hTNIo52gWoaptw8t3axvvZf+4Qkk6\nif45AmXrDgrLpgGnVjzvC1H7HV4GFgjHyYjZZci4OnUFmM1sS3e/yeJlzsomT79HmYp3okHsu6FN\nn/BIan4Ea1PznKxhZni8NmT0vnUSrvqCV+Q8YQeie/QrCp4wb0ySOBrxyLISb4+hkCHu/qyZPVpl\njAWcWVwQvCTjgEOtXk7lKHefYpKs6ZvAmHQTP4W8zUfGPOnZAGxmf0Res8nh+2pI5gZrFL3O9u2P\nx3odyisclMLF5RtDTQLmg6hf3zy2eT/aBbB+5i0O5/yPich/AuLZ5Y2819HzXcTzKIS6I/XJW6+j\n4uStoK793s8KOiVYqHDsusSgVg7QqwbZHWb2Qa+VehmKjJsh1Feofw11gt3GUK8v7H1b6MhfsSYl\nTLyCIF2yfZS42A+U9sTufjJwspl90yNCkW1iZ2Ssjg2ez4vy547MVIuE1BlFWYZY7HsMxczew1Aa\n9SHeRDeoRbTdAbp76STEzI4x8VYa6t31r3mda1uHkRl+UG/8DUX9xPJeK/i8LPArMzvI3X9eOM4C\nqPPPvw/ZvarMiPSSzEwzOwp5B2LZ02WTp2VznquyskpRlHlOUFiviLL71nFNxzBJuQC4IOcJ+zYK\n/ZThPc+VeEPJODua2Slh/fty/xPzDrl7UQU/W/4U8FWriS4fAOwfjNIRKHvRUYbsMShUmqm8V40z\nK+bGKoKBl9EIzqYmer0FEk9uJXs4hinEy4FVwpSM9BXk1V8Ohe+viIXYzKy/4ev3gjcqS17ISuNt\nYWaf8hZCo+4+ycymAB91905l84MMqQdD5KovvNvM6xzB3Wb2ZY9rNt7TygF6NWT5ECKd1mXaIE9F\ng5hit2FmT7j7B0rWRdXOLXCbrETpuGwANbOlEJGzr+I9Kk4cTeWuaPPIstl/P2f4zc4X4418ABVo\nLiWkzihM9S8zI3DX8D/h+2fcfbGS/bJr34wZDBFbtUzE3O7esYmTxYUa3dvgLfUywgx9G3d/qbC8\n3+HEinOdhTxvE3PLjnT3I/txrH6Hd02k/rY9JwMR1ljibWFgGcrLjnVk4M6Hrs3sF8CL2e9oTXi+\nZnYhGugz2ZE9EGd0dyuIXoftx3tJyaKS42cZ6vMRKQfmTTLFTVyn9YC7vcZ1jApsWz8oFGG/rCD4\n2ojXtgvwPZckSpQTXuGxHgds5SErtIVz5/vXeSgItlM/MaoTIm7l+LnzLEptHMgnBg1Dk7FmUjM9\n6yHbtmT576ymB9WHATDY9MdyPhjNWk7MLctfW9k1nY1mnVna8J5h2TbtNLhJKGYz2p/hNztfbLb8\nVSR1kZ+pQmdn6/mkhSKRs0oaIH/tMxQibtcLOiPwek2nORFzFY0xEI/MJDXSSXwUWMckO5F5o3ak\nFq5qZyCaEc9VvzwnAwmmTOTF0KTtbRSiyurXHtZCmHJGMdiqJWuqsA+qSpAlldyK+LkA7wRP3+Nm\n9g2kodZurcoTmm9SiXbkmPoVwy54i6Fex+9KapzwVmQmngZuN+nC5etoRrltrfSv1phQdnoL7Sie\n5wXa1GxsaEcvT5qslmmTIR+nHY46u6nufihdRH8sZzNbD3jWQyaXiXTaV2anwnsVK6fUVqZmQuuw\nSBZvbNlAgjXWuyudjc5uqPIsteN1avVcKAx1HtJNOgAR/DMvRDQ5yUOd2A62Yyz98JwMJJjEdA/L\nh/7C8sr6tU2OuRVKmCpqpMW2PRwRyqOSNd5GZnvhuOuiDM0FET9uAZQdOsPZ3W20oWU5pv56yMK+\n0WL11kQaJHKcI2LLvZXSRPXHKU0oa+c4nURPGmTWmGkzBng45mK0UGB5FjcxioLlXKmbFTrzrV2F\nXDdFobSMs7Cyu0c5C2Z2I/KIZcKRuyNRx35JUVTBVMvyLhQWHecdzH7sFcQG8U4P7J2Exevd3ePu\nX+xqw2YRrCbz0rAKlYrpmJfM6uUujkLegSW8Ju/Q1kA0A+0oZtEBnZGNmVWwQgZbYV1p/domxzwH\nicC+gvqwWxG/N8r9tHgmZalkTW6/p4lnK3ZUaqaE+vAq8vQfEjhysf2KEjA7UKs8ULcp/aRQWK1Y\n/WXhOH3F6s3sDBTar9Kc7DisifxKN9CrBtkkFLLLMm22QKG5fPhpEPJCneLuK0YOM6DRX86CKVvm\nVNTROKpDuL/PeAZJ7FzDkNDpJoiztiISZyxVy59dYLXM3gMRITfD/MAnvaKocTdhZg+4++q5v/Oi\nkk6bNN15DoeJlLwY9eHF0vfKlA18RO77D4DNsslRtwaiXoSZPe7uy5esK+XotnjsJdDE5FvIYO4o\nlceUTZhhOAqLfQ0JoEbRH++lmR2NsrsvQEbPboikPwH4mrtvXrLfol5fjgszW9HdS9vXj7bFitW/\nhHQmh6C6zrHyfLFjjULKBUUvf1vUJGtDfmVWoVc5ZHWZNu4+1lR/Kl+iYiqKBffqzL9fnAVXUsOs\nCkVMQ2ny05DGzAs0qQU5G2GgZ/aWIVrvrovt6QmY2TdRNty/qa/3Fx00ANz9iAg35TKrKX0PobxO\nbCfa3LSmaCfOM4twXwkP90vAeGuzxFzYd080mfwgMg5OQx6TjsIbNf5OMmU6v0mJ6HU/sWNhInhG\nmLx/28xiMhIZxpnZ9939YgAzOwSNm6t0oE0ZjHrN0GlIMqTtUDNwPgov7oB4xnsjtf224G3Ir8wq\n9KpB9t8ws78VON+UKffmQPVK9BMXAreY2UtoEB0HfeTWWOHVyvIQ3kQcsJ94DZVX+RlwZqTj6RmY\npA9ORp7F6Ujv6aAyN38I99xiZr9z97+Z2Tzu/lZs2wGGWL27Bl2mhAYcgOQLmj7jJdyUviLZpqy4\nmY5ZmSwyC3Agql+7B/H6tVeiPvKv1A/8VTgJ1es9HRjr7s90ssEZrD5TfhBq90NIa2t3ZLB3QvT6\nLTP7DDVdy11QkXKols/ZHBlvn0Ye4IdR1mUnEStWf3roOzdAFJ7XAUwiyCsjgy2Ghd39LDM7INcP\n31uybVN4/+RXZgp6NWQ5Aj1oWTmGBZDV/BpyBWdFgm8Gfu3u70UOM+DRDmfBWigPMRPatxOqqbce\n4hzcAdzq7jd2+lwzGyZV7V9Q497tBnzT3ddvst+GwFnoNxkdiKv7uvvXZ2qDO4AQch7u7g0GfkI9\nAjF+G2+hrmMzbop1sF7knIZAT2moX1tF42hyvFXRePFhFDZ71N0/16n2hnPkpWamosSsE7KQoBXK\nM3k/Ra8Lk0pH/N6DUObm2u5+W8W++yENxelI8uGO/rShSfvWor4G6/1h+f2EJInwfRCqZFCWfHOX\nu29gZn9BupTPA5d6RD6q19CTBlkZTIKJc6FisaACwNPc/Uvda9Wsh3WwJmCL51sJSZEcCCzq7nPP\nqnN3ChmnqrCsrmxOyX53o5noVTkC9ywha7cDUzbXc17L2i0qjbdVwHxOgdUqf6yKOJJ/pj5TsSHV\nvhk3xZrU2UxoH9Zmibmwz/zoN9oMhS4XAe5y970rd+wQrM3yTBXHOTaEJUsLbDfZ/6/IqNkfeD+a\nYN7q7t9q91glx68sTxQzpmP9cW7dDujdeT/iS8+PDNmrOtHebqKnDLJmnAjg6eIA2sqgOrvBZlGW\nn5ldBqyB3P63opfkHm9BPXygwMxGhn+/jUrTXISepV2Bhdz9sCb73+3u61uhgPRAe+asn1m7czqs\nJMU+g1ek2ltJkWzgRJ/J9SLnNISxYQQyllspMZcRzW8Ln1u9TfHsNttXlJrZGXmjZlj0OnASVwfG\n9+c5MrNPBD5V9n0Ikhg5ur9tipzjShRxaEiCMZWWupmaNtvXgS3c/ROdOn+voKcMsmYIg86n3f3J\n8H1Z5Mqcozq7mW2QZd4WVIPsfpTh2lQjbSDCainpMVKte5MUaDO7FHHoTkMZpwcA67j7blX7zWrY\nDCiNJ8w4ctyUzNCfKUXVE9rHzOZ/WlxqZjUkeg31Toa2Ey5CgsCXUZLRW9T3ZdPdfYH+t74zMLNb\ngQ8hLby8mOuOJp3OU9CkxYEbgQO9MfNzOHp//gNcjTItN0EOgaM9Ivjca+hZg8wiKeiIA3A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5CQ0BLMbBrwZmwVMNzdk5csoWeQDLKEhISEhISEhC4jhSwT5mgU6leCxGFfAm5z96e70KSEhISE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\nkJCQkJCQ0GX8P86hj8VxS8vFAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tNUnL83is0HI",
        "outputId": "d57e9bc5-7cac-4e89-c599-118346630188",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        }
      },
      "source": [
        "# opa... chegamos em algo que já ficou útil para destacar o epicentro\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "confirmed_by_country[last_date].sort_values(ascending=False)[:10].plot(kind='bar')\n",
        "plt.title(\"Confirmados por país\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1Tkl+o3cMcynJoiR/meTYJMdNvXrHNQ5J3pRkyyQbJzk9ycokL+wd1zgkeXyS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\nExMxSZKkTkzEJEmSOjERkyRJ6uT/A4iVp0UImIg9AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dgh4czZCtFT3",
        "outputId": "c9400d48-07d3-40a6-b54c-e48c33f29803",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 401
        }
      },
      "source": [
        "# aqui já vira uma comparação entre os países fora do epicentro\n",
        "\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "confirmed_by_country[last_date].sort_values(ascending=False)[1:10].plot(kind='bar')\n",
        "plt.title(\"Confirmados por país (amostra de 10 países)\")\n",
        "plt.show()\n",
        "\n",
        "# Lembrando que existe um vicio aqui pois paises que não testaram individuos\n",
        "# podem sim ter casos ocorrendo mas não confirmados ainda."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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VpvUa4LAkbwV+CXystX8M+EySRcDFdCGNqjotyeHA6cANwEuqaukteHxJkqQ1wmoFrqo6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\nlyRJUs/+Pz/F7bOTGo5zAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FEK-ZH3atS4P",
        "outputId": "9dc86011-fc42-4c16-ff3d-96090364132b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        }
      },
      "source": [
        "deaths = pd.read_csv(\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Deaths.csv\")\n",
        "recovered = pd.read_csv(\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Recovered.csv\")\n",
        "\n",
        "display(deaths.head())\n",
        "display(recovered.head())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Province/State</th>\n",
              "      <th>Country/Region</th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
              "      <th>1/23/20</th>\n",
              "      <th>1/24/20</th>\n",
              "      <th>1/25/20</th>\n",
              "      <th>1/26/20</th>\n",
              "      <th>1/27/20</th>\n",
              "      <th>1/28/20</th>\n",
              "      <th>1/29/20</th>\n",
              "      <th>1/30/20</th>\n",
              "      <th>1/31/20</th>\n",
              "      <th>2/1/20</th>\n",
              "      <th>2/2/20</th>\n",
              "      <th>2/3/20</th>\n",
              "      <th>2/4/20</th>\n",
              "      <th>2/5/20</th>\n",
              "      <th>2/6/20</th>\n",
              "      <th>2/7/20</th>\n",
              "      <th>2/8/20</th>\n",
              "      <th>2/9/20</th>\n",
              "      <th>2/10/20</th>\n",
              "      <th>2/11/20</th>\n",
              "      <th>2/12/20</th>\n",
              "      <th>2/13/20</th>\n",
              "      <th>2/14/20</th>\n",
              "      <th>2/15/20</th>\n",
              "      <th>2/16/20</th>\n",
              "      <th>2/17/20</th>\n",
              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
              "      <th>2/21/20</th>\n",
              "      <th>2/22/20</th>\n",
              "      <th>2/23/20</th>\n",
              "      <th>2/24/20</th>\n",
              "      <th>2/25/20</th>\n",
              "      <th>2/26/20</th>\n",
              "      <th>2/27/20</th>\n",
              "      <th>2/28/20</th>\n",
              "      <th>2/29/20</th>\n",
              "      <th>3/1/20</th>\n",
              "      <th>3/2/20</th>\n",
              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Anhui</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.8257</td>\n",
              "      <td>117.2264</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Beijing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>40.1824</td>\n",
              "      <td>116.4142</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.0572</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fujian</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.0789</td>\n",
              "      <td>117.9874</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gansu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.0611</td>\n",
              "      <td>103.8343</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>2</td>\n",
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              "      <td>2</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Province/State  Country/Region      Lat  ...  3/2/20  3/3/20  3/4/20\n",
              "0          Anhui  Mainland China  31.8257  ...       6       6       6\n",
              "1        Beijing  Mainland China  40.1824  ...       8       8       8\n",
              "2      Chongqing  Mainland China  30.0572  ...       6       6       6\n",
              "3         Fujian  Mainland China  26.0789  ...       1       1       1\n",
              "4          Gansu  Mainland China  36.0611  ...       2       2       2\n",
              "\n",
              "[5 rows x 47 columns]"
            ]
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              "      <th>3/4/20</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Anhui</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.8257</td>\n",
              "      <td>117.2264</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>14</td>\n",
              "      <td>20</td>\n",
              "      <td>23</td>\n",
              "      <td>34</td>\n",
              "      <td>47</td>\n",
              "      <td>59</td>\n",
              "      <td>72</td>\n",
              "      <td>88</td>\n",
              "      <td>105</td>\n",
              "      <td>127</td>\n",
              "      <td>157</td>\n",
              "      <td>193</td>\n",
              "      <td>221</td>\n",
              "      <td>255</td>\n",
              "      <td>280</td>\n",
              "      <td>361</td>\n",
              "      <td>413</td>\n",
              "      <td>474</td>\n",
              "      <td>539</td>\n",
              "      <td>597</td>\n",
              "      <td>637</td>\n",
              "      <td>663</td>\n",
              "      <td>712</td>\n",
              "      <td>744</td>\n",
              "      <td>792</td>\n",
              "      <td>821</td>\n",
              "      <td>868</td>\n",
              "      <td>873</td>\n",
              "      <td>917</td>\n",
              "      <td>936</td>\n",
              "      <td>956</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Beijing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>40.1824</td>\n",
              "      <td>116.4142</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>12</td>\n",
              "      <td>23</td>\n",
              "      <td>24</td>\n",
              "      <td>31</td>\n",
              "      <td>33</td>\n",
              "      <td>34</td>\n",
              "      <td>37</td>\n",
              "      <td>44</td>\n",
              "      <td>48</td>\n",
              "      <td>56</td>\n",
              "      <td>69</td>\n",
              "      <td>80</td>\n",
              "      <td>98</td>\n",
              "      <td>108</td>\n",
              "      <td>114</td>\n",
              "      <td>122</td>\n",
              "      <td>145</td>\n",
              "      <td>153</td>\n",
              "      <td>169</td>\n",
              "      <td>178</td>\n",
              "      <td>189</td>\n",
              "      <td>198</td>\n",
              "      <td>215</td>\n",
              "      <td>235</td>\n",
              "      <td>248</td>\n",
              "      <td>257</td>\n",
              "      <td>271</td>\n",
              "      <td>276</td>\n",
              "      <td>282</td>\n",
              "      <td>288</td>\n",
              "      <td>297</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.0572</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>24</td>\n",
              "      <td>31</td>\n",
              "      <td>39</td>\n",
              "      <td>51</td>\n",
              "      <td>66</td>\n",
              "      <td>79</td>\n",
              "      <td>102</td>\n",
              "      <td>128</td>\n",
              "      <td>152</td>\n",
              "      <td>184</td>\n",
              "      <td>207</td>\n",
              "      <td>225</td>\n",
              "      <td>254</td>\n",
              "      <td>274</td>\n",
              "      <td>299</td>\n",
              "      <td>316</td>\n",
              "      <td>328</td>\n",
              "      <td>335</td>\n",
              "      <td>349</td>\n",
              "      <td>372</td>\n",
              "      <td>384</td>\n",
              "      <td>401</td>\n",
              "      <td>422</td>\n",
              "      <td>438</td>\n",
              "      <td>450</td>\n",
              "      <td>469</td>\n",
              "      <td>490</td>\n",
              "      <td>502</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fujian</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.0789</td>\n",
              "      <td>117.9874</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>3</td>\n",
              "      <td>11</td>\n",
              "      <td>14</td>\n",
              "      <td>20</td>\n",
              "      <td>24</td>\n",
              "      <td>35</td>\n",
              "      <td>39</td>\n",
              "      <td>45</td>\n",
              "      <td>53</td>\n",
              "      <td>57</td>\n",
              "      <td>63</td>\n",
              "      <td>71</td>\n",
              "      <td>82</td>\n",
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              "      <td>93</td>\n",
              "      <td>112</td>\n",
              "      <td>126</td>\n",
              "      <td>149</td>\n",
              "      <td>162</td>\n",
              "      <td>170</td>\n",
              "      <td>183</td>\n",
              "      <td>199</td>\n",
              "      <td>218</td>\n",
              "      <td>228</td>\n",
              "      <td>235</td>\n",
              "      <td>243</td>\n",
              "      <td>247</td>\n",
              "      <td>255</td>\n",
              "      <td>260</td>\n",
              "      <td>270</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gansu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.0611</td>\n",
              "      <td>103.8343</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>12</td>\n",
              "      <td>16</td>\n",
              "      <td>17</td>\n",
              "      <td>24</td>\n",
              "      <td>31</td>\n",
              "      <td>39</td>\n",
              "      <td>39</td>\n",
              "      <td>49</td>\n",
              "      <td>54</td>\n",
              "      <td>58</td>\n",
              "      <td>62</td>\n",
              "      <td>65</td>\n",
              "      <td>71</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>78</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>81</td>\n",
              "      <td>81</td>\n",
              "      <td>82</td>\n",
              "      <td>82</td>\n",
              "      <td>84</td>\n",
              "      <td>85</td>\n",
              "      <td>86</td>\n",
              "      <td>87</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Province/State  Country/Region      Lat  ...  3/2/20  3/3/20  3/4/20\n",
              "0          Anhui  Mainland China  31.8257  ...     917     936     956\n",
              "1        Beijing  Mainland China  40.1824  ...     282     288     297\n",
              "2      Chongqing  Mainland China  30.0572  ...     469     490     502\n",
              "3         Fujian  Mainland China  26.0789  ...     255     260     270\n",
              "4          Gansu  Mainland China  36.0611  ...      85      86      87\n",
              "\n",
              "[5 rows x 47 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M0kwTOtOMiuO",
        "outputId": "1d275abc-7d9c-4969-c82b-3234cd8155fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        }
      },
      "source": [
        "def latest_by_country(data):\n",
        "  return data.groupby(\"Country/Region\").sum().iloc[:,-1]\n",
        "\n",
        "display(latest_by_country(confirmed).head())\n",
        "display(latest_by_country(deaths).head())\n",
        "display(latest_by_country(recovered).head())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Country/Region\n",
              "Afghanistan     1\n",
              "Algeria        12\n",
              "Andorra         1\n",
              "Argentina       1\n",
              "Armenia         1\n",
              "Name: 3/4/20, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Country/Region\n",
              "Afghanistan    0\n",
              "Algeria        0\n",
              "Andorra        0\n",
              "Argentina      0\n",
              "Armenia        0\n",
              "Name: 3/4/20, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Country/Region\n",
              "Afghanistan    0\n",
              "Algeria        0\n",
              "Andorra        0\n",
              "Argentina      0\n",
              "Armenia        0\n",
              "Name: 3/4/20, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "32ROBiGkNGGg",
        "outputId": "98340117-9991-43aa-ae38-9dc2f3cfad0f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        }
      },
      "source": [
        "informations = [latest_by_country(confirmed), latest_by_country(deaths), latest_by_country(recovered)]\n",
        "combined = pd.concat(informations, axis=1)\n",
        "combined.columns = [\"confirmed\", \"deaths\", \"recovered\"]\n",
        "combined.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andorra</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Armenia</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  recovered\n",
              "Country/Region                              \n",
              "Afghanistan             1       0          0\n",
              "Algeria                12       0          0\n",
              "Andorra                 1       0          0\n",
              "Argentina               1       0          0\n",
              "Armenia                 1       0          0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tKIRHu-zOEnq"
      },
      "source": [
        "# taxa de letalidade é expressa em %\n",
        "# o número de casos letais dentro dos casos que foram letais e não letais\n",
        "\n",
        "# imagina que existe uma doença que em janeiro de 2020 afetou 100 pessoas\n",
        "# 5 pessoas morreram (por exemplo). letalidade foi de 5%.\n",
        "# não digo que ela É de 5% para sempre pq a doença continuou existindo\n",
        "\n",
        "# conclusão é MUITO dificil de falar de letalidade tentando ser preciso\n",
        "# durante uma epidemia\n",
        "\n",
        "# no começo é comum que somente casos graves sejam reportados"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BqPEKZzpP8Dq",
        "outputId": "5a6e3ea9-5316-42f6-a821-49e8f1d953e6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "sum_up = combined.sum()\n",
        "letality_rate_1 = sum_up[\"deaths\"] / sum_up[\"confirmed\"]\n",
        "letality_rate_2 = sum_up[\"deaths\"] / (sum_up[\"deaths\"] + sum_up[\"recovered\"])\n",
        "print(letality_rate_1 * 100)\n",
        "print(letality_rate_2 * 100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "3.4207981161431396\n",
            "5.978870004593477\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fhBgxicja-I2",
        "outputId": "e3bfa16e-5b00-4582-f2fa-fa2a4fa2c016",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "def latest_by_country_at(data, date):\n",
        "  return data.groupby(\"Country/Region\").sum()[date]\n",
        "\n",
        "\n",
        "informations = [latest_by_country_at(confirmed, '2/20/20'), latest_by_country_at(deaths, '2/20/20'), latest_by_country_at(recovered, '2/20/20')]\n",
        "combined_2_20_20 = pd.concat(informations, axis=1)\n",
        "combined_2_20_20.columns = [\"confirmed\", \"deaths\", \"recovered\"]\n",
        "\n",
        "sum_up = combined_2_20_20.loc[\"Mainland China\"]\n",
        "letality_rate_1 = sum_up[\"deaths\"] / sum_up[\"confirmed\"]\n",
        "letality_rate_2 = sum_up[\"deaths\"] / (sum_up[\"deaths\"] + sum_up[\"recovered\"])\n",
        "print(letality_rate_1 * 100)\n",
        "print(letality_rate_2 * 100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2.981373084974466\n",
            "11.048522581282736\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "btr4elbUUdAM",
        "outputId": "12d2a239-0cd5-4395-c889-cb32f7df7a9c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        }
      },
      "source": [
        "display(sum_up)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "confirmed    74999\n",
              "deaths        2236\n",
              "recovered    18002\n",
              "Name: Mainland China, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Tjiw5LOHu3zl",
        "outputId": "384539bb-e2ca-423e-e878-4102913f15f8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        }
      },
      "source": [
        "informations = [latest_by_country_at(confirmed, '2/8/20'), latest_by_country_at(deaths, '2/20/20'), latest_by_country_at(recovered, '2/20/20')]\n",
        "combined_12 = pd.concat(informations, axis=1)\n",
        "combined_12.columns = [\"confirmed\", \"deaths\", \"recovered\"]\n",
        "\n",
        "sum_up = combined_12.loc[\"Mainland China\"]\n",
        "letality_rate_3 = sum_up[\"deaths\"] / sum_up[\"confirmed\"]\n",
        "print(letality_rate_3 * 100)\n",
        "display(sum_up)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "6.079721572679319\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "confirmed    36778\n",
              "deaths        2236\n",
              "recovered    18002\n",
              "Name: Mainland China, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8dGaO49zQIsz",
        "outputId": "4a2c7b8e-1d57-44e4-c59a-b2f610c7ae71",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        }
      },
      "source": [
        "letality_rate_1 = combined[\"deaths\"] / combined[\"confirmed\"] * 100\n",
        "letality_rate_2 = combined[\"deaths\"] / (combined[\"recovered\"] + combined[\"deaths\"]) * 100\n",
        "combined[\"letality_rate_1\"] = letality_rate_1\n",
        "combined[\"letality_rate_2\"] = letality_rate_2\n",
        "combined.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andorra</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Armenia</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  recovered  letality_rate_1  letality_rate_2\n",
              "Country/Region                                                                \n",
              "Afghanistan             1       0          0              0.0              NaN\n",
              "Algeria                12       0          0              0.0              NaN\n",
              "Andorra                 1       0          0              0.0              NaN\n",
              "Argentina               1       0          0              0.0              NaN\n",
              "Armenia                 1       0          0              0.0              NaN"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sVvk4OBBT8U0",
        "outputId": "815137f5-40cb-447d-d9c8-4ec80d0a84ee",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        }
      },
      "source": [
        "combined.sort_values(\"letality_rate_1\", ascending=False).head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Philippines</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>33.333333</td>\n",
              "      <td>50.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>US</th>\n",
              "      <td>153</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>7.189542</td>\n",
              "      <td>57.894737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>San Marino</th>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>6.250000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iraq</th>\n",
              "      <td>35</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>5.714286</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>52</td>\n",
              "      <td>2</td>\n",
              "      <td>11</td>\n",
              "      <td>3.846154</td>\n",
              "      <td>15.384615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>80271</td>\n",
              "      <td>2981</td>\n",
              "      <td>49955</td>\n",
              "      <td>3.713670</td>\n",
              "      <td>5.631328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>3089</td>\n",
              "      <td>107</td>\n",
              "      <td>276</td>\n",
              "      <td>3.463904</td>\n",
              "      <td>27.937337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iran</th>\n",
              "      <td>2922</td>\n",
              "      <td>92</td>\n",
              "      <td>552</td>\n",
              "      <td>3.148528</td>\n",
              "      <td>14.285714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Taiwan</th>\n",
              "      <td>42</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>2.380952</td>\n",
              "      <td>7.692308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Thailand</th>\n",
              "      <td>43</td>\n",
              "      <td>1</td>\n",
              "      <td>31</td>\n",
              "      <td>2.325581</td>\n",
              "      <td>3.125000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  recovered  letality_rate_1  letality_rate_2\n",
              "Country/Region                                                                \n",
              "Philippines             3       1          1        33.333333        50.000000\n",
              "US                    153      11          8         7.189542        57.894737\n",
              "San Marino             16       1          0         6.250000       100.000000\n",
              "Iraq                   35       2          0         5.714286       100.000000\n",
              "Australia              52       2         11         3.846154        15.384615\n",
              "Mainland China      80271    2981      49955         3.713670         5.631328\n",
              "Italy                3089     107        276         3.463904        27.937337\n",
              "Iran                 2922      92        552         3.148528        14.285714\n",
              "Taiwan                 42       1         12         2.380952         7.692308\n",
              "Thailand               43       1         31         2.325581         3.125000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g9Xq-twUV946",
        "outputId": "0ac19631-acd6-4b36-ba22-8d65829f8795",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "# visualização horrenda\n",
        "\n",
        "combined[[\"confirmed\", \"letality_rate_1\"]].plot()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa163c817b8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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coM8grZCKQO3A2DMxY2AYESc8pDRykUuNPQYzBoYRcRKhIaXmhWwUCzMGhhFxwjWDKPQb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\nYWDGwDAMw8CMgWEYhoEZA8MwDAP4/3K3ghwQxs+gAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X3ijDX-wWt69"
      },
      "source": [
        "# combined[[\"confirmed\", \"letality_rate_1\"]].plot(kind='scatter')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZctRDUktW-Xu",
        "outputId": "7fdb2025-d442-47f4-87e9-6d68759aee4c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "source": [
        "import seaborn as sns\n",
        "\n",
        "sns.scatterplot(data = combined, x=\"confirmed\", y=\"letality_rate_1\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1584f9b70>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SB3wBZu80lZvmH8pQwLQpbezaPdUHe82s9Fo2/Mc702fX7qlFl2ZmVriW7fbxmT5mZuNr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\nTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hj75tt1YXH0x",
        "outputId": "2db9d14a-0ab6-4c6e-93ca-7732fb1951a0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "sns.scatterplot(data = combined.query(\"confirmed > 40 and confirmed < 50000\"), x=\"confirmed\", y=\"letality_rate_1\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa155c7aac8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "urYCHsI5XY-h",
        "outputId": "9c88bd9f-cf84-4e13-fdf6-110b42c0aae8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "sns.scatterplot(data = combined.query(\"confirmed > 40\"), x=\"confirmed\", y=\"letality_rate_1\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa155bece10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FFDZa1D8Xtw1",
        "outputId": "f7a44670-4dc9-4877-be23-02f028beb6d1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "sns.scatterplot(data = combined.query(\"recovered > 40\"), x=\"confirmed\", y=\"letality_rate_2\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa155b6a630>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vT3fbtmH4S9ISM9Tfy6YNo7M7gJk+/6H+3rZtwxO+krTEdHUF61cPcNPFp3i1jyTVSVdX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\nGjL8JamGDH9JqqH/DxFNP5grwV1WAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IVTRP8pIX8sZ",
        "outputId": "ed15b274-a199-4863-9b4e-1719c9838a14",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "sns.distplot(combined.query(\"confirmed > 40\")[\"letality_rate_1\"], kde=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa155b0db70>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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HVrjOJcBnGAT8XODSIfe/tqp+1H2+P4NrsxzG4Lraey7zz3JakucOi+wFrGPw5hlSbwy4\npkWAj1TVPzxv4+BNJ3Z0NjAD/FJV/bC7hOteK12kqh5O8v0kJzDY2z97yEN23Gv+EHBrVZ3RzXXb\nEo8J8Oaq+tpK55JG4TFwTYvPA+d2bzRBkkOS/BzwJLDfDvfbn8GbJ/wwya8DrxzyfRc+HgZve3YF\nz9+7Xon9+cm16M9ZZo3PA+/tLt1LkqN3Yg1pxQy4pkJV3QxcBdyZ5F4GF/Dfr6r+C/j37knJjwNX\nArPdfX6L4dcHvxU44rknGLttNzE4RDPs8MlCHwM+kuRunv/b68I1PsTg8MpXk9zf3V5S91vEhcA5\nSbYlOWIn59JuysvJareTZBb426p67aRnkcbhMXDtVpKcD/wOw499S1PPPXDt9pJ8APjNBZuvraq/\n6nGN3wD+esHmb1fVGX2tod2PAZekRvkkpiQ1yoBLUqMMuCQ1yoBLUqP+HwjGsgfDrpEdAAAAAElF\nTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a13ayKgsYYFd",
        "outputId": "581a712f-5087-4091-8a99-1ebae82041e5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "# grafico nao faz sentido pois so tem 3 pontos ainda\n",
        "\n",
        "sns.distplot(combined.query(\"recovered > 40\")[\"letality_rate_2\"], kde=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa155ac0198>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FOv2GIWhSVX2BwRNECy0ccmEv8K/WtKh1UFUPVtXBbvm7DP4Sb2XK+qIGHu9WN3efAi5g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\nS1IjDHRJaoSBLkmN+H/zcFQvPOqdEwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z6Zt0jnAY7QX",
        "outputId": "c840e564-7998-4e9f-9dde-1814050f4a9f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        }
      },
      "source": [
        "combined.sort_values(\"letality_rate_1\", ascending=False).query(\"confirmed > 40\").head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>US</th>\n",
              "      <td>153</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>7.189542</td>\n",
              "      <td>57.894737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>52</td>\n",
              "      <td>2</td>\n",
              "      <td>11</td>\n",
              "      <td>3.846154</td>\n",
              "      <td>15.384615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>80271</td>\n",
              "      <td>2981</td>\n",
              "      <td>49955</td>\n",
              "      <td>3.713670</td>\n",
              "      <td>5.631328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>3089</td>\n",
              "      <td>107</td>\n",
              "      <td>276</td>\n",
              "      <td>3.463904</td>\n",
              "      <td>27.937337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iran</th>\n",
              "      <td>2922</td>\n",
              "      <td>92</td>\n",
              "      <td>552</td>\n",
              "      <td>3.148528</td>\n",
              "      <td>14.285714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Taiwan</th>\n",
              "      <td>42</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>2.380952</td>\n",
              "      <td>7.692308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Thailand</th>\n",
              "      <td>43</td>\n",
              "      <td>1</td>\n",
              "      <td>31</td>\n",
              "      <td>2.325581</td>\n",
              "      <td>3.125000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hong Kong</th>\n",
              "      <td>105</td>\n",
              "      <td>2</td>\n",
              "      <td>37</td>\n",
              "      <td>1.904762</td>\n",
              "      <td>5.128205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>331</td>\n",
              "      <td>6</td>\n",
              "      <td>43</td>\n",
              "      <td>1.812689</td>\n",
              "      <td>12.244898</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>France</th>\n",
              "      <td>285</td>\n",
              "      <td>4</td>\n",
              "      <td>12</td>\n",
              "      <td>1.403509</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  recovered  letality_rate_1  letality_rate_2\n",
              "Country/Region                                                                \n",
              "US                    153      11          8         7.189542        57.894737\n",
              "Australia              52       2         11         3.846154        15.384615\n",
              "Mainland China      80271    2981      49955         3.713670         5.631328\n",
              "Italy                3089     107        276         3.463904        27.937337\n",
              "Iran                 2922      92        552         3.148528        14.285714\n",
              "Taiwan                 42       1         12         2.380952         7.692308\n",
              "Thailand               43       1         31         2.325581         3.125000\n",
              "Hong Kong             105       2         37         1.904762         5.128205\n",
              "Japan                 331       6         43         1.812689        12.244898\n",
              "France                285       4         12         1.403509        25.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rVLYH54AZPb0",
        "outputId": "65d29889-c056-45ab-be8a-11293f46140b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        }
      },
      "source": [
        "combined.sort_values(\"letality_rate_2\", ascending=False).query(\"recovered > 40\").head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country/Region</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>South Korea</th>\n",
              "      <td>5621</td>\n",
              "      <td>35</td>\n",
              "      <td>41</td>\n",
              "      <td>0.622665</td>\n",
              "      <td>46.052632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>3089</td>\n",
              "      <td>107</td>\n",
              "      <td>276</td>\n",
              "      <td>3.463904</td>\n",
              "      <td>27.937337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iran</th>\n",
              "      <td>2922</td>\n",
              "      <td>92</td>\n",
              "      <td>552</td>\n",
              "      <td>3.148528</td>\n",
              "      <td>14.285714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>331</td>\n",
              "      <td>6</td>\n",
              "      <td>43</td>\n",
              "      <td>1.812689</td>\n",
              "      <td>12.244898</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>80271</td>\n",
              "      <td>2981</td>\n",
              "      <td>49955</td>\n",
              "      <td>3.713670</td>\n",
              "      <td>5.631328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Singapore</th>\n",
              "      <td>110</td>\n",
              "      <td>0</td>\n",
              "      <td>78</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  recovered  letality_rate_1  letality_rate_2\n",
              "Country/Region                                                                \n",
              "South Korea          5621      35         41         0.622665        46.052632\n",
              "Italy                3089     107        276         3.463904        27.937337\n",
              "Iran                 2922      92        552         3.148528        14.285714\n",
              "Japan                 331       6         43         1.812689        12.244898\n",
              "Mainland China      80271    2981      49955         3.713670         5.631328\n",
              "Singapore             110       0         78         0.000000         0.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3o3T3Wb3-REV"
      },
      "source": [
        "# Segunda parte"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rcsdN1OV_ooc"
      },
      "source": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ub3cZA6U-SiZ",
        "outputId": "c99e34bb-8f66-4909-866c-e05a41a1b18b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        }
      },
      "source": [
        "confirmed.set_index(\"Country/Region\").loc[\"Mainland China\"].sum().tail()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2/29/20    79251\n",
              "3/1/20     79826\n",
              "3/2/20     80026\n",
              "3/3/20     80151\n",
              "3/4/20     80271\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zo6q608_-UYL",
        "outputId": "5d816da5-c25d-4865-80e3-e42697bd6462",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        }
      },
      "source": [
        "is_mainland = confirmed[\"Country/Region\"] == \"Mainland China\"\n",
        "is_mainland.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    True\n",
              "1    True\n",
              "2    True\n",
              "3    True\n",
              "4    True\n",
              "Name: Country/Region, dtype: bool"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UrMAbkyM_gby",
        "outputId": "ad5f4705-d0ea-4e19-a3a0-d4c8e00fe254",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        }
      },
      "source": [
        "confirmed[\"is_mainland_china\"] = is_mainland\n",
        "display(confirmed.head())\n",
        "display(confirmed.tail())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "      <td>Anhui</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.8257</td>\n",
              "      <td>117.2264</td>\n",
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              "      <td>733</td>\n",
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              "      <td>830</td>\n",
              "      <td>860</td>\n",
              "      <td>889</td>\n",
              "      <td>910</td>\n",
              "      <td>934</td>\n",
              "      <td>950</td>\n",
              "      <td>962</td>\n",
              "      <td>973</td>\n",
              "      <td>982</td>\n",
              "      <td>986</td>\n",
              "      <td>987</td>\n",
              "      <td>988</td>\n",
              "      <td>989</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Beijing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>40.1824</td>\n",
              "      <td>116.4142</td>\n",
              "      <td>14</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.0572</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>27</td>\n",
              "      <td>57</td>\n",
              "      <td>75</td>\n",
              "      <td>110</td>\n",
              "      <td>132</td>\n",
              "      <td>147</td>\n",
              "      <td>182</td>\n",
              "      <td>211</td>\n",
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              "      <td>529</td>\n",
              "      <td>537</td>\n",
              "      <td>544</td>\n",
              "      <td>551</td>\n",
              "      <td>553</td>\n",
              "      <td>555</td>\n",
              "      <td>560</td>\n",
              "      <td>567</td>\n",
              "      <td>572</td>\n",
              "      <td>573</td>\n",
              "      <td>575</td>\n",
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              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fujian</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.0789</td>\n",
              "      <td>117.9874</td>\n",
              "      <td>1</td>\n",
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              "      <td>18</td>\n",
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              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gansu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.0611</td>\n",
              "      <td>103.8343</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>40</td>\n",
              "      <td>51</td>\n",
              "      <td>55</td>\n",
              "      <td>57</td>\n",
              "      <td>62</td>\n",
              "      <td>62</td>\n",
              "      <td>67</td>\n",
              "      <td>79</td>\n",
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              "      <td>87</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
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              "      <td>91</td>\n",
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              "      <td>91</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Province/State  Country/Region      Lat  ...  3/3/20  3/4/20  is_mainland_china\n",
              "0          Anhui  Mainland China  31.8257  ...     990     990               True\n",
              "1        Beijing  Mainland China  40.1824  ...     414     418               True\n",
              "2      Chongqing  Mainland China  30.0572  ...     576     576               True\n",
              "3         Fujian  Mainland China  26.0789  ...     296     296               True\n",
              "4          Gansu  Mainland China  36.0611  ...      91      91               True\n",
              "\n",
              "[5 rows x 48 columns]"
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>156</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Liechtenstein</td>\n",
              "      <td>47.1400</td>\n",
              "      <td>9.5500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Poland</td>\n",
              "      <td>51.9194</td>\n",
              "      <td>19.1451</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Tunisia</td>\n",
              "      <td>34.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>Contra Costa County, CA</td>\n",
              "      <td>US</td>\n",
              "      <td>37.8534</td>\n",
              "      <td>-121.9018</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Province/State Country/Region  ...  3/4/20  is_mainland_china\n",
              "155                      NaN      Gibraltar  ...       1              False\n",
              "156                      NaN  Liechtenstein  ...       1              False\n",
              "157                      NaN         Poland  ...       1              False\n",
              "158                      NaN        Tunisia  ...       1              False\n",
              "159  Contra Costa County, CA             US  ...       1              False\n",
              "\n",
              "[5 rows x 48 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H0VQ36pv_vi8",
        "outputId": "6a880760-feff-4c41-ede8-b5f22a2fb98b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 998
        }
      },
      "source": [
        "# query só de mainland china\n",
        "confirmed.query(\"is_mainland_china\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Province/State</th>\n",
              "      <th>Country/Region</th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
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              "      <th>2/3/20</th>\n",
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              "      <th>2/17/20</th>\n",
              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
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              "      <th>2/29/20</th>\n",
              "      <th>3/1/20</th>\n",
              "      <th>3/2/20</th>\n",
              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
              "      <th>is_mainland_china</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Anhui</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.82570</td>\n",
              "      <td>117.2264</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
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              "      <td>106</td>\n",
              "      <td>152</td>\n",
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              "      <td>237</td>\n",
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              "      <td>340</td>\n",
              "      <td>408</td>\n",
              "      <td>480</td>\n",
              "      <td>530</td>\n",
              "      <td>591</td>\n",
              "      <td>665</td>\n",
              "      <td>733</td>\n",
              "      <td>779</td>\n",
              "      <td>830</td>\n",
              "      <td>860</td>\n",
              "      <td>889</td>\n",
              "      <td>910</td>\n",
              "      <td>934</td>\n",
              "      <td>950</td>\n",
              "      <td>962</td>\n",
              "      <td>973</td>\n",
              "      <td>982</td>\n",
              "      <td>986</td>\n",
              "      <td>987</td>\n",
              "      <td>988</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Beijing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>40.18240</td>\n",
              "      <td>116.4142</td>\n",
              "      <td>14</td>\n",
              "      <td>22</td>\n",
              "      <td>36</td>\n",
              "      <td>41</td>\n",
              "      <td>68</td>\n",
              "      <td>80</td>\n",
              "      <td>91</td>\n",
              "      <td>111</td>\n",
              "      <td>114</td>\n",
              "      <td>139</td>\n",
              "      <td>168</td>\n",
              "      <td>191</td>\n",
              "      <td>212</td>\n",
              "      <td>228</td>\n",
              "      <td>253</td>\n",
              "      <td>274</td>\n",
              "      <td>297</td>\n",
              "      <td>315</td>\n",
              "      <td>326</td>\n",
              "      <td>337</td>\n",
              "      <td>342</td>\n",
              "      <td>352</td>\n",
              "      <td>366</td>\n",
              "      <td>372</td>\n",
              "      <td>375</td>\n",
              "      <td>380</td>\n",
              "      <td>381</td>\n",
              "      <td>387</td>\n",
              "      <td>393</td>\n",
              "      <td>395</td>\n",
              "      <td>396</td>\n",
              "      <td>399</td>\n",
              "      <td>399</td>\n",
              "      <td>399</td>\n",
              "      <td>400</td>\n",
              "      <td>400</td>\n",
              "      <td>410</td>\n",
              "      <td>410</td>\n",
              "      <td>411</td>\n",
              "      <td>413</td>\n",
              "      <td>414</td>\n",
              "      <td>414</td>\n",
              "      <td>418</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.05720</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>27</td>\n",
              "      <td>57</td>\n",
              "      <td>75</td>\n",
              "      <td>110</td>\n",
              "      <td>132</td>\n",
              "      <td>147</td>\n",
              "      <td>182</td>\n",
              "      <td>211</td>\n",
              "      <td>247</td>\n",
              "      <td>300</td>\n",
              "      <td>337</td>\n",
              "      <td>366</td>\n",
              "      <td>389</td>\n",
              "      <td>411</td>\n",
              "      <td>426</td>\n",
              "      <td>428</td>\n",
              "      <td>468</td>\n",
              "      <td>486</td>\n",
              "      <td>505</td>\n",
              "      <td>518</td>\n",
              "      <td>529</td>\n",
              "      <td>537</td>\n",
              "      <td>544</td>\n",
              "      <td>551</td>\n",
              "      <td>553</td>\n",
              "      <td>555</td>\n",
              "      <td>560</td>\n",
              "      <td>567</td>\n",
              "      <td>572</td>\n",
              "      <td>573</td>\n",
              "      <td>575</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fujian</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.07890</td>\n",
              "      <td>117.9874</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>18</td>\n",
              "      <td>35</td>\n",
              "      <td>59</td>\n",
              "      <td>80</td>\n",
              "      <td>84</td>\n",
              "      <td>101</td>\n",
              "      <td>120</td>\n",
              "      <td>144</td>\n",
              "      <td>159</td>\n",
              "      <td>179</td>\n",
              "      <td>194</td>\n",
              "      <td>205</td>\n",
              "      <td>215</td>\n",
              "      <td>224</td>\n",
              "      <td>239</td>\n",
              "      <td>250</td>\n",
              "      <td>261</td>\n",
              "      <td>267</td>\n",
              "      <td>272</td>\n",
              "      <td>279</td>\n",
              "      <td>281</td>\n",
              "      <td>285</td>\n",
              "      <td>287</td>\n",
              "      <td>290</td>\n",
              "      <td>292</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>294</td>\n",
              "      <td>294</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gansu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.06110</td>\n",
              "      <td>103.8343</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>40</td>\n",
              "      <td>51</td>\n",
              "      <td>55</td>\n",
              "      <td>57</td>\n",
              "      <td>62</td>\n",
              "      <td>62</td>\n",
              "      <td>67</td>\n",
              "      <td>79</td>\n",
              "      <td>83</td>\n",
              "      <td>83</td>\n",
              "      <td>86</td>\n",
              "      <td>87</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Guangdong</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>23.34170</td>\n",
              "      <td>113.4244</td>\n",
              "      <td>26</td>\n",
              "      <td>32</td>\n",
              "      <td>53</td>\n",
              "      <td>78</td>\n",
              "      <td>111</td>\n",
              "      <td>151</td>\n",
              "      <td>207</td>\n",
              "      <td>277</td>\n",
              "      <td>354</td>\n",
              "      <td>436</td>\n",
              "      <td>535</td>\n",
              "      <td>632</td>\n",
              "      <td>725</td>\n",
              "      <td>813</td>\n",
              "      <td>895</td>\n",
              "      <td>970</td>\n",
              "      <td>1034</td>\n",
              "      <td>1095</td>\n",
              "      <td>1131</td>\n",
              "      <td>1159</td>\n",
              "      <td>1177</td>\n",
              "      <td>1219</td>\n",
              "      <td>1241</td>\n",
              "      <td>1261</td>\n",
              "      <td>1294</td>\n",
              "      <td>1316</td>\n",
              "      <td>1322</td>\n",
              "      <td>1328</td>\n",
              "      <td>1331</td>\n",
              "      <td>1332</td>\n",
              "      <td>1333</td>\n",
              "      <td>1339</td>\n",
              "      <td>1342</td>\n",
              "      <td>1345</td>\n",
              "      <td>1347</td>\n",
              "      <td>1347</td>\n",
              "      <td>1347</td>\n",
              "      <td>1348</td>\n",
              "      <td>1349</td>\n",
              "      <td>1349</td>\n",
              "      <td>1350</td>\n",
              "      <td>1350</td>\n",
              "      <td>1350</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Guangxi</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>23.82980</td>\n",
              "      <td>108.7881</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>36</td>\n",
              "      <td>46</td>\n",
              "      <td>51</td>\n",
              "      <td>58</td>\n",
              "      <td>78</td>\n",
              "      <td>87</td>\n",
              "      <td>100</td>\n",
              "      <td>111</td>\n",
              "      <td>127</td>\n",
              "      <td>139</td>\n",
              "      <td>150</td>\n",
              "      <td>168</td>\n",
              "      <td>172</td>\n",
              "      <td>183</td>\n",
              "      <td>195</td>\n",
              "      <td>210</td>\n",
              "      <td>215</td>\n",
              "      <td>222</td>\n",
              "      <td>222</td>\n",
              "      <td>226</td>\n",
              "      <td>235</td>\n",
              "      <td>237</td>\n",
              "      <td>238</td>\n",
              "      <td>242</td>\n",
              "      <td>244</td>\n",
              "      <td>245</td>\n",
              "      <td>246</td>\n",
              "      <td>249</td>\n",
              "      <td>249</td>\n",
              "      <td>251</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>252</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Guizhou</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.81540</td>\n",
              "      <td>106.8748</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>12</td>\n",
              "      <td>29</td>\n",
              "      <td>29</td>\n",
              "      <td>38</td>\n",
              "      <td>46</td>\n",
              "      <td>58</td>\n",
              "      <td>64</td>\n",
              "      <td>71</td>\n",
              "      <td>81</td>\n",
              "      <td>89</td>\n",
              "      <td>99</td>\n",
              "      <td>109</td>\n",
              "      <td>127</td>\n",
              "      <td>133</td>\n",
              "      <td>135</td>\n",
              "      <td>140</td>\n",
              "      <td>143</td>\n",
              "      <td>144</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Hainan</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>19.19590</td>\n",
              "      <td>109.7453</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>19</td>\n",
              "      <td>22</td>\n",
              "      <td>33</td>\n",
              "      <td>40</td>\n",
              "      <td>43</td>\n",
              "      <td>46</td>\n",
              "      <td>52</td>\n",
              "      <td>62</td>\n",
              "      <td>64</td>\n",
              "      <td>72</td>\n",
              "      <td>80</td>\n",
              "      <td>99</td>\n",
              "      <td>106</td>\n",
              "      <td>117</td>\n",
              "      <td>124</td>\n",
              "      <td>131</td>\n",
              "      <td>138</td>\n",
              "      <td>144</td>\n",
              "      <td>157</td>\n",
              "      <td>157</td>\n",
              "      <td>159</td>\n",
              "      <td>162</td>\n",
              "      <td>162</td>\n",
              "      <td>163</td>\n",
              "      <td>163</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Hebei</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>38.04280</td>\n",
              "      <td>114.5149</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>33</td>\n",
              "      <td>48</td>\n",
              "      <td>65</td>\n",
              "      <td>82</td>\n",
              "      <td>96</td>\n",
              "      <td>104</td>\n",
              "      <td>113</td>\n",
              "      <td>126</td>\n",
              "      <td>135</td>\n",
              "      <td>157</td>\n",
              "      <td>172</td>\n",
              "      <td>195</td>\n",
              "      <td>206</td>\n",
              "      <td>218</td>\n",
              "      <td>239</td>\n",
              "      <td>251</td>\n",
              "      <td>265</td>\n",
              "      <td>283</td>\n",
              "      <td>291</td>\n",
              "      <td>300</td>\n",
              "      <td>301</td>\n",
              "      <td>306</td>\n",
              "      <td>306</td>\n",
              "      <td>307</td>\n",
              "      <td>308</td>\n",
              "      <td>309</td>\n",
              "      <td>311</td>\n",
              "      <td>311</td>\n",
              "      <td>311</td>\n",
              "      <td>312</td>\n",
              "      <td>317</td>\n",
              "      <td>318</td>\n",
              "      <td>318</td>\n",
              "      <td>318</td>\n",
              "      <td>318</td>\n",
              "      <td>318</td>\n",
              "      <td>318</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Heilongjiang</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>47.86200</td>\n",
              "      <td>127.7615</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>21</td>\n",
              "      <td>33</td>\n",
              "      <td>38</td>\n",
              "      <td>44</td>\n",
              "      <td>59</td>\n",
              "      <td>80</td>\n",
              "      <td>95</td>\n",
              "      <td>121</td>\n",
              "      <td>155</td>\n",
              "      <td>190</td>\n",
              "      <td>227</td>\n",
              "      <td>277</td>\n",
              "      <td>295</td>\n",
              "      <td>307</td>\n",
              "      <td>331</td>\n",
              "      <td>360</td>\n",
              "      <td>378</td>\n",
              "      <td>395</td>\n",
              "      <td>419</td>\n",
              "      <td>425</td>\n",
              "      <td>445</td>\n",
              "      <td>457</td>\n",
              "      <td>464</td>\n",
              "      <td>470</td>\n",
              "      <td>476</td>\n",
              "      <td>479</td>\n",
              "      <td>479</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>480</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Henan</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>33.88202</td>\n",
              "      <td>113.6140</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>9</td>\n",
              "      <td>32</td>\n",
              "      <td>83</td>\n",
              "      <td>128</td>\n",
              "      <td>168</td>\n",
              "      <td>206</td>\n",
              "      <td>278</td>\n",
              "      <td>352</td>\n",
              "      <td>422</td>\n",
              "      <td>493</td>\n",
              "      <td>566</td>\n",
              "      <td>675</td>\n",
              "      <td>764</td>\n",
              "      <td>851</td>\n",
              "      <td>914</td>\n",
              "      <td>981</td>\n",
              "      <td>1033</td>\n",
              "      <td>1073</td>\n",
              "      <td>1105</td>\n",
              "      <td>1135</td>\n",
              "      <td>1169</td>\n",
              "      <td>1184</td>\n",
              "      <td>1212</td>\n",
              "      <td>1231</td>\n",
              "      <td>1246</td>\n",
              "      <td>1257</td>\n",
              "      <td>1262</td>\n",
              "      <td>1265</td>\n",
              "      <td>1267</td>\n",
              "      <td>1270</td>\n",
              "      <td>1271</td>\n",
              "      <td>1271</td>\n",
              "      <td>1271</td>\n",
              "      <td>1271</td>\n",
              "      <td>1272</td>\n",
              "      <td>1272</td>\n",
              "      <td>1272</td>\n",
              "      <td>1272</td>\n",
              "      <td>1272</td>\n",
              "      <td>1272</td>\n",
              "      <td>1272</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Hubei</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.97560</td>\n",
              "      <td>112.2707</td>\n",
              "      <td>444</td>\n",
              "      <td>444</td>\n",
              "      <td>549</td>\n",
              "      <td>761</td>\n",
              "      <td>1058</td>\n",
              "      <td>1423</td>\n",
              "      <td>3554</td>\n",
              "      <td>3554</td>\n",
              "      <td>4903</td>\n",
              "      <td>5806</td>\n",
              "      <td>7153</td>\n",
              "      <td>11177</td>\n",
              "      <td>13522</td>\n",
              "      <td>16678</td>\n",
              "      <td>19665</td>\n",
              "      <td>22112</td>\n",
              "      <td>24953</td>\n",
              "      <td>27100</td>\n",
              "      <td>29631</td>\n",
              "      <td>31728</td>\n",
              "      <td>33366</td>\n",
              "      <td>33366</td>\n",
              "      <td>48206</td>\n",
              "      <td>54406</td>\n",
              "      <td>56249</td>\n",
              "      <td>58182</td>\n",
              "      <td>59989</td>\n",
              "      <td>61682</td>\n",
              "      <td>62031</td>\n",
              "      <td>62442</td>\n",
              "      <td>62662</td>\n",
              "      <td>64084</td>\n",
              "      <td>64084</td>\n",
              "      <td>64287</td>\n",
              "      <td>64786</td>\n",
              "      <td>65187</td>\n",
              "      <td>65596</td>\n",
              "      <td>65914</td>\n",
              "      <td>66337</td>\n",
              "      <td>66907</td>\n",
              "      <td>67103</td>\n",
              "      <td>67217</td>\n",
              "      <td>67332</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Hunan</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>27.61040</td>\n",
              "      <td>111.7088</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>24</td>\n",
              "      <td>43</td>\n",
              "      <td>69</td>\n",
              "      <td>100</td>\n",
              "      <td>143</td>\n",
              "      <td>221</td>\n",
              "      <td>277</td>\n",
              "      <td>332</td>\n",
              "      <td>389</td>\n",
              "      <td>463</td>\n",
              "      <td>521</td>\n",
              "      <td>593</td>\n",
              "      <td>661</td>\n",
              "      <td>711</td>\n",
              "      <td>772</td>\n",
              "      <td>803</td>\n",
              "      <td>838</td>\n",
              "      <td>879</td>\n",
              "      <td>912</td>\n",
              "      <td>946</td>\n",
              "      <td>968</td>\n",
              "      <td>988</td>\n",
              "      <td>1001</td>\n",
              "      <td>1004</td>\n",
              "      <td>1006</td>\n",
              "      <td>1007</td>\n",
              "      <td>1008</td>\n",
              "      <td>1010</td>\n",
              "      <td>1011</td>\n",
              "      <td>1013</td>\n",
              "      <td>1016</td>\n",
              "      <td>1016</td>\n",
              "      <td>1016</td>\n",
              "      <td>1016</td>\n",
              "      <td>1017</td>\n",
              "      <td>1017</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>1018</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Inner Mongolia</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>44.09350</td>\n",
              "      <td>113.9448</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>16</td>\n",
              "      <td>19</td>\n",
              "      <td>20</td>\n",
              "      <td>23</td>\n",
              "      <td>27</td>\n",
              "      <td>34</td>\n",
              "      <td>35</td>\n",
              "      <td>42</td>\n",
              "      <td>46</td>\n",
              "      <td>50</td>\n",
              "      <td>52</td>\n",
              "      <td>54</td>\n",
              "      <td>58</td>\n",
              "      <td>58</td>\n",
              "      <td>60</td>\n",
              "      <td>61</td>\n",
              "      <td>65</td>\n",
              "      <td>68</td>\n",
              "      <td>70</td>\n",
              "      <td>72</td>\n",
              "      <td>73</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>75</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Jiangsu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>32.97110</td>\n",
              "      <td>119.4550</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>9</td>\n",
              "      <td>18</td>\n",
              "      <td>33</td>\n",
              "      <td>47</td>\n",
              "      <td>70</td>\n",
              "      <td>99</td>\n",
              "      <td>129</td>\n",
              "      <td>168</td>\n",
              "      <td>202</td>\n",
              "      <td>236</td>\n",
              "      <td>271</td>\n",
              "      <td>308</td>\n",
              "      <td>341</td>\n",
              "      <td>373</td>\n",
              "      <td>408</td>\n",
              "      <td>439</td>\n",
              "      <td>468</td>\n",
              "      <td>492</td>\n",
              "      <td>515</td>\n",
              "      <td>543</td>\n",
              "      <td>570</td>\n",
              "      <td>593</td>\n",
              "      <td>604</td>\n",
              "      <td>617</td>\n",
              "      <td>626</td>\n",
              "      <td>629</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>631</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Jiangxi</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>27.61400</td>\n",
              "      <td>115.7221</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>36</td>\n",
              "      <td>72</td>\n",
              "      <td>109</td>\n",
              "      <td>109</td>\n",
              "      <td>162</td>\n",
              "      <td>240</td>\n",
              "      <td>286</td>\n",
              "      <td>333</td>\n",
              "      <td>391</td>\n",
              "      <td>476</td>\n",
              "      <td>548</td>\n",
              "      <td>600</td>\n",
              "      <td>661</td>\n",
              "      <td>698</td>\n",
              "      <td>740</td>\n",
              "      <td>771</td>\n",
              "      <td>804</td>\n",
              "      <td>844</td>\n",
              "      <td>872</td>\n",
              "      <td>900</td>\n",
              "      <td>913</td>\n",
              "      <td>925</td>\n",
              "      <td>930</td>\n",
              "      <td>933</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>934</td>\n",
              "      <td>935</td>\n",
              "      <td>935</td>\n",
              "      <td>935</td>\n",
              "      <td>935</td>\n",
              "      <td>935</td>\n",
              "      <td>935</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Jilin</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>43.66610</td>\n",
              "      <td>126.1923</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>14</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>23</td>\n",
              "      <td>31</td>\n",
              "      <td>42</td>\n",
              "      <td>54</td>\n",
              "      <td>59</td>\n",
              "      <td>65</td>\n",
              "      <td>69</td>\n",
              "      <td>78</td>\n",
              "      <td>80</td>\n",
              "      <td>81</td>\n",
              "      <td>83</td>\n",
              "      <td>84</td>\n",
              "      <td>86</td>\n",
              "      <td>88</td>\n",
              "      <td>89</td>\n",
              "      <td>89</td>\n",
              "      <td>89</td>\n",
              "      <td>90</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Liaoning</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>41.29560</td>\n",
              "      <td>122.6085</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>17</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>34</td>\n",
              "      <td>39</td>\n",
              "      <td>41</td>\n",
              "      <td>48</td>\n",
              "      <td>64</td>\n",
              "      <td>70</td>\n",
              "      <td>74</td>\n",
              "      <td>81</td>\n",
              "      <td>89</td>\n",
              "      <td>94</td>\n",
              "      <td>99</td>\n",
              "      <td>105</td>\n",
              "      <td>107</td>\n",
              "      <td>108</td>\n",
              "      <td>111</td>\n",
              "      <td>116</td>\n",
              "      <td>117</td>\n",
              "      <td>119</td>\n",
              "      <td>119</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>121</td>\n",
              "      <td>122</td>\n",
              "      <td>122</td>\n",
              "      <td>125</td>\n",
              "      <td>125</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Ningxia</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>37.26920</td>\n",
              "      <td>106.1655</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>12</td>\n",
              "      <td>17</td>\n",
              "      <td>21</td>\n",
              "      <td>26</td>\n",
              "      <td>28</td>\n",
              "      <td>31</td>\n",
              "      <td>34</td>\n",
              "      <td>34</td>\n",
              "      <td>40</td>\n",
              "      <td>43</td>\n",
              "      <td>45</td>\n",
              "      <td>45</td>\n",
              "      <td>49</td>\n",
              "      <td>53</td>\n",
              "      <td>58</td>\n",
              "      <td>64</td>\n",
              "      <td>67</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>71</td>\n",
              "      <td>72</td>\n",
              "      <td>72</td>\n",
              "      <td>73</td>\n",
              "      <td>73</td>\n",
              "      <td>74</td>\n",
              "      <td>74</td>\n",
              "      <td>75</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Qinghai</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>35.74520</td>\n",
              "      <td>95.9956</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>11</td>\n",
              "      <td>13</td>\n",
              "      <td>15</td>\n",
              "      <td>17</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Shaanxi</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>35.19170</td>\n",
              "      <td>108.8701</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>22</td>\n",
              "      <td>35</td>\n",
              "      <td>46</td>\n",
              "      <td>56</td>\n",
              "      <td>63</td>\n",
              "      <td>87</td>\n",
              "      <td>101</td>\n",
              "      <td>116</td>\n",
              "      <td>128</td>\n",
              "      <td>142</td>\n",
              "      <td>165</td>\n",
              "      <td>173</td>\n",
              "      <td>184</td>\n",
              "      <td>195</td>\n",
              "      <td>208</td>\n",
              "      <td>213</td>\n",
              "      <td>219</td>\n",
              "      <td>225</td>\n",
              "      <td>229</td>\n",
              "      <td>230</td>\n",
              "      <td>232</td>\n",
              "      <td>236</td>\n",
              "      <td>240</td>\n",
              "      <td>240</td>\n",
              "      <td>242</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>245</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Shandong</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.34270</td>\n",
              "      <td>118.1498</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>15</td>\n",
              "      <td>27</td>\n",
              "      <td>46</td>\n",
              "      <td>75</td>\n",
              "      <td>95</td>\n",
              "      <td>130</td>\n",
              "      <td>158</td>\n",
              "      <td>184</td>\n",
              "      <td>206</td>\n",
              "      <td>230</td>\n",
              "      <td>259</td>\n",
              "      <td>275</td>\n",
              "      <td>307</td>\n",
              "      <td>347</td>\n",
              "      <td>386</td>\n",
              "      <td>416</td>\n",
              "      <td>444</td>\n",
              "      <td>466</td>\n",
              "      <td>487</td>\n",
              "      <td>497</td>\n",
              "      <td>509</td>\n",
              "      <td>523</td>\n",
              "      <td>532</td>\n",
              "      <td>537</td>\n",
              "      <td>541</td>\n",
              "      <td>543</td>\n",
              "      <td>544</td>\n",
              "      <td>546</td>\n",
              "      <td>749</td>\n",
              "      <td>750</td>\n",
              "      <td>754</td>\n",
              "      <td>755</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>756</td>\n",
              "      <td>758</td>\n",
              "      <td>758</td>\n",
              "      <td>758</td>\n",
              "      <td>758</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Shanghai</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.20200</td>\n",
              "      <td>121.4491</td>\n",
              "      <td>9</td>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>33</td>\n",
              "      <td>40</td>\n",
              "      <td>53</td>\n",
              "      <td>66</td>\n",
              "      <td>96</td>\n",
              "      <td>112</td>\n",
              "      <td>135</td>\n",
              "      <td>169</td>\n",
              "      <td>182</td>\n",
              "      <td>203</td>\n",
              "      <td>219</td>\n",
              "      <td>243</td>\n",
              "      <td>257</td>\n",
              "      <td>277</td>\n",
              "      <td>286</td>\n",
              "      <td>293</td>\n",
              "      <td>299</td>\n",
              "      <td>303</td>\n",
              "      <td>311</td>\n",
              "      <td>315</td>\n",
              "      <td>318</td>\n",
              "      <td>326</td>\n",
              "      <td>328</td>\n",
              "      <td>333</td>\n",
              "      <td>333</td>\n",
              "      <td>333</td>\n",
              "      <td>334</td>\n",
              "      <td>334</td>\n",
              "      <td>335</td>\n",
              "      <td>335</td>\n",
              "      <td>335</td>\n",
              "      <td>336</td>\n",
              "      <td>337</td>\n",
              "      <td>337</td>\n",
              "      <td>337</td>\n",
              "      <td>337</td>\n",
              "      <td>337</td>\n",
              "      <td>337</td>\n",
              "      <td>338</td>\n",
              "      <td>338</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Shanxi</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>37.57770</td>\n",
              "      <td>112.2922</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>13</td>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>35</td>\n",
              "      <td>39</td>\n",
              "      <td>47</td>\n",
              "      <td>66</td>\n",
              "      <td>74</td>\n",
              "      <td>81</td>\n",
              "      <td>81</td>\n",
              "      <td>96</td>\n",
              "      <td>104</td>\n",
              "      <td>115</td>\n",
              "      <td>119</td>\n",
              "      <td>119</td>\n",
              "      <td>124</td>\n",
              "      <td>126</td>\n",
              "      <td>126</td>\n",
              "      <td>127</td>\n",
              "      <td>128</td>\n",
              "      <td>129</td>\n",
              "      <td>130</td>\n",
              "      <td>131</td>\n",
              "      <td>131</td>\n",
              "      <td>132</td>\n",
              "      <td>132</td>\n",
              "      <td>132</td>\n",
              "      <td>132</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>133</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Sichuan</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.61710</td>\n",
              "      <td>102.7103</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>15</td>\n",
              "      <td>28</td>\n",
              "      <td>44</td>\n",
              "      <td>69</td>\n",
              "      <td>90</td>\n",
              "      <td>108</td>\n",
              "      <td>142</td>\n",
              "      <td>177</td>\n",
              "      <td>207</td>\n",
              "      <td>231</td>\n",
              "      <td>254</td>\n",
              "      <td>282</td>\n",
              "      <td>301</td>\n",
              "      <td>321</td>\n",
              "      <td>344</td>\n",
              "      <td>364</td>\n",
              "      <td>386</td>\n",
              "      <td>405</td>\n",
              "      <td>417</td>\n",
              "      <td>436</td>\n",
              "      <td>451</td>\n",
              "      <td>463</td>\n",
              "      <td>470</td>\n",
              "      <td>481</td>\n",
              "      <td>495</td>\n",
              "      <td>508</td>\n",
              "      <td>514</td>\n",
              "      <td>520</td>\n",
              "      <td>525</td>\n",
              "      <td>526</td>\n",
              "      <td>526</td>\n",
              "      <td>527</td>\n",
              "      <td>529</td>\n",
              "      <td>531</td>\n",
              "      <td>534</td>\n",
              "      <td>538</td>\n",
              "      <td>538</td>\n",
              "      <td>538</td>\n",
              "      <td>538</td>\n",
              "      <td>538</td>\n",
              "      <td>538</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Tianjin</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>39.30540</td>\n",
              "      <td>117.3230</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>8</td>\n",
              "      <td>10</td>\n",
              "      <td>14</td>\n",
              "      <td>23</td>\n",
              "      <td>24</td>\n",
              "      <td>27</td>\n",
              "      <td>31</td>\n",
              "      <td>32</td>\n",
              "      <td>41</td>\n",
              "      <td>48</td>\n",
              "      <td>60</td>\n",
              "      <td>67</td>\n",
              "      <td>69</td>\n",
              "      <td>79</td>\n",
              "      <td>81</td>\n",
              "      <td>88</td>\n",
              "      <td>91</td>\n",
              "      <td>95</td>\n",
              "      <td>106</td>\n",
              "      <td>112</td>\n",
              "      <td>119</td>\n",
              "      <td>120</td>\n",
              "      <td>122</td>\n",
              "      <td>124</td>\n",
              "      <td>125</td>\n",
              "      <td>128</td>\n",
              "      <td>130</td>\n",
              "      <td>131</td>\n",
              "      <td>132</td>\n",
              "      <td>135</td>\n",
              "      <td>135</td>\n",
              "      <td>135</td>\n",
              "      <td>135</td>\n",
              "      <td>135</td>\n",
              "      <td>136</td>\n",
              "      <td>136</td>\n",
              "      <td>136</td>\n",
              "      <td>136</td>\n",
              "      <td>136</td>\n",
              "      <td>136</td>\n",
              "      <td>136</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Tibet</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.69270</td>\n",
              "      <td>88.0924</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Xinjiang</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>41.11290</td>\n",
              "      <td>85.2401</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>13</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>18</td>\n",
              "      <td>21</td>\n",
              "      <td>24</td>\n",
              "      <td>29</td>\n",
              "      <td>32</td>\n",
              "      <td>36</td>\n",
              "      <td>39</td>\n",
              "      <td>42</td>\n",
              "      <td>45</td>\n",
              "      <td>49</td>\n",
              "      <td>55</td>\n",
              "      <td>59</td>\n",
              "      <td>63</td>\n",
              "      <td>65</td>\n",
              "      <td>70</td>\n",
              "      <td>71</td>\n",
              "      <td>75</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>76</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Yunnan</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>24.97400</td>\n",
              "      <td>101.4870</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>16</td>\n",
              "      <td>26</td>\n",
              "      <td>44</td>\n",
              "      <td>55</td>\n",
              "      <td>70</td>\n",
              "      <td>83</td>\n",
              "      <td>93</td>\n",
              "      <td>105</td>\n",
              "      <td>117</td>\n",
              "      <td>122</td>\n",
              "      <td>128</td>\n",
              "      <td>133</td>\n",
              "      <td>138</td>\n",
              "      <td>138</td>\n",
              "      <td>141</td>\n",
              "      <td>149</td>\n",
              "      <td>153</td>\n",
              "      <td>154</td>\n",
              "      <td>156</td>\n",
              "      <td>162</td>\n",
              "      <td>168</td>\n",
              "      <td>171</td>\n",
              "      <td>171</td>\n",
              "      <td>172</td>\n",
              "      <td>172</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Zhejiang</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>29.18320</td>\n",
              "      <td>120.0934</td>\n",
              "      <td>10</td>\n",
              "      <td>27</td>\n",
              "      <td>43</td>\n",
              "      <td>62</td>\n",
              "      <td>104</td>\n",
              "      <td>128</td>\n",
              "      <td>173</td>\n",
              "      <td>296</td>\n",
              "      <td>428</td>\n",
              "      <td>538</td>\n",
              "      <td>599</td>\n",
              "      <td>661</td>\n",
              "      <td>724</td>\n",
              "      <td>829</td>\n",
              "      <td>895</td>\n",
              "      <td>954</td>\n",
              "      <td>1006</td>\n",
              "      <td>1048</td>\n",
              "      <td>1075</td>\n",
              "      <td>1092</td>\n",
              "      <td>1117</td>\n",
              "      <td>1131</td>\n",
              "      <td>1145</td>\n",
              "      <td>1155</td>\n",
              "      <td>1162</td>\n",
              "      <td>1167</td>\n",
              "      <td>1171</td>\n",
              "      <td>1172</td>\n",
              "      <td>1174</td>\n",
              "      <td>1175</td>\n",
              "      <td>1203</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1205</td>\n",
              "      <td>1206</td>\n",
              "      <td>1213</td>\n",
              "      <td>1213</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Province/State  Country/Region       Lat  ...  3/3/20  3/4/20  is_mainland_china\n",
              "0            Anhui  Mainland China  31.82570  ...     990     990               True\n",
              "1          Beijing  Mainland China  40.18240  ...     414     418               True\n",
              "2        Chongqing  Mainland China  30.05720  ...     576     576               True\n",
              "3           Fujian  Mainland China  26.07890  ...     296     296               True\n",
              "4            Gansu  Mainland China  36.06110  ...      91      91               True\n",
              "5        Guangdong  Mainland China  23.34170  ...    1350    1350               True\n",
              "6          Guangxi  Mainland China  23.82980  ...     252     252               True\n",
              "7          Guizhou  Mainland China  26.81540  ...     146     146               True\n",
              "8           Hainan  Mainland China  19.19590  ...     168     168               True\n",
              "9            Hebei  Mainland China  38.04280  ...     318     318               True\n",
              "10    Heilongjiang  Mainland China  47.86200  ...     480     480               True\n",
              "11           Henan  Mainland China  33.88202  ...    1272    1272               True\n",
              "12           Hubei  Mainland China  30.97560  ...   67217   67332               True\n",
              "13           Hunan  Mainland China  27.61040  ...    1018    1018               True\n",
              "14  Inner Mongolia  Mainland China  44.09350  ...      75      75               True\n",
              "15         Jiangsu  Mainland China  32.97110  ...     631     631               True\n",
              "16         Jiangxi  Mainland China  27.61400  ...     935     935               True\n",
              "17           Jilin  Mainland China  43.66610  ...      93      93               True\n",
              "18        Liaoning  Mainland China  41.29560  ...     125     125               True\n",
              "19         Ningxia  Mainland China  37.26920  ...      74      75               True\n",
              "20         Qinghai  Mainland China  35.74520  ...      18      18               True\n",
              "21         Shaanxi  Mainland China  35.19170  ...     245     245               True\n",
              "22        Shandong  Mainland China  36.34270  ...     758     758               True\n",
              "23        Shanghai  Mainland China  31.20200  ...     338     338               True\n",
              "24          Shanxi  Mainland China  37.57770  ...     133     133               True\n",
              "25         Sichuan  Mainland China  30.61710  ...     538     538               True\n",
              "26         Tianjin  Mainland China  39.30540  ...     136     136               True\n",
              "27           Tibet  Mainland China  31.69270  ...       1       1               True\n",
              "28        Xinjiang  Mainland China  41.11290  ...      76      76               True\n",
              "29          Yunnan  Mainland China  24.97400  ...     174     174               True\n",
              "30        Zhejiang  Mainland China  29.18320  ...    1213    1213               True\n",
              "\n",
              "[31 rows x 48 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iXgiEtYV_4w-",
        "outputId": "4b538d82-4e2c-49b4-acc9-0c5eed274885",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        }
      },
      "source": [
        "confirmed.groupby(\"is_mainland_china\").sum()[last_date].plot(kind='pie')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1559db4e0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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MmFuvcVX3TYVjGtMfb2kHaK/akP5COixj5b1/EtgbuCWpUN2wwpusSdUZvlrhG+jkQpn3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\n/wFkxlcO7UNMowAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xnOVJvXIAEBh",
        "outputId": "7b64250c-ffaf-4578-d2b8-05e7f39d3fce",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 314
        }
      },
      "source": [
        "confirmed.groupby(\"is_mainland_china\").sum()[last_date].plot(kind='bar')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1559f07f0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rxvzjGCCAs4j"
      },
      "source": [
        "## No dia 02/03/2020 mainland china tinha 8 vezes o número de casos que o resto. Mas isso é até injusto pois estamos resumindo as informações e com isso, perdendo elas.\n",
        "\n",
        "Mas olhar uma fotografia é muito limitado, queremos ver também como anda esse crescimento."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gjsAw3wLAtYQ",
        "outputId": "b43469ab-4f74-4b1e-aa5d-b0119da84107",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        }
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "confirmed['is_mainland_china_label'] = np.where(confirmed[\"is_mainland_china\"], 'Mainland China', 'Others')\n",
        "display(confirmed.head())\n",
        "display(confirmed.tail())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Province/State</th>\n",
              "      <th>Country/Region</th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
              "      <th>1/23/20</th>\n",
              "      <th>1/24/20</th>\n",
              "      <th>1/25/20</th>\n",
              "      <th>1/26/20</th>\n",
              "      <th>1/27/20</th>\n",
              "      <th>1/28/20</th>\n",
              "      <th>1/29/20</th>\n",
              "      <th>1/30/20</th>\n",
              "      <th>1/31/20</th>\n",
              "      <th>2/1/20</th>\n",
              "      <th>2/2/20</th>\n",
              "      <th>2/3/20</th>\n",
              "      <th>2/4/20</th>\n",
              "      <th>2/5/20</th>\n",
              "      <th>2/6/20</th>\n",
              "      <th>2/7/20</th>\n",
              "      <th>2/8/20</th>\n",
              "      <th>2/9/20</th>\n",
              "      <th>2/10/20</th>\n",
              "      <th>2/11/20</th>\n",
              "      <th>2/12/20</th>\n",
              "      <th>2/13/20</th>\n",
              "      <th>2/14/20</th>\n",
              "      <th>2/15/20</th>\n",
              "      <th>2/16/20</th>\n",
              "      <th>2/17/20</th>\n",
              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
              "      <th>2/21/20</th>\n",
              "      <th>2/22/20</th>\n",
              "      <th>2/23/20</th>\n",
              "      <th>2/24/20</th>\n",
              "      <th>2/25/20</th>\n",
              "      <th>2/26/20</th>\n",
              "      <th>2/27/20</th>\n",
              "      <th>2/28/20</th>\n",
              "      <th>2/29/20</th>\n",
              "      <th>3/1/20</th>\n",
              "      <th>3/2/20</th>\n",
              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
              "      <th>is_mainland_china</th>\n",
              "      <th>is_mainland_china_label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Anhui</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>31.8257</td>\n",
              "      <td>117.2264</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>39</td>\n",
              "      <td>60</td>\n",
              "      <td>70</td>\n",
              "      <td>106</td>\n",
              "      <td>152</td>\n",
              "      <td>200</td>\n",
              "      <td>237</td>\n",
              "      <td>297</td>\n",
              "      <td>340</td>\n",
              "      <td>408</td>\n",
              "      <td>480</td>\n",
              "      <td>530</td>\n",
              "      <td>591</td>\n",
              "      <td>665</td>\n",
              "      <td>733</td>\n",
              "      <td>779</td>\n",
              "      <td>830</td>\n",
              "      <td>860</td>\n",
              "      <td>889</td>\n",
              "      <td>910</td>\n",
              "      <td>934</td>\n",
              "      <td>950</td>\n",
              "      <td>962</td>\n",
              "      <td>973</td>\n",
              "      <td>982</td>\n",
              "      <td>986</td>\n",
              "      <td>987</td>\n",
              "      <td>988</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>989</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>990</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Beijing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>40.1824</td>\n",
              "      <td>116.4142</td>\n",
              "      <td>14</td>\n",
              "      <td>22</td>\n",
              "      <td>36</td>\n",
              "      <td>41</td>\n",
              "      <td>68</td>\n",
              "      <td>80</td>\n",
              "      <td>91</td>\n",
              "      <td>111</td>\n",
              "      <td>114</td>\n",
              "      <td>139</td>\n",
              "      <td>168</td>\n",
              "      <td>191</td>\n",
              "      <td>212</td>\n",
              "      <td>228</td>\n",
              "      <td>253</td>\n",
              "      <td>274</td>\n",
              "      <td>297</td>\n",
              "      <td>315</td>\n",
              "      <td>326</td>\n",
              "      <td>337</td>\n",
              "      <td>342</td>\n",
              "      <td>352</td>\n",
              "      <td>366</td>\n",
              "      <td>372</td>\n",
              "      <td>375</td>\n",
              "      <td>380</td>\n",
              "      <td>381</td>\n",
              "      <td>387</td>\n",
              "      <td>393</td>\n",
              "      <td>395</td>\n",
              "      <td>396</td>\n",
              "      <td>399</td>\n",
              "      <td>399</td>\n",
              "      <td>399</td>\n",
              "      <td>400</td>\n",
              "      <td>400</td>\n",
              "      <td>410</td>\n",
              "      <td>410</td>\n",
              "      <td>411</td>\n",
              "      <td>413</td>\n",
              "      <td>414</td>\n",
              "      <td>414</td>\n",
              "      <td>418</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Chongqing</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.0572</td>\n",
              "      <td>107.8740</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>27</td>\n",
              "      <td>57</td>\n",
              "      <td>75</td>\n",
              "      <td>110</td>\n",
              "      <td>132</td>\n",
              "      <td>147</td>\n",
              "      <td>182</td>\n",
              "      <td>211</td>\n",
              "      <td>247</td>\n",
              "      <td>300</td>\n",
              "      <td>337</td>\n",
              "      <td>366</td>\n",
              "      <td>389</td>\n",
              "      <td>411</td>\n",
              "      <td>426</td>\n",
              "      <td>428</td>\n",
              "      <td>468</td>\n",
              "      <td>486</td>\n",
              "      <td>505</td>\n",
              "      <td>518</td>\n",
              "      <td>529</td>\n",
              "      <td>537</td>\n",
              "      <td>544</td>\n",
              "      <td>551</td>\n",
              "      <td>553</td>\n",
              "      <td>555</td>\n",
              "      <td>560</td>\n",
              "      <td>567</td>\n",
              "      <td>572</td>\n",
              "      <td>573</td>\n",
              "      <td>575</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>576</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fujian</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>26.0789</td>\n",
              "      <td>117.9874</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>18</td>\n",
              "      <td>35</td>\n",
              "      <td>59</td>\n",
              "      <td>80</td>\n",
              "      <td>84</td>\n",
              "      <td>101</td>\n",
              "      <td>120</td>\n",
              "      <td>144</td>\n",
              "      <td>159</td>\n",
              "      <td>179</td>\n",
              "      <td>194</td>\n",
              "      <td>205</td>\n",
              "      <td>215</td>\n",
              "      <td>224</td>\n",
              "      <td>239</td>\n",
              "      <td>250</td>\n",
              "      <td>261</td>\n",
              "      <td>267</td>\n",
              "      <td>272</td>\n",
              "      <td>279</td>\n",
              "      <td>281</td>\n",
              "      <td>285</td>\n",
              "      <td>287</td>\n",
              "      <td>290</td>\n",
              "      <td>292</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>293</td>\n",
              "      <td>294</td>\n",
              "      <td>294</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>296</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gansu</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>36.0611</td>\n",
              "      <td>103.8343</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>40</td>\n",
              "      <td>51</td>\n",
              "      <td>55</td>\n",
              "      <td>57</td>\n",
              "      <td>62</td>\n",
              "      <td>62</td>\n",
              "      <td>67</td>\n",
              "      <td>79</td>\n",
              "      <td>83</td>\n",
              "      <td>83</td>\n",
              "      <td>86</td>\n",
              "      <td>87</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>90</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>91</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Province/State  Country/Region  ...  is_mainland_china  is_mainland_china_label\n",
              "0          Anhui  Mainland China  ...               True           Mainland China\n",
              "1        Beijing  Mainland China  ...               True           Mainland China\n",
              "2      Chongqing  Mainland China  ...               True           Mainland China\n",
              "3         Fujian  Mainland China  ...               True           Mainland China\n",
              "4          Gansu  Mainland China  ...               True           Mainland China\n",
              "\n",
              "[5 rows x 49 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
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              "    <tr>\n",
              "      <th>156</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Liechtenstein</td>\n",
              "      <td>47.1400</td>\n",
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              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Poland</td>\n",
              "      <td>51.9194</td>\n",
              "      <td>19.1451</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "      <td>Others</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Tunisia</td>\n",
              "      <td>34.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "      <td>Others</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>Contra Costa County, CA</td>\n",
              "      <td>US</td>\n",
              "      <td>37.8534</td>\n",
              "      <td>-121.9018</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "      <td>Others</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Province/State  ... is_mainland_china_label\n",
              "155                      NaN  ...                  Others\n",
              "156                      NaN  ...                  Others\n",
              "157                      NaN  ...                  Others\n",
              "158                      NaN  ...                  Others\n",
              "159  Contra Costa County, CA  ...                  Others\n",
              "\n",
              "[5 rows x 49 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UgLR3MEJA_2F",
        "outputId": "5659f429-9175-4464-e660-4883224480e8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        }
      },
      "source": [
        "confirmed.groupby(\"is_mainland_china_label\").sum()[last_date].plot(kind='bar')\n",
        "plt.title(f\"Casos confirmados acumulados até {last_date}\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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QgiRtA3wUGEFp7TAizqgqJ7NOku6OiP2rzqPVeJ9Ba7qG4uZBLwPPlh5mfcE8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\nigmoZq0AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "onER9FnMBnhR",
        "outputId": "eb02783d-3454-45f9-f6db-91169b3d7de8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        }
      },
      "source": [
        "summed = confirmed.groupby(\"is_mainland_china_label\").sum()\n",
        "summed[\"delta\"] = summed[\"3/2/20\"] - summed[\"3/1/20\"]\n",
        "summed[\"delta\"].plot(kind='bar')\n",
        "plt.title(f\"Novos casos confirmados em {last_date}\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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eBGxUczlmNgy4T7+DSTok37DiXtKdsxYCP621KDOrlUO/s30B2Ae4KyK2B/YD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\nmRXk/wChxvWEvVK2cwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jS0hssBzCroj",
        "outputId": "9be0d3d2-d7d4-46e0-80d9-61b6f45b33e8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "summed.T.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>is_mainland_china_label</th>\n",
              "      <th>Mainland China</th>\n",
              "      <th>Others</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Lat</th>\n",
              "      <td>1035.61502</td>\n",
              "      <td>4003.2272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Long</th>\n",
              "      <td>3457.83000</td>\n",
              "      <td>91.7267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/22/20</th>\n",
              "      <td>547.00000</td>\n",
              "      <td>8.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/23/20</th>\n",
              "      <td>639.00000</td>\n",
              "      <td>14.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/24/20</th>\n",
              "      <td>916.00000</td>\n",
              "      <td>25.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "is_mainland_china_label  Mainland China     Others\n",
              "Lat                          1035.61502  4003.2272\n",
              "Long                         3457.83000    91.7267\n",
              "1/22/20                       547.00000     8.0000\n",
              "1/23/20                       639.00000    14.0000\n",
              "1/24/20                       916.00000    25.0000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vpA90-ObCOzu",
        "outputId": "dce33ed8-42c8-4708-d870-9fe804c8bd89",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "summed.T[2:-2].plot()\n",
        "plt.title(\"Desenvolvimento de casos confirmados com o passar do tempo\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lmcv7cNkp0faoGRNQld7TEZHuIrLM55UuIneKSHMRmS8iG917M5dfRORFEYkX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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wdgsGsoaBHyI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        },
        "outputId": "d214836e-820c-4543-975f-113b7d50c823"
      },
      "source": [
        "differences.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>is_mainland_china_label</th>\n",
              "      <th>Mainland China</th>\n",
              "      <th>Others</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1/23/20</th>\n",
              "      <td>92.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/24/20</th>\n",
              "      <td>277.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/25/20</th>\n",
              "      <td>483.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/26/20</th>\n",
              "      <td>663.0</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/27/20</th>\n",
              "      <td>801.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "is_mainland_china_label  Mainland China  Others\n",
              "1/23/20                            92.0     6.0\n",
              "1/24/20                           277.0    11.0\n",
              "1/25/20                           483.0    10.0\n",
              "1/26/20                           663.0    21.0\n",
              "1/27/20                           801.0     8.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j_luHVqKDAMw",
        "outputId": "8968480f-26b8-4839-9c25-6e24652e0b54",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        }
      },
      "source": [
        "import datetime\n",
        "import matplotlib.dates as mdates\n",
        "\n",
        "differences = summed.T[2:-2].diff().dropna()\n",
        "ax = differences.plot(figsize=(10,5),\n",
        "                      title=\"Casos novos com o decorrer do tempo\",\n",
        "                      grid=True)\n",
        "plt.legend([\"Mainland China\", \"Outros\"])\n",
        "ax.set_ylabel(\"# casos\")\n",
        "ax.set_xlabel(\"O pico ocorreu devido a mudança de abordagem em Hubei onde, por segurança, passou-se a considerar confirmado mesmos casos sem diagnóstico de laboratório.\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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CSpggIiKtpEBIRESSrmLPiFATU+NycwCNCImISOspEBIRkaSLTo3Ly2l8alxe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\nDsf/BzLSyjAAAAAESURBVP8Qn5VevLOYAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oTXyOUW8Dpoz",
        "outputId": "02ad7a0d-1f09-4be1-8345-9d7940166fa5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "cases = confirmed.groupby(\"is_mainland_china_label\").sum()[last_date].loc[\"Mainland China\"]\n",
        "estimated_population =  1437525528\n",
        "incidence_ratio = cases / estimated_population * 100000\n",
        "incidence_ratio\n",
        "\n",
        "# conta péssima, e ruim. e errada. pois estou usando uma populacao MUITO maior do que\n",
        "# deveria estar usando"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5.566927226074276"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mwPcOe-WJHzf",
        "outputId": "bdcc5dbb-55da-40b4-f242-73a253ee9b67",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "un_population = pd.read_csv(\"https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_TotalPopulationBySex.csv\")\n",
        "un_population[\"PopTotal\"] = un_population[\"PopTotal\"] * 1000\n",
        "un_population.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>LocID</th>\n",
              "      <th>Location</th>\n",
              "      <th>VarID</th>\n",
              "      <th>Variant</th>\n",
              "      <th>Time</th>\n",
              "      <th>MidPeriod</th>\n",
              "      <th>PopMale</th>\n",
              "      <th>PopFemale</th>\n",
              "      <th>PopTotal</th>\n",
              "      <th>PopDensity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>4</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2</td>\n",
              "      <td>Medium</td>\n",
              "      <td>1950</td>\n",
              "      <td>1950.5</td>\n",
              "      <td>4099.243</td>\n",
              "      <td>3652.874</td>\n",
              "      <td>7752117.0</td>\n",
              "      <td>11.874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2</td>\n",
              "      <td>Medium</td>\n",
              "      <td>1951</td>\n",
              "      <td>1951.5</td>\n",
              "      <td>4134.756</td>\n",
              "      <td>3705.395</td>\n",
              "      <td>7840151.0</td>\n",
              "      <td>12.009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2</td>\n",
              "      <td>Medium</td>\n",
              "      <td>1952</td>\n",
              "      <td>1952.5</td>\n",
              "      <td>4174.450</td>\n",
              "      <td>3761.546</td>\n",
              "      <td>7935996.0</td>\n",
              "      <td>12.156</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2</td>\n",
              "      <td>Medium</td>\n",
              "      <td>1953</td>\n",
              "      <td>1953.5</td>\n",
              "      <td>4218.336</td>\n",
              "      <td>3821.348</td>\n",
              "      <td>8039684.0</td>\n",
              "      <td>12.315</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>2</td>\n",
              "      <td>Medium</td>\n",
              "      <td>1954</td>\n",
              "      <td>1954.5</td>\n",
              "      <td>4266.484</td>\n",
              "      <td>3884.832</td>\n",
              "      <td>8151316.0</td>\n",
              "      <td>12.486</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   LocID     Location  VarID  ... PopFemale   PopTotal  PopDensity\n",
              "0      4  Afghanistan      2  ...  3652.874  7752117.0      11.874\n",
              "1      4  Afghanistan      2  ...  3705.395  7840151.0      12.009\n",
              "2      4  Afghanistan      2  ...  3761.546  7935996.0      12.156\n",
              "3      4  Afghanistan      2  ...  3821.348  8039684.0      12.315\n",
              "4      4  Afghanistan      2  ...  3884.832  8151316.0      12.486\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nN9jWNIWJ7_g",
        "outputId": "f8ca0978-dcbd-4b58-a693-12363ca0cdaa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        }
      },
      "source": [
        "un_population.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>LocID</th>\n",
              "      <th>VarID</th>\n",
              "      <th>Time</th>\n",
              "      <th>MidPeriod</th>\n",
              "      <th>PopMale</th>\n",
              "      <th>PopFemale</th>\n",
              "      <th>PopTotal</th>\n",
              "      <th>PopDensity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>280932.000000</td>\n",
              "      <td>280932.000000</td>\n",
              "      <td>280932.000000</td>\n",
              "      <td>280932.000000</td>\n",
              "      <td>2.508760e+05</td>\n",
              "      <td>2.508760e+05</td>\n",
              "      <td>2.809320e+05</td>\n",
              "      <td>280932.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>703.125062</td>\n",
              "      <td>22.411345</td>\n",
              "      <td>2051.026494</td>\n",
              "      <td>2051.526494</td>\n",
              "      <td>2.324362e+05</td>\n",
              "      <td>2.298754e+05</td>\n",
              "      <td>4.128536e+08</td>\n",
              "      <td>426.659040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>631.959759</td>\n",
              "      <td>55.972847</td>\n",
              "      <td>33.642148</td>\n",
              "      <td>33.642148</td>\n",
              "      <td>6.938837e+05</td>\n",
              "      <td>6.829825e+05</td>\n",
              "      <td>1.308911e+09</td>\n",
              "      <td>2418.990784</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1950.000000</td>\n",
              "      <td>1950.500000</td>\n",
              "      <td>6.812000e+00</td>\n",
              "      <td>6.889000e+00</td>\n",
              "      <td>1.510000e+02</td>\n",
              "      <td>0.052000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>300.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2031.000000</td>\n",
              "      <td>2031.500000</td>\n",
              "      <td>1.847834e+03</td>\n",
              "      <td>1.860604e+03</td>\n",
              "      <td>1.240100e+06</td>\n",
              "      <td>34.205250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>586.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>2055.000000</td>\n",
              "      <td>2055.500000</td>\n",
              "      <td>1.136849e+04</td>\n",
              "      <td>1.164585e+04</td>\n",
              "      <td>1.420555e+07</td>\n",
              "      <td>91.590000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>903.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>2078.000000</td>\n",
              "      <td>2078.500000</td>\n",
              "      <td>8.526402e+04</td>\n",
              "      <td>8.648854e+04</td>\n",
              "      <td>1.171661e+08</td>\n",
              "      <td>216.985750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>5501.000000</td>\n",
              "      <td>207.000000</td>\n",
              "      <td>2100.000000</td>\n",
              "      <td>2100.500000</td>\n",
              "      <td>1.092000e+07</td>\n",
              "      <td>1.071273e+07</td>\n",
              "      <td>2.163274e+10</td>\n",
              "      <td>56025.839000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               LocID          VarID  ...      PopTotal     PopDensity\n",
              "count  280932.000000  280932.000000  ...  2.809320e+05  280932.000000\n",
              "mean      703.125062      22.411345  ...  4.128536e+08     426.659040\n",
              "std       631.959759      55.972847  ...  1.308911e+09    2418.990784\n",
              "min         4.000000       2.000000  ...  1.510000e+02       0.052000\n",
              "25%       300.000000       2.000000  ...  1.240100e+06      34.205250\n",
              "50%       586.000000       5.000000  ...  1.420555e+07      91.590000\n",
              "75%       903.000000       9.000000  ...  1.171661e+08     216.985750\n",
              "max      5501.000000     207.000000  ...  2.163274e+10   56025.839000\n",
              "\n",
              "[8 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Oy1ivO7ZbPeP",
        "outputId": "459b0dd5-5d5d-4add-94b1-26ae238b599d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        }
      },
      "source": [
        "un_population_total = un_population.query(\"Time==2019\")[[\"Location\",\"PopTotal\"]].set_index(\"Location\")\n",
        "un_population_total.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PopTotal</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Location</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>3.804176e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Africa</th>\n",
              "      <td>1.308064e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>African Group</th>\n",
              "      <td>1.306321e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>African Union</th>\n",
              "      <td>1.306903e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>African Union: Central Africa</th>\n",
              "      <td>1.540137e+08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                   PopTotal\n",
              "Location                                   \n",
              "Afghanistan                    3.804176e+07\n",
              "Africa                         1.308064e+09\n",
              "African Group                  1.306321e+09\n",
              "African Union                  1.306903e+09\n",
              "African Union: Central Africa  1.540137e+08"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D_MSNBKtbcNS",
        "outputId": "ca0b1750-8936-4b24-9a65-b7e9aa6bb556",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        }
      },
      "source": [
        "combined.join(un_population_total)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "      <th>PopTotal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>38041757.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>43053054.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andorra</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>77146.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>44780675.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Armenia</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2957728.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>UK</th>\n",
              "      <td>85</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>US</th>\n",
              "      <td>153</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>7.189542</td>\n",
              "      <td>57.894737</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ukraine</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>43993643.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>United Arab Emirates</th>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9770526.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Vietnam</th>\n",
              "      <td>16</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>86 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      confirmed  deaths  ...  letality_rate_2    PopTotal\n",
              "Afghanistan                   1       0  ...              NaN  38041757.0\n",
              "Algeria                      12       0  ...              NaN  43053054.0\n",
              "Andorra                       1       0  ...              NaN     77146.0\n",
              "Argentina                     1       0  ...              NaN  44780675.0\n",
              "Armenia                       1       0  ...              NaN   2957728.0\n",
              "...                         ...     ...  ...              ...         ...\n",
              "UK                           85       0  ...         0.000000         NaN\n",
              "US                          153      11  ...        57.894737         NaN\n",
              "Ukraine                       1       0  ...              NaN  43993643.0\n",
              "United Arab Emirates         27       0  ...         0.000000   9770526.0\n",
              "Vietnam                      16       0  ...         0.000000         NaN\n",
              "\n",
              "[86 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zoviyknCcAKV",
        "outputId": "3f902bb3-3f42-428c-ee49-67bbefc9f3c6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 648
        }
      },
      "source": [
        "combined.join(un_population_total).sort_values(\"confirmed\", ascending=False).head(20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "      <th>PopTotal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>80271</td>\n",
              "      <td>2981</td>\n",
              "      <td>49955</td>\n",
              "      <td>3.713670</td>\n",
              "      <td>5.631328</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>South Korea</th>\n",
              "      <td>5621</td>\n",
              "      <td>35</td>\n",
              "      <td>41</td>\n",
              "      <td>0.622665</td>\n",
              "      <td>46.052632</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>3089</td>\n",
              "      <td>107</td>\n",
              "      <td>276</td>\n",
              "      <td>3.463904</td>\n",
              "      <td>27.937337</td>\n",
              "      <td>60550092.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iran</th>\n",
              "      <td>2922</td>\n",
              "      <td>92</td>\n",
              "      <td>552</td>\n",
              "      <td>3.148528</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Others</th>\n",
              "      <td>706</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>0.849858</td>\n",
              "      <td>37.500000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>331</td>\n",
              "      <td>6</td>\n",
              "      <td>43</td>\n",
              "      <td>1.812689</td>\n",
              "      <td>12.244898</td>\n",
              "      <td>126860299.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>France</th>\n",
              "      <td>285</td>\n",
              "      <td>4</td>\n",
              "      <td>12</td>\n",
              "      <td>1.403509</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>65129731.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Germany</th>\n",
              "      <td>262</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>83517046.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spain</th>\n",
              "      <td>222</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.900901</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>46736782.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>US</th>\n",
              "      <td>153</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>7.189542</td>\n",
              "      <td>57.894737</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Singapore</th>\n",
              "      <td>110</td>\n",
              "      <td>0</td>\n",
              "      <td>78</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5804343.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hong Kong</th>\n",
              "      <td>105</td>\n",
              "      <td>2</td>\n",
              "      <td>37</td>\n",
              "      <td>1.904762</td>\n",
              "      <td>5.128205</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Switzerland</th>\n",
              "      <td>90</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>8591361.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>UK</th>\n",
              "      <td>85</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Kuwait</th>\n",
              "      <td>56</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4207077.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Norway</th>\n",
              "      <td>56</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5378859.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>52</td>\n",
              "      <td>2</td>\n",
              "      <td>11</td>\n",
              "      <td>3.846154</td>\n",
              "      <td>15.384615</td>\n",
              "      <td>25203200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahrain</th>\n",
              "      <td>52</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1641164.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Malaysia</th>\n",
              "      <td>50</td>\n",
              "      <td>0</td>\n",
              "      <td>22</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>31949789.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Thailand</th>\n",
              "      <td>43</td>\n",
              "      <td>1</td>\n",
              "      <td>31</td>\n",
              "      <td>2.325581</td>\n",
              "      <td>3.125000</td>\n",
              "      <td>69625581.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  ...  letality_rate_2     PopTotal\n",
              "Mainland China      80271    2981  ...         5.631328          NaN\n",
              "South Korea          5621      35  ...        46.052632          NaN\n",
              "Italy                3089     107  ...        27.937337   60550092.0\n",
              "Iran                 2922      92  ...        14.285714          NaN\n",
              "Others                706       6  ...        37.500000          NaN\n",
              "Japan                 331       6  ...        12.244898  126860299.0\n",
              "France                285       4  ...        25.000000   65129731.0\n",
              "Germany               262       0  ...         0.000000   83517046.0\n",
              "Spain                 222       2  ...        50.000000   46736782.0\n",
              "US                    153      11  ...        57.894737          NaN\n",
              "Singapore             110       0  ...         0.000000    5804343.0\n",
              "Hong Kong             105       2  ...         5.128205          NaN\n",
              "Switzerland            90       0  ...         0.000000    8591361.0\n",
              "UK                     85       0  ...         0.000000          NaN\n",
              "Kuwait                 56       0  ...              NaN    4207077.0\n",
              "Norway                 56       0  ...              NaN    5378859.0\n",
              "Australia              52       2  ...        15.384615   25203200.0\n",
              "Bahrain                52       0  ...              NaN    1641164.0\n",
              "Malaysia               50       0  ...         0.000000   31949789.0\n",
              "Thailand               43       1  ...         3.125000   69625581.0\n",
              "\n",
              "[20 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZG9iEAcbcdqX",
        "outputId": "79868064-1805-4b82-a90d-836b40f78daf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        }
      },
      "source": [
        "un_population_total.index[:5]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Afghanistan', 'Africa', 'African Group', 'African Union',\n",
              "       'African Union: Central Africa'],\n",
              "      dtype='object', name='Location')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C0eCM6sRczGc",
        "outputId": "6c0e11e7-4e84-4b4d-bf58-1994f77771bc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        }
      },
      "source": [
        "def locate(population, country):\n",
        "  return population.query(f\"Location.str.contains('{country}') and Time==2019\", engine='python')\n",
        "\n",
        "locate(un_population, 'Hong K')\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>LocID</th>\n",
              "      <th>Location</th>\n",
              "      <th>VarID</th>\n",
              "      <th>Variant</th>\n",
              "      <th>Time</th>\n",
              "      <th>MidPeriod</th>\n",
              "      <th>PopMale</th>\n",
              "      <th>PopFemale</th>\n",
              "      <th>PopTotal</th>\n",
              "      <th>PopDensity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>48928</th>\n",
              "      <td>344</td>\n",
              "      <td>China, Hong Kong SAR</td>\n",
              "      <td>2</td>\n",
              "      <td>Medium</td>\n",
              "      <td>2019</td>\n",
              "      <td>2019.5</td>\n",
              "      <td>3418.487</td>\n",
              "      <td>4017.67</td>\n",
              "      <td>7436157.0</td>\n",
              "      <td>7082.054</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       LocID              Location  VarID  ... PopFemale   PopTotal  PopDensity\n",
              "48928    344  China, Hong Kong SAR      2  ...   4017.67  7436157.0    7082.054\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l-05EhcAc5Oq",
        "outputId": "4eb5ca82-f986-4a83-fc18-16aed5abf5ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        }
      },
      "source": [
        "# vou assumir algumas premissas\n",
        "# estou assumindo que na UN China = John Hokpins Mainland China\n",
        "\n",
        "def rename_location(location):\n",
        "  if location=='China':\n",
        "    return 'Mainland China'\n",
        "  if location=='Republic of Korea':\n",
        "    return 'South Korea'\n",
        "  if location=='Iran (Islamic Republic of)':\n",
        "    return 'Iran'\n",
        "  if location=='China, Hong Kong SAR':\n",
        "    return 'Hong Kong'\n",
        "  if location=='United States of America':\n",
        "    return 'US'\n",
        "  return location\n",
        "\n",
        "un_population_total['location_for_who'] = un_population_total.index.map(rename_location)\n",
        "un_population_total.query(\"location_for_who=='South Korea'\").head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PopTotal</th>\n",
              "      <th>location_for_who</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Location</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Republic of Korea</th>\n",
              "      <td>51225321.0</td>\n",
              "      <td>South Korea</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     PopTotal location_for_who\n",
              "Location                                      \n",
              "Republic of Korea  51225321.0      South Korea"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jGSA2Nz-erbM",
        "outputId": "b271f91e-4c7c-4cac-bfa5-2cf2427df1cf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        }
      },
      "source": [
        "un_population_total = un_population_total.set_index(\"location_for_who\")\n",
        "un_population_total.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PopTotal</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>location_for_who</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>3.804176e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Africa</th>\n",
              "      <td>1.308064e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>African Group</th>\n",
              "      <td>1.306321e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>African Union</th>\n",
              "      <td>1.306903e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>African Union: Central Africa</th>\n",
              "      <td>1.540137e+08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                   PopTotal\n",
              "location_for_who                           \n",
              "Afghanistan                    3.804176e+07\n",
              "Africa                         1.308064e+09\n",
              "African Group                  1.306321e+09\n",
              "African Union                  1.306903e+09\n",
              "African Union: Central Africa  1.540137e+08"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fn3B1_3hecht",
        "outputId": "e87be4b0-2d59-42c7-ed52-9c99046fd1ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 348
        }
      },
      "source": [
        "combined_expanded = combined.join(un_population_total).sort_values(\"confirmed\", ascending=False).dropna()\n",
        "combined_expanded.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "      <th>PopTotal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>80271</td>\n",
              "      <td>2981</td>\n",
              "      <td>49955</td>\n",
              "      <td>3.713670</td>\n",
              "      <td>5.631328</td>\n",
              "      <td>1.433784e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>South Korea</th>\n",
              "      <td>5621</td>\n",
              "      <td>35</td>\n",
              "      <td>41</td>\n",
              "      <td>0.622665</td>\n",
              "      <td>46.052632</td>\n",
              "      <td>5.122532e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>3089</td>\n",
              "      <td>107</td>\n",
              "      <td>276</td>\n",
              "      <td>3.463904</td>\n",
              "      <td>27.937337</td>\n",
              "      <td>6.055009e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iran</th>\n",
              "      <td>2922</td>\n",
              "      <td>92</td>\n",
              "      <td>552</td>\n",
              "      <td>3.148528</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>8.291389e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>331</td>\n",
              "      <td>6</td>\n",
              "      <td>43</td>\n",
              "      <td>1.812689</td>\n",
              "      <td>12.244898</td>\n",
              "      <td>1.268603e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>France</th>\n",
              "      <td>285</td>\n",
              "      <td>4</td>\n",
              "      <td>12</td>\n",
              "      <td>1.403509</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>6.512973e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Germany</th>\n",
              "      <td>262</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>8.351705e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spain</th>\n",
              "      <td>222</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.900901</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>4.673678e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>US</th>\n",
              "      <td>153</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>7.189542</td>\n",
              "      <td>57.894737</td>\n",
              "      <td>3.290649e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Singapore</th>\n",
              "      <td>110</td>\n",
              "      <td>0</td>\n",
              "      <td>78</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.804343e+06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  ...  letality_rate_2      PopTotal\n",
              "Mainland China      80271    2981  ...         5.631328  1.433784e+09\n",
              "South Korea          5621      35  ...        46.052632  5.122532e+07\n",
              "Italy                3089     107  ...        27.937337  6.055009e+07\n",
              "Iran                 2922      92  ...        14.285714  8.291389e+07\n",
              "Japan                 331       6  ...        12.244898  1.268603e+08\n",
              "France                285       4  ...        25.000000  6.512973e+07\n",
              "Germany               262       0  ...         0.000000  8.351705e+07\n",
              "Spain                 222       2  ...        50.000000  4.673678e+07\n",
              "US                    153      11  ...        57.894737  3.290649e+08\n",
              "Singapore             110       0  ...         0.000000  5.804343e+06\n",
              "\n",
              "[10 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A4X0wPBMexI4",
        "outputId": "2157f127-219a-4a09-8238-a88981083cd3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 348
        }
      },
      "source": [
        "# O cálculo de incidencia aqui está errado, pois assumi que a população em risco de Mainland China é todo mundo\n",
        "# mas até agora 83% dos casos estão em Hubei\n",
        "# Durante esse momento da epidemia é injusto com a localização (Mainland China) considerar essa incidência.\n",
        "\n",
        "combined_expanded['incidence_ratio'] = combined_expanded['confirmed'] / combined_expanded['PopTotal'] * 100000\n",
        "combined_expanded['mortality_rate'] = combined_expanded['deaths'] / combined_expanded['PopTotal'] * 100000\n",
        "combined_expanded.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>deaths</th>\n",
              "      <th>recovered</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "      <th>PopTotal</th>\n",
              "      <th>incidence_ratio</th>\n",
              "      <th>mortality_rate</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Mainland China</th>\n",
              "      <td>80271</td>\n",
              "      <td>2981</td>\n",
              "      <td>49955</td>\n",
              "      <td>3.713670</td>\n",
              "      <td>5.631328</td>\n",
              "      <td>1.433784e+09</td>\n",
              "      <td>5.598543</td>\n",
              "      <td>0.207911</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>South Korea</th>\n",
              "      <td>5621</td>\n",
              "      <td>35</td>\n",
              "      <td>41</td>\n",
              "      <td>0.622665</td>\n",
              "      <td>46.052632</td>\n",
              "      <td>5.122532e+07</td>\n",
              "      <td>10.973089</td>\n",
              "      <td>0.068326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Italy</th>\n",
              "      <td>3089</td>\n",
              "      <td>107</td>\n",
              "      <td>276</td>\n",
              "      <td>3.463904</td>\n",
              "      <td>27.937337</td>\n",
              "      <td>6.055009e+07</td>\n",
              "      <td>5.101561</td>\n",
              "      <td>0.176713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iran</th>\n",
              "      <td>2922</td>\n",
              "      <td>92</td>\n",
              "      <td>552</td>\n",
              "      <td>3.148528</td>\n",
              "      <td>14.285714</td>\n",
              "      <td>8.291389e+07</td>\n",
              "      <td>3.524138</td>\n",
              "      <td>0.110958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>331</td>\n",
              "      <td>6</td>\n",
              "      <td>43</td>\n",
              "      <td>1.812689</td>\n",
              "      <td>12.244898</td>\n",
              "      <td>1.268603e+08</td>\n",
              "      <td>0.260917</td>\n",
              "      <td>0.004730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>France</th>\n",
              "      <td>285</td>\n",
              "      <td>4</td>\n",
              "      <td>12</td>\n",
              "      <td>1.403509</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>6.512973e+07</td>\n",
              "      <td>0.437588</td>\n",
              "      <td>0.006142</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Germany</th>\n",
              "      <td>262</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>8.351705e+07</td>\n",
              "      <td>0.313708</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spain</th>\n",
              "      <td>222</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.900901</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>4.673678e+07</td>\n",
              "      <td>0.475001</td>\n",
              "      <td>0.004279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>US</th>\n",
              "      <td>153</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>7.189542</td>\n",
              "      <td>57.894737</td>\n",
              "      <td>3.290649e+08</td>\n",
              "      <td>0.046495</td>\n",
              "      <td>0.003343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Singapore</th>\n",
              "      <td>110</td>\n",
              "      <td>0</td>\n",
              "      <td>78</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.804343e+06</td>\n",
              "      <td>1.895133</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                confirmed  deaths  ...  incidence_ratio  mortality_rate\n",
              "Mainland China      80271    2981  ...         5.598543        0.207911\n",
              "South Korea          5621      35  ...        10.973089        0.068326\n",
              "Italy                3089     107  ...         5.101561        0.176713\n",
              "Iran                 2922      92  ...         3.524138        0.110958\n",
              "Japan                 331       6  ...         0.260917        0.004730\n",
              "France                285       4  ...         0.437588        0.006142\n",
              "Germany               262       0  ...         0.313708        0.000000\n",
              "Spain                 222       2  ...         0.475001        0.004279\n",
              "US                    153      11  ...         0.046495        0.003343\n",
              "Singapore             110       0  ...         1.895133        0.000000\n",
              "\n",
              "[10 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0iFDaThokvzC"
      },
      "source": [
        "Penso em comparar com outro virus, como Influenza, em outro pais, como Brasil, em outro estado,\n",
        "como Rio Grande do Sul, em outro período de 2019, em outro tamanho de período de 1 ano inteiro versus 2 meses.\n",
        "\n",
        "Totalmente diferente, qual a chance da comparação ser justa e honesta?\n",
        "\n",
        "Fonte: https://www.cevs.rs.gov.br/informativos-epidemiologicos-2019\n",
        "\n",
        "\n",
        "> O coeficiente de incidência entre os SRAG, está em 3,88/100.000 habitantes, o coeficiente de mortalidade (CM) está em 0,61/100.000 habitantes, enquanto que o CM nacional, na SE 46 foi de 0,50/100.000 habitantes. A letalidade no Estado está em 15,8%.\n",
        "\n",
        "Parece que, dado o coeficiente de incidencia nos paises afetados pelo coronavirus até então, e somente o tempo de 2 meses, além da curva de crescimento de casos novos na China e fora da China, parece que existe ainda um triste potencial alto de um coeficiente de incidência mais alto que Influenza no relatório analisado.\n",
        "\n",
        "Mesmo que comparemos com o CDB Burden Influenza, ou outros relatorios é muito dificil pois estamos no começo da epidemia. Além disso, são muitas variáveis e métricas distintas.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oz21U7QWplzx",
        "outputId": "af9bb96b-a2c9-4a18-de4d-bfcfd8698fd5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 218
        }
      },
      "source": [
        "confirmed.sort_values(last_date, ascending=False).head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Province/State</th>\n",
              "      <th>Country/Region</th>\n",
              "      <th>Lat</th>\n",
              "      <th>Long</th>\n",
              "      <th>1/22/20</th>\n",
              "      <th>1/23/20</th>\n",
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              "      <th>1/27/20</th>\n",
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              "      <th>1/30/20</th>\n",
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              "      <th>2/7/20</th>\n",
              "      <th>2/8/20</th>\n",
              "      <th>2/9/20</th>\n",
              "      <th>2/10/20</th>\n",
              "      <th>2/11/20</th>\n",
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              "      <th>2/18/20</th>\n",
              "      <th>2/19/20</th>\n",
              "      <th>2/20/20</th>\n",
              "      <th>2/21/20</th>\n",
              "      <th>2/22/20</th>\n",
              "      <th>2/23/20</th>\n",
              "      <th>2/24/20</th>\n",
              "      <th>2/25/20</th>\n",
              "      <th>2/26/20</th>\n",
              "      <th>2/27/20</th>\n",
              "      <th>2/28/20</th>\n",
              "      <th>2/29/20</th>\n",
              "      <th>3/1/20</th>\n",
              "      <th>3/2/20</th>\n",
              "      <th>3/3/20</th>\n",
              "      <th>3/4/20</th>\n",
              "      <th>is_mainland_china</th>\n",
              "      <th>is_mainland_china_label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Hubei</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>30.9756</td>\n",
              "      <td>112.2707</td>\n",
              "      <td>444</td>\n",
              "      <td>444</td>\n",
              "      <td>549</td>\n",
              "      <td>761</td>\n",
              "      <td>1058</td>\n",
              "      <td>1423</td>\n",
              "      <td>3554</td>\n",
              "      <td>3554</td>\n",
              "      <td>4903</td>\n",
              "      <td>5806</td>\n",
              "      <td>7153</td>\n",
              "      <td>11177</td>\n",
              "      <td>13522</td>\n",
              "      <td>16678</td>\n",
              "      <td>19665</td>\n",
              "      <td>22112</td>\n",
              "      <td>24953</td>\n",
              "      <td>27100</td>\n",
              "      <td>29631</td>\n",
              "      <td>31728</td>\n",
              "      <td>33366</td>\n",
              "      <td>33366</td>\n",
              "      <td>48206</td>\n",
              "      <td>54406</td>\n",
              "      <td>56249</td>\n",
              "      <td>58182</td>\n",
              "      <td>59989</td>\n",
              "      <td>61682</td>\n",
              "      <td>62031</td>\n",
              "      <td>62442</td>\n",
              "      <td>62662</td>\n",
              "      <td>64084</td>\n",
              "      <td>64084</td>\n",
              "      <td>64287</td>\n",
              "      <td>64786</td>\n",
              "      <td>65187</td>\n",
              "      <td>65596</td>\n",
              "      <td>65914</td>\n",
              "      <td>66337</td>\n",
              "      <td>66907</td>\n",
              "      <td>67103</td>\n",
              "      <td>67217</td>\n",
              "      <td>67332</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>NaN</td>\n",
              "      <td>South Korea</td>\n",
              "      <td>36.0000</td>\n",
              "      <td>128.0000</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
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              "      <td>24</td>\n",
              "      <td>25</td>\n",
              "      <td>27</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>29</td>\n",
              "      <td>30</td>\n",
              "      <td>31</td>\n",
              "      <td>31</td>\n",
              "      <td>104</td>\n",
              "      <td>204</td>\n",
              "      <td>433</td>\n",
              "      <td>602</td>\n",
              "      <td>833</td>\n",
              "      <td>977</td>\n",
              "      <td>1261</td>\n",
              "      <td>1766</td>\n",
              "      <td>2337</td>\n",
              "      <td>3150</td>\n",
              "      <td>3736</td>\n",
              "      <td>4335</td>\n",
              "      <td>5186</td>\n",
              "      <td>5621</td>\n",
              "      <td>False</td>\n",
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              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Italy</td>\n",
              "      <td>43.0000</td>\n",
              "      <td>12.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>3</td>\n",
              "      <td>3</td>\n",
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              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>20</td>\n",
              "      <td>62</td>\n",
              "      <td>155</td>\n",
              "      <td>229</td>\n",
              "      <td>322</td>\n",
              "      <td>453</td>\n",
              "      <td>655</td>\n",
              "      <td>888</td>\n",
              "      <td>1128</td>\n",
              "      <td>1694</td>\n",
              "      <td>2036</td>\n",
              "      <td>2502</td>\n",
              "      <td>3089</td>\n",
              "      <td>False</td>\n",
              "      <td>Others</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Iran</td>\n",
              "      <td>32.0000</td>\n",
              "      <td>53.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>18</td>\n",
              "      <td>28</td>\n",
              "      <td>43</td>\n",
              "      <td>61</td>\n",
              "      <td>95</td>\n",
              "      <td>139</td>\n",
              "      <td>245</td>\n",
              "      <td>388</td>\n",
              "      <td>593</td>\n",
              "      <td>978</td>\n",
              "      <td>1501</td>\n",
              "      <td>2336</td>\n",
              "      <td>2922</td>\n",
              "      <td>False</td>\n",
              "      <td>Others</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Guangdong</td>\n",
              "      <td>Mainland China</td>\n",
              "      <td>23.3417</td>\n",
              "      <td>113.4244</td>\n",
              "      <td>26</td>\n",
              "      <td>32</td>\n",
              "      <td>53</td>\n",
              "      <td>78</td>\n",
              "      <td>111</td>\n",
              "      <td>151</td>\n",
              "      <td>207</td>\n",
              "      <td>277</td>\n",
              "      <td>354</td>\n",
              "      <td>436</td>\n",
              "      <td>535</td>\n",
              "      <td>632</td>\n",
              "      <td>725</td>\n",
              "      <td>813</td>\n",
              "      <td>895</td>\n",
              "      <td>970</td>\n",
              "      <td>1034</td>\n",
              "      <td>1095</td>\n",
              "      <td>1131</td>\n",
              "      <td>1159</td>\n",
              "      <td>1177</td>\n",
              "      <td>1219</td>\n",
              "      <td>1241</td>\n",
              "      <td>1261</td>\n",
              "      <td>1294</td>\n",
              "      <td>1316</td>\n",
              "      <td>1322</td>\n",
              "      <td>1328</td>\n",
              "      <td>1331</td>\n",
              "      <td>1332</td>\n",
              "      <td>1333</td>\n",
              "      <td>1339</td>\n",
              "      <td>1342</td>\n",
              "      <td>1345</td>\n",
              "      <td>1347</td>\n",
              "      <td>1347</td>\n",
              "      <td>1347</td>\n",
              "      <td>1348</td>\n",
              "      <td>1349</td>\n",
              "      <td>1349</td>\n",
              "      <td>1350</td>\n",
              "      <td>1350</td>\n",
              "      <td>1350</td>\n",
              "      <td>True</td>\n",
              "      <td>Mainland China</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Province/State  Country/Region  ...  is_mainland_china  is_mainland_china_label\n",
              "12          Hubei  Mainland China  ...               True           Mainland China\n",
              "33            NaN     South Korea  ...              False                   Others\n",
              "59            NaN           Italy  ...              False                   Others\n",
              "74            NaN            Iran  ...              False                   Others\n",
              "5       Guangdong  Mainland China  ...               True           Mainland China\n",
              "\n",
              "[5 rows x 49 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OhQLPyPArwCo",
        "outputId": "8fc649bd-24ee-437f-c0ed-7288c6793a15",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "# https://en.wikipedia.org/wiki/Hubei\n",
        "# hubei population\n",
        "\n",
        "hubei_population = 59020000\n",
        "confirmed_cases = confirmed.set_index(\"Province/State\").loc[\"Hubei\"][last_date]\n",
        "death_cases = deaths.set_index(\"Province/State\").loc[\"Hubei\"][last_date]\n",
        "recovered_cases = recovered.set_index(\"Province/State\").loc[\"Hubei\"][last_date]\n",
        "\n",
        "letality_rate_1 = death_cases / confirmed_cases * 100\n",
        "letality_rate_2 = death_cases / (death_cases + recovered_cases) * 100\n",
        "print(f\"Letality rate 1: {letality_rate_1}%\")\n",
        "print(f\"Letality rate 2: {letality_rate_2}%\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Letality rate 1: 4.177160484628109%\n",
            "Letality rate 2: 7.629909900100716%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MniOPqEWsJVm",
        "outputId": "dbe00596-16f1-4253-c207-55bd1399a3ef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "# nos estados unidos de acordo com burden report de influenza 2018-2019 estimativa não final\n",
        "letality_rate_hospitalization = 34157 / 490561 * 100\n",
        "\n",
        "print(f\"Letality rate hospitalização EUA influenza 2018-2019: {letality_rate_hospitalization}%\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Letality rate hospitalização EUA influenza 2018-2019: 6.962844579980879%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AIXv6G2Bt3EA",
        "outputId": "81898ed8-1154-4909-bbf1-beb75c39247d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "# nos estados unidos de acordo com burden report de influenza 2018-2019 estimativa não final\n",
        "letality_rate_medical_visit = 34157 / 16520350 * 100\n",
        "\n",
        "print(f\"Letality rate visita médica EUA influenza 2018-2019: {letality_rate_medical_visit}%\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Letality rate visita médica EUA influenza 2018-2019: 0.20675712076317995%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WB44VzHluArz",
        "outputId": "2390609c-7226-46bc-9124-9fea315579dd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "# nos estados unidos de acordo com burden report de influenza 2018-2019 estimativa não final\n",
        "letality_rate_symptomatic = 34157 / 35520883 * 100\n",
        "\n",
        "print(f\"Letality rate sintomáticos EUA influenza 2018-2019: {letality_rate_symptomatic}%\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Letality rate sintomáticos EUA influenza 2018-2019: 0.09616033475293956%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_9bCn0zGuLoS",
        "outputId": "b3013f3a-e039-4d42-e5e6-32bf99a61653",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "incidence_ratio = confirmed_cases / hubei_population * 100000\n",
        "mortality_rate = death_cases / hubei_population * 100000\n",
        "\n",
        "print(f\"Coeficiente de incidencia em Hubei {incidence_ratio}\")\n",
        "print(f\"Coeficiente de mortalidade em Hubei {mortality_rate}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Coeficiente de incidencia em Hubei 113.69535750593019\n",
            "Coeficiente de mortalidade em Hubei 4.749237546594375\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LF2mlYBDvmxs",
        "outputId": "9de4dd0e-d11f-4c6f-b53c-d34e3a471bab",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "# estados unidos, mesmo relatorio de burden, coeficiente de incidencia\n",
        "\n",
        "incidence_ratio = 35520883 / 329450000 * 100000\n",
        "mortality_rate = 34157 / 329450000 * 100000\n",
        "\n",
        "print(f\"Coeficiente de incidencia de influenza 2018-2019 em EUA  {incidence_ratio}\")\n",
        "print(f\"Coeficiente de mortalidade de influenza 2018-2019 em EUA {mortality_rate}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Coeficiente de incidencia de influenza 2018-2019 em EUA  10781.873728942177\n",
            "Coeficiente de mortalidade de influenza 2018-2019 em EUA 10.367885870390044\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mEYKPj3Lw45T"
      },
      "source": [
        "É muito ruim e muito difícil fazer comparação com períodos de tempo diferentes (2 meses / 12 meses). Você quer extrapolar simplesmente e multiplicar por 6? 24 a mortalidade. Mas extrapolar com esse tipo de crescimento pode ser muito irreal. Então infelizmente tem que ir por estimativas.... estatística."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LIOgK9bc0UGL",
        "outputId": "588ec903-c6f6-44b7-8aa6-8549ef92462a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "grouped_per_day = pd.DataFrame([confirmed.sum()[2:-1],recovered.sum()[2:], deaths.sum()[2:]],\n",
        "            index=[\"confirmed\", \"recovered\", \"deaths\"]).T\n",
        "grouped_per_day.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>recovered</th>\n",
              "      <th>deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1/22/20</th>\n",
              "      <td>555.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>17.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/23/20</th>\n",
              "      <td>653.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/24/20</th>\n",
              "      <td>941.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>26.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/25/20</th>\n",
              "      <td>1434.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>42.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/26/20</th>\n",
              "      <td>2118.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>56.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         confirmed  recovered  deaths\n",
              "1/22/20      555.0       28.0    17.0\n",
              "1/23/20      653.0       30.0    18.0\n",
              "1/24/20      941.0       36.0    26.0\n",
              "1/25/20     1434.0       39.0    42.0\n",
              "1/26/20     2118.0       52.0    56.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qbFZwbU41DAc",
        "outputId": "c6aee6de-3c6c-4c9e-92cd-81f2861c59a2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "grouped_per_day[\"letality_rate_1\"] = grouped_per_day[\"deaths\"]/ grouped_per_day[\"confirmed\"] * 100\n",
        "grouped_per_day[\"letality_rate_2\"] = grouped_per_day[\"deaths\"] / (grouped_per_day[\"deaths\"] + grouped_per_day[\"recovered\"]) * 100\n",
        "grouped_per_day.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>confirmed</th>\n",
              "      <th>recovered</th>\n",
              "      <th>deaths</th>\n",
              "      <th>letality_rate_1</th>\n",
              "      <th>letality_rate_2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1/22/20</th>\n",
              "      <td>555.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3.063063</td>\n",
              "      <td>37.777778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/23/20</th>\n",
              "      <td>653.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.756508</td>\n",
              "      <td>37.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/24/20</th>\n",
              "      <td>941.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>2.763018</td>\n",
              "      <td>41.935484</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/25/20</th>\n",
              "      <td>1434.0</td>\n",
              "      <td>39.0</td>\n",
              "      <td>42.0</td>\n",
              "      <td>2.928870</td>\n",
              "      <td>51.851852</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1/26/20</th>\n",
              "      <td>2118.0</td>\n",
              "      <td>52.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>2.644004</td>\n",
              "      <td>51.851852</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         confirmed  recovered  deaths  letality_rate_1  letality_rate_2\n",
              "1/22/20      555.0       28.0    17.0         3.063063        37.777778\n",
              "1/23/20      653.0       30.0    18.0         2.756508        37.500000\n",
              "1/24/20      941.0       36.0    26.0         2.763018        41.935484\n",
              "1/25/20     1434.0       39.0    42.0         2.928870        51.851852\n",
              "1/26/20     2118.0       52.0    56.0         2.644004        51.851852"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I-6r-Kpw1m4G",
        "outputId": "8872b189-36d8-4fbd-d6fe-eadd3d8a059b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        }
      },
      "source": [
        "fig = plt.figure(figsize=(10,5))\n",
        "grouped_per_day[\"letality_rate_1\"].plot()\n",
        "ax = grouped_per_day[\"letality_rate_2\"].plot()\n",
        "plt.legend(['Mortes por casos confirmados (\"otimista\")', 'Mortes por casos recuperados ou óbitos (\"pessimista\")'])\n",
        "plt.title(\"Taxa de letalidade do COVID-19 (evolução acumulada)\", pad=10)\n",
        "plt.grid(linestyle='-')\n",
        "ax.set_ylabel(\"letalidade %\")\n",
        "ax.set_xlabel(\"Fonte Johns Hopkins CSSE / Gráfico e Collab www.alura.com.br\", labelpad=10)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ilZssGw/Hd0Hb57NuPq7gbtDs/2DVR7Dig6wpM7lzZ2HWIJjY2ekqNcYYkyWm\nT5+e4dsombzBEq/c4vRR+Ok/cEMkVMviGZ1b/QNqtIdvnoIdv2Rt2Ynn4PMH4X8zYMdiWGN3rTe5\nn4jQp08fz/OEhAQCAwPp3LnzJZWzevVq5s6dm9XhGR+rUqUKhw4d8nUYfPzxx+zYscMzLUVMTEyq\n52jHjh05duwYx44d45133smyGG6//Xa2bt0K4IkjJ6bJWLFiRYqTG6dl0KBBrF+/PtXlU6ZMydB9\nJvv37++ZIzEp6W3Tpg1Hjx69pHhSY4lXbrF4LMQfh7ajsr7sAn7OxKqlq8D0e+D47qwpNzHRuXpy\n7UyIjIJr6zpdpWdPZ035xmSTgIAA1q5dy+nTzrn6/fffc911111SGQkJCbkm8cro/Q1zWm6KKzfF\nklF9+vRh+PDhGVp37ty5lCpVKksTr3Xr1nHu3LmL7u+YE+rXr88bb7xxSdu8//771K5dO9XlGU28\nUtK3b98sq1dLvHKD47vh13EQdhdUCE1//cwoWgru/sQZR/Zp78tPjlRh3gj4bTI0fxKaPeF0kcbu\ncbpMjcnlOnbsyJw5cwCYOnUqPXv29Cw7cuQI3bp1IywsjMaNG3vurRgdHU3fvn1p2rQpffv25bnn\nnmPatGlEREQwbdo0Tp48ycCBA2nYsCF16tRh9uzZgPMF1rBhQyIiIggLC2PTpk0XxVO8eHEef/xx\ngoODiYyM5ODBg4DTqta4cWPCwsLo3r2757/uli1b8thjj1G/fn1ef/31C8qKi4tjwIABhIaGEhYW\nxqxZswAYPHgw9evXJzg4mKioKM/6I0aMoHbt2oSFhTFs2DAAtm/fTuvWrQkLCyMyMpKdO3cCMGPG\nDEJCQggPD6d58+YXHUdMTAzNmjWjS5cuni/Bjz/+2HP8DzzwAOfOOUMS5s2bR926dQkPDycyMtJT\nx6+88oqnvJCQELZv38727du58cYb6d27N7Vq1eL222/33A9y5cqVtGjRgnr16tG+fXv27duXYh19\n9dVXNGrUiDp16tCmTRv2798PwOHDh2nXrh3BwcEMGjQI7zu6vPrqq4SEhBASEsJrr70GwMmTJ+nU\nqRPh4eGEhIR4bu/kLa33bcWKFQAcOnQoxdYjVWX48OGEhIQQGhp6QfmxsbF06tSJoKAgHnzwQRIT\nE4HzrXQjRoxgy5YtREREMHz4cFSVZ5555qKy9u3bR/PmzYmIiCAkJMRzH01vU6ZMoWvXrp7ngYGB\nF/yOiYmhefPmKcbz3Xff0aRJE+rWrcsdd9zhmacupXMtpXPKu3UvOjqafv360axZMypXrsxnn33G\nk08+SWhoKB06dODs2bMX1I87mC4AACAASURBVO25c+fo37+/55jHjh3LzJkz+e233+jduzcRERGc\nPn2a559/ngYNGhASEsL999/ved9LlixJoUKFKFOmDH5+fgB06dKFqVOnXlRHmaKquf6nZs2amq99\n/pDq8+VUj2xPc7WFCxde/r7+mKMadZXqrPtVExMzV0Ziour3UU45856+sJzJt6n+u5LqqSOXH2sa\nsqQu8oG8WA/r168//2TuU6ofdsySn7PvtXMez30q3RgCAgJ0zZo1etttt+np06c1PDxcFy5cqJ06\ndVJV1aFDh2p0dLSqqi5YsEDDw8NVVTUqKkrr1q2rp06dUlXVCRMm6JAhQzzljhw5UidPnqyqqkeP\nHtUaNWpoXFycDh06VD/++GNVVT1z5oxne2+AZ51Ro0Z5yg0NDdWYmBhVVX322Wf10UcfVVXVFi1a\n6ODBgy8qJzY2Vp988knPeqqqR444f4+HDx9WVdWEhARt0aKFrlmzRg8dOqQ1a9bURPfv+OjRo6qq\n2rlzZ504caKqqn7wwQfatWtXVVUNCQnR3bt3X7Cut4ULF2qxYsV069atquq83507d9a///5bVVUH\nDx6skyZN0gMHDmjFihU96yXFFhUVpWPGjPGUFxwcrNu2bdNt27YpoIsXL1ZV1QEDBuiYMWP077//\n1iZNmuiBAwdUVfXTTz/VAQMGaGxs7EV1dOTIEc9xvvfee/rEE0+oqurDDz+so0aNUlXVr7/+WgE9\nePCgrlixQkNCQjQuLk5PnDihtWvX1lWrVunMmTN10KBBnnKPHTt2UT2k9b4tX75cVVUPHjyolStX\nvmjbmTNnaps2bTQhIUH/+usvrVSpku7du1cXLlyohQsX1i1btmhCQoK2adNGZ8yYoaqqlStX1oMH\nD+q2bds0ODj4grJatWp1UVmvvPKKjh49WlWd8yE2NvaiOJo3b66///77Ra8nSS2egwcParNmzTQu\nLk5VVV988UUdNWpUqudaSueU999jVFSUNm3aVP/++29dvXq1Fi1aVOfOnauqqt26ddPPP//8grpd\nsWKFtmnTxhNnUpk333yzp+5Vz59zqqp9+vTRL7/8MtVjVVWtXr26Hjp06KLXL/hMcwErNJWcxlq8\nfG3/eljzCTS8H0pXzv793djRGfP1+6fw638zV8aiV5yu0foDod1oZ+b8JG2iIT4Wfno1K6I1JtuE\nhYWxfft2pk6dSseOHS9YtnjxYvr27QtA69atOXz4MLGxsYDzn2/RokVTLPO7777z3DS7ZcuWxMfH\ns3PnTpo0acILL7zASy+9xI4dO1LcvkCBAtx1112A08W0ePFijh8/zrFjx2jRwhn32a9fPxYtWuTZ\nJmn95ObPn8+QIUM8z0uXLg04A7Xr1q1LnTp1WLduHevXr6dkyZIUKVKEe++9l88++4xixYoBsGTJ\nEnr16gU43SyLFy8GoGnTpvTv35/33nvP03KVXMOGDalatSoACxYsYOXKlTRo0ICIiAgWLFjA1q1b\n+fXXX2nevLlnvTJl0r/HrPfNvZPqaMOGDaxdu5a2bdsSERHB6NGj2b37/HAK7zravXs37du3JzQ0\nlDFjxrBu3ToAFi1a5Bnz16lTJ099LV68mO7duxMQEEDx4sXp0aMHP/30E6GhoXz//fc89dRT/PTT\nT5QsWfKCONN739KzePFievbsiZ+fH1dffTUtWrRg+fLlnrqtVq0afn5+9OzZ0/O+pFXW7bffflFZ\nDRo0YMKECURHR/O///0vxXsY7tu3z9O6lZqU4vn1119Zv349TZs2JSIigkmTJrFjx45Uz7WMnFO3\n3HIL/v7+hIaGcu7cOTp06ABAaGjoRRcfVKtWja1bt/Lwww8zb948rroq5YnIFy5cSKNGjQgNDeWH\nH37wnA+pKV++fKa7Kr3ZDZd8bX40FCrhXHmYU5oNg31r4Ltn4OraUK1lxrdd8jYsHA3hPaHjfy5M\nugAqhED43bD0XWj0AJSsmJWRm/zmlhezrKjTmbgBbpcuXRg2bBgxMTEcPnw4Q9sEBASkukxVmTVr\nFkFBQRe8XqtWLRo1asScOXPo2LEj7777Lq1bt05zP5L8b+sSY0lu27ZtvPLKKyxfvpzSpUvTv39/\n4uPjKViwIMuWLWPBggXMnDmTt956ix9++CHVcsaNG8fSpUuZM2cO9erVY+XKlZQtWzbVuFSVfv36\n8e9///uCdb766qsUyy9YsKCnuwogPj7e8zh5nYgIqkpwcDBLliy5YNmJEycuiuXhhx/miSeeoEuX\nLsTExBAdHZ3qcaalZs2arFq1irlz5/LMM88QGRnJc889l6FtvY/P+9gyKqU6yIzmzZuzaNEi5syZ\nQ//+/XniiSe45557LlinaNGi6caY2nvStm3bFLvmUjrXUjqnkitcuDDg/IPi7+/v2W+BAgUuGr9X\nunRp1qxZw7fffsu4ceOYPn06H3744QXrxMfH89BDD7FixQoqVapEdHR0uscaHx+f6j9dl8JavHxp\n+2LY9C3c/BgUS/+/vSxToAB0HwflasCMAXB0e8a2W/EhfPs01O4GXd5KfcqLVv9wfi98IUvCNSa7\nDBw4kKioKEJDLxxb2axZM6ZMmQI4Y03KlSuX4n/NJUqU8HzBA7Rv354333zTM1bkt9+cG9Zv3bqV\natWq8cgjj9C1a1fPmDFviYmJzJw5E4BPPvmEm2++mZIlS1K6dGnP+JvJkyd7WlHS0rZtW95++23P\n86NHjxIbG0tAQAAlS5Zk//79fPPNN4AzHuz48eN07NiRsWPHsmbNGgBuuukmPv3UuUp5ypQpNGvW\nDIAtW7bQqFEjnn/+eQIDA9m1a1easURGRjJz5kwOHDgAOOPnduzYQePGjVm0aBHbtm3zvA7OWKVV\nq1YBsGrVKs9ycG7SnJRgJdVRUFAQBw8e9Lx+9uzZVFsujh8/7rmIYtKkSZ7XmzdvzieffALAN998\n4xmP1axZM7744gtOnTrFyZMn+fzzz2nWrBl79+6lWLFinsHvSfEmSet9q1KliiexSHq/k2vWrBnT\npk3j3LlzHDx4kEWLFtGwYUPASVy2bdtGYmIi06ZN4+abb75g2+TnZLNmzZg1a9ZFZe3YsYOrr76a\n++67j0GDBl10DOD8w7B58+YUY0ySUjyNGzfm559/9mx78uRJNm7cmOq5dqnnVHoOHTpEYmIit912\nG6NHj/YcW/HixT11k5RklStXjri4uFTfiySqyl9//ZUlV3Rai5evJN0Iu8S10Hhwzu+/cAlnsP17\nrZzB9vd+B4XS+O95zafw9RPOtBQ93gO/NE6dUpWg0f3wy1vQZAhcHZz18RuTBSpWrJjiJevR0dEM\nHDiQsLAwihUrdsGXtLdWrVp5uhZHjhzJs88+y2OPPUZYWBiJiYlUrVqVr7/+munTpzN58mT8/f2p\nUKECTz/99EVlBQQEsGzZMkaPHk358uU9g6AnTZrEgw8+yKlTp6hWrRoTJkxI97ieeeYZhgwZQkhI\nCH5+fkRFRdGjRw/q1KnDjTfeeEGX3YkTJ+jatSvx8fGoKq++6gwTePPNNxkwYABjxowhMDDQs9/h\nw4ezadMmVJXIyEjCw8PTjKV27dqMHj2adu3akZiYiL+/P2+//TaNGzdm/Pjx9OjRg8TERMqXL8/3\n33/PbbfdxkcffURwcDCNGjWiZs2anrKCgoJ4++23GThwILVr12bw4MEUKlSImTNn8sgjj3D8+HES\nEhJ47LHHuP7661N8X++44w5Kly5N69atPUldVFQUPXv2JDg4mJtuusmzbd26denfv78n6Rk0aBB1\n6tTh22+/Zfjw4Z7Wl//+9+JhG6m9b8OGDePOO+9k/PjxdOrUKcU66969O0uWLCE8PBwR4eWXX6ZC\nhQr8+eefNGjQgKFDh7J582ZatWpF9+4XTrZdtmxZmjZtSkhICLfccgsvv/wyP/7440VlTZo0iTFj\nxuDv70/x4sX56KOPLoqjU6dOxMTE0KZNm1Tf35TiKVCgABMnTqRnz56cOePcNWX06NGUKFEixXMt\npXPqxx9/THWf6dmzZw8DBgzwtCwmtbb27t2bBx98kKJFi7JkyRLuu+8+QkJCqFChAg0aNEizzJUr\nV9K4cWMKFsyCtCm1wV+56SdfDq5f+7kzOH3lpAxvki0DqTd9rxpdSnV6v9QH26/93Fln4q2qf5/O\nWLknDzuD7D++I8tC9ZYXB5Vnh7xYDykNRM0KKQ0OzksCAgKypJy8Xg+pST5oPD35tR4yI7N1cerU\nKW3UqJEmJCSkuNx7AHxecDnnxCOPPKLz589PcZkNrs8Lzp2FBc9D4I0Q3su3sVRv48zBte5z+Pm1\ni5dv/BZm3QsVG0LPqeBfJGPlFisDNz/hdKVuT3vwpzHGmNynaNGijBo1ij179vg6FJ8LCQnxTHly\nuayr8XJtjYETf13aNntXOzevvntq2l12OaXpo85g+/mj4OoQ5x6P4BzbtL7O3GK9p6fdFZmSRg84\nc3p9/xwMWnDxQHxjjEfSPEcmZVWqVGHt2rW+DuOK0759+1SXtWzZkpYtW+ZcMD503333ZVlZueBb\nPw87shU+6pr+eimp1gqCbsnaeDJLBLq+BYc2wcx74f6FcPIgTO0JZW+APp9BkZLpl5Ocf1Fo9TTM\nHgLrZzv3jTQGZ4hDZq/GMsaY3EK9JtvNKEu8LseGec7vAfOgxNWXtm2pyrmrBahQANw9Bca3hCl3\nOInXVdfCPbMv74rL8J7OIPsFz8ONncDPP8tCNnlTkSJFOHz4MGXLlrXkyxiTZ6kqhw8fpkiRDA7B\ncVnidTk2fuOM06rcxNeRZI3SleGOiTC5O5S8Du75EoqXv7wyC/g5k6pOvQtWTYIGg7IgUJOXVaxY\nkd27d3tuiZNV4uPjL/kDMD+yenBYPZxndeHIjnooUqQIFSte2nyVlnhlVvxx2PELNBnq60iyVrUW\nMGi+M/Hp5SZdSWq2h8pNIeYlCLsbChfPmnJNnuTv7++ZrTwrxcTEUKdOnSwvN6+xenBYPZxndeHI\nLfVgVzVm1uYFkJgANTv4OpKsd13drEu6wOlSbTMKTh5wZr43xhhjrlDZmniJyHYR+Z+IrBaRFe5r\nZUTkexHZ5P4unZ0xZJuN86BoGajU0NeR5A2VGkCtLvDLGxCXtV1MxhhjTF6REy1erVQ1QlXru89H\nAAtUtQawwH2et5xLgE3fQY12zhgmkzGRUXD2NCx62deRGGOMMT7hi67GrkDS/TcmAXlvjoHdy+H0\nUQjKh92M2alcdajXz7nn4+Etvo7GGGOMyXHZnXgp8J2IrBSR+93XrlbVfe7jv4BLnIchF9j4DRQo\nCDe09nUkeU+LEeBXCH4Y7etIjDHGmBwnmZn8K8OFi1ynqntEpDzwPfAw8KWqlvJa56iqXjTOy03U\n7gcIDAysN3369GyL81I1WDaEvwuVYU3EP3N0v3FxcRQvnvevCKyybQpVdkxnZd1XOHFVjUyVkV/q\n4nJZPZxndeGwenBYPZxndeHIyXpo1arVSq8hVhfI1sTrgh2JRANxwH1AS1XdJyLXADGqGpTWtkFB\nQbphw4YciDIDjmyFN+pAhxeh8eAc3XVMTEz+uD3DmRPwegSUrwX9vsrURLL5pi4uk9XDeVYXDqsH\nh9XDeVYXjpysBxFJNfHKtq5GEQkQkRJJj4F2wFrgS6Cfu1o/YHZ2xZAtNn7r/M6P00jklMIloMVT\nsP0nZ1oOY4wx5gqRnWO8rgYWi8gaYBkwR1XnAS8CbUVkE9DGfZ53bHBnqy+T9RNAXlHq9YfSVZ0b\naMcd8HU0xhhjTI7ItpnrVXUrEJ7C64eByOzab7aKPw47foYmQ3wdSd5XsBC0Gw3T+sDYYAjuDg0f\ngIr1fB2ZMcYYk21s5vpL4Zmt/hZfR5I/1OoMQ5dDvQHw51x4vzW81xrWTIOEM76OzhhjjMlylnhd\nCputPuuVqwEdX4Yn1sMtYyA+Fj6/H8aGwA//gth96ZdhjDHG5BGWeGVU4jmbrT47FbkKGt0PQ5ZB\nn8+c+0UuGgOvhcDMgbBzKeTQFbjGGGNMdsm2MV75zq5lNlt9TihQAKpHOj9HtsKy9+G3j2HtLLgm\n3BkHFnKbr6M0xhhjMsVavDLKZqvPeWWqQYcXnG7ITq86475mPwRja1Pq6BpfR2eMMcZcMku8MmrD\nPKjcFIqU9HUkV57CxaHBvfDQr3DPl1CsLLX+GAsnD/s6MmOMMeaSWOKVEUe2wqENEGRXM/qUCFRr\nAbd/iP/ZEzDncRv3ZYwxJk+xxCsjPLPVt/dtHMZRIZRtVXvB+tnwe+65h6cxxhiTHku8MmLDN1Au\nyBlzZHKFXZW6wfVNYO4wOLbL1+EYY4wxGWKJV3qSZqu3qxlzF/GDbv8FTYQvBkNioq8jMsYYY9Jl\niVd6tvxgs9XnVmWqQod/OzfbXjrO19EYY4wx6bLEKz0bbLb6XK1OXycpnh8NB/7wdTTGGGNMmizx\nSovNVp/7iUCXN6BwCfjsfkj429cRGWOMMamyxCstu5bB6SN2NWNuV7w83Po6/PU7/PiSr6Mxxhhj\nUmWJV1qSZquvHunrSEx6anWGiD6w+FXnvo7GGGNMLmSJV1o2fmuz1eclHf4NJSvC5w/AmThfR2OM\nMcZcxBKv1BzZBgf/tNnq85IiV0G3cXB0O3z3jK+jMcYYYy5iiVdqNs5zftv4rrylSlO46WFYOeH8\nHQeMMcaYXMISr9TYbPV5V+tnoHwwzB5qN9I2xhiTq1jilZL4WJutPi8rWBh6jIf4Y/D1o3YjbWOM\nMbmGJV4p2bLAZqvP6yqEQKt/wB9fwZpPfR2NMcYYA1jilbIN86BoaZutPq+76WG4/ib45km7kbYx\nxphcwRKv5Gy2+vyjgB90txtpG2OMyT0s8Upu93J3tnob35UvlK4CHV50bqT982u+jsYYY8wVrqCv\nA8h1Nths9flOnT7OuL0Fo0AKwM2P+ToiY4wxVyhLvJLbOM9mq89vRKDHe07SNT8K4o9D5HPO68YY\nY0wOssTLW9Js9XX7+ToSk9X8/J3kq3AJ536OZ07ALS9DAettN8YYk3Ms8fKWNNO5zd+VPxXwg86v\nQeGr4Jc34EwsdH0H/OzPwBhjTM6wbxxvG222+nxPBNo+73Ql//BP52bat38I/kV8HZkxxpgrgPWz\nJImPhe02W/0VQQSaD4NbxsCGOfDJnU4CZowxxmQzS7ySrJ0JiWdttvorSaP7ods42L4YJneD00d9\nHZExxph8zhIvgON74Pso52rGSo18HY3JSRE94c5JsG8NTOwMcQd8HZExxph8zBIvVfjyYefejF3f\ntqvcrkS1boVe0+DIVviwg91eyBhjTLaxLGPVR87kmm2fhzJVfR2N8ZUbWkPfL+DUISf5OrTJ1xEZ\nY4zJh67sxOvYLvj2H1ClGdS/19fRGF+7vhH0nwPnzjjJ177ffR2RMcaYfObKTbxU4cuhzg2Uu75l\nXYzGUSEUBsyDgkWcMV87l/o6ImOMMflItmcbIuInIr+JyNfu86oislRENovINBEplN0xpGjlBNga\nA+3+6dxI2Zgk5arDwHkQUA4+7mHdjsYYY7JMTjTzPAr84fX8JWCsqlYHjgI538d3dAd89yxUbQH1\nB+b47k0eUKoS9PsK/ArBjP5w9rSvIzLGGJMPZGviJSIVgU7A++5zAVoDM91VJgHdsjOGiyQmOl2M\n4HQx2o2STWpKXgfd34X9a52xgMYYY8xlElXNvsJFZgL/BkoAw4D+wK9uaxciUgn4RlVDUtj2fuB+\ngMDAwHrTp0/Pkpiu3TOXmpveZUPNIey7tl2WlJlT4uLiKF68uK/DyBVysi6qbZnI9bs+Z13tJzlY\nvmmO7DOj7Jw4z+rCYfXgsHo4z+rCkZP10KpVq5WqWj+lZdl2r0YR6QwcUNWVItLyUrdX1fHAeICg\noCBt2fKSi7jYkW3w88dwQ2uCev6LoDzW2hUTE0OW1EM+kKN10awpTNhN8JZx0KZXrpp2xM6J86wu\nHFYPDquH86wuHLmlHrKzq7Ep0EVEtgOf4nQxvg6UEpGkhK8isCcbYzgvMRFmD4UCftDlTetiNBnn\n5w+3feCcMzMHQMIZX0dkjDEmj8q2xEtVR6pqRVWtAtwN/KCqvYGFwO3uav2A2dkVwwWWvwc7FkP7\nF6BkxRzZpclHSld27myw9zeYH+3raIwxxuRRvpi86ingCRHZDJQFPsj2PR7e4nxZVm8Ldfpk++5M\nPlXrVmj4APz6Dvw519fRGGOMyYNyJPFS1RhV7ew+3qqqDVW1uqreoarZ22+TmAizh0ABf7j1deti\nNJen3T/hmnD4YrDd09EYY8wly//TtS8dBzuXQId/O9MDGHM5ChaG2ydA4jmYdS+cO+vriIwxxuQh\n+TvxOrQZFjwPNdpDRC9fR2Pyi7I3wK2vwa6l8MNoX0djjDEmD8m/iVfiOZj9EBQsZF2MJuuF3g71\n+sPPr8Gm+b6OxhhjTB6RJxKvQmePw7ovYMcSZ6D8mbj0N/r1HadF4paX4aprsj9Ic+Xp8CKUrw2f\n3w+x+3wdjTHGmDwg2yZQzUqF4w/CjH4XvugfAMXLe/1c7f6Uh4JFnS6goI4Qdpdvgjb5n39RuGMi\njG8JswZBvy+deeKMMcaYVOSJxCuueFUYPBvi9kPcgWS/98OhTbB9MZw+en6joqWh81jrYjTZKzAI\nOv3Hucrxx5eh1UhfR2SMMSYXyxOJl4ofXB3s/KQl4QycPOgkY6UqQ0C5nAnQXNkiesG2n+DHl6Dy\nTVCtha8jMsYYk0vliTFeGVawsDMr/XX1LOkyOavjGChXAz67z2mNNcYYY1KQvxIvY3ylcHFnfq/4\n4/DZ/c7EvcYYY0wylngZk1UqhDhXOm5dCN+OBFVfR2SMMSaXyRNjvIzJM+r1dy72+PVtKFoGWj7l\n64iMMcbkIhlOvESkOhANFAVeUdUl2RWUMXmWCLQbDfHHIOYFKFISGj/o66iMMcbkEqkmXiJSRFXj\nvV76J/Ck+/grICI7AzMmzypQAG59wxnvNe8pKFoKwu/2dVTGGGNygbTGeH0lIvd4PT8LVAEqA+ey\nMyhj8jy/gnDbB1C1OXzxEPw519cRGWOMyQXSSrw6AFeJyDwRaQ4MA9oD3YHeORGcMXmafxG4+xO4\nNgJm9Hfm+jLGGHNFSzXxUtVzqvoWcBfQBXgdmKCq/6eqf+ZUgMbkaYVLQO+ZUKYqTL0b9qzydUTG\nGGN8KNXES0QaichM4L/AROAZ4F8i8h8RKZVD8RmT9xUrA30/d35/fBsc3ODriIwxxvhIWl2N7wKP\n4FzJ+K6qblHVu4EvgWk5EJsx+cdV18I9s8HPHz7qBsd2+joiY4wxPpBW4pXA+cH0fye9qKo/qmr7\nbI7LmPynTDXo8xmcPekkX3ZrIWOMueKklXj1Am4DWgP3pLGeMSajKoRArxlwYh9M7gGnj/k6ImOM\nMTkorcH1G92B9CNVdVdOBmVMvnZ9I7hrMhz8Ez65C/4+5euIjDHG5BC7V6MxvlC9Ddz2PuxeBtPv\ngYS/09/GGGNMnmeJlzG+EtwNOr8Gm7+Hzx+ARJuX2Bhj8rsM3atRRIoC16uqXQdvTFaq18+5r+P3\nz0FAOeg4xtcRGWOMyUbptniJyK3AamCe+zxCRL7M7sCMuWI0fRSaDIVl42HpeF9HY4wxJhtlpKsx\nGmgIHANQ1dVA1WyMyZgrT9vnIaijc1PtTfN9HY0xxphskpHE66yqHk/2mmZHMMZcsQr4QY/3oHww\nzBwAB/7wdUTGGGOyQUYSr3Ui0gvwE5EaIvIm8Es2x2XMladwcej1KfgXhU/uhJOHfB2RMcaYLJaR\nxOthIBg4A0wFYoHHsjMoY65YJStCz6nOrPaf9oKz8b6OyBhjTBZKN/FS1VOq+g9VbaCq9d3H9m1g\nTHa5rh50Hwe7lsKXD4Naz74xxuQXqU4nISJfkcZYLlXtki0RGWMguDsc3gw/jIZyNaHFcF9HZIwx\nJgukNY/XK+7vHkAF4GP3eU9gf3YGZYwBmg2DQ5th4WgoewOE9PB1RMYYYy5TqomXqv4IICL/UdX6\nXou+EpEV2R6ZMVc6EejyBhzdDl8MhlKVoWI9X0dljDHmMmRkcH2AiFRLeiIiVYGA7AvJGONRsDDc\nPQWKXw1T74Zjdr96Y4zJyzKSeD0OxIhIjIj8CCzErmo0JucElINe0yEh3km+zpzwdUTGGGMyKSNX\nNc4DagCPAo8AQar6bXYHZozxUv5GuGOCM7HqrEF2Q21jjMmjMtLiBU7iFQSEA3eJyD3pbSAiRURk\nmYisEZF1IjLKfb2qiCwVkc0iMk1ECmU+fGOuINXbwC0vwcZ5zk21jTHG5DlpXdUIgIhEAS2B2sBc\n4BZgMfBROpueAVqrapyI+AOLReQb4AlgrKp+KiLjgHuB/2b+EIy5gjS8z5lmYslbULY6dttUY4zJ\nWzLS4nU7EAn8paoDcFq9Sqa3kTri3Kf+7o8CrYGZ7uuTgG6XGrQxV7R2/4LqbWHuMEodXePraIwx\nxlwC0XRmxRaRZaraUERWAq2AE8AfqnpjuoWL+AErgerA28AY4FdVre4urwR8o6ohKWx7P3A/QGBg\nYL3p06df0oHlR3FxcRQvXtzXYeQKV3pd+CWcou6qp/A/c4jf6o3hdLGKvg7J5670cyKJ1YPD6uE8\nqwtHTtZDq1atViabissj3a5GYIWIlALew0mi4oAlGdmxqp4DItztPwfSTda8th0PjAcICgrSli1b\nZnTTfCsmJgarB4fVBVAvmL/faUajza/CoPlQrIyvI/IpOyccVg8Oq4fzrC4cuaUeMnJV40OqekxV\nxwFtgX5ul2OGqeoxnGkomgClRCQp4asI7LnEmI0xAKUrsy54BBzfBTP6wbmzvo7IGGNMOlJNvESk\nbvIfoAxQ0H2cJhEJdFu6EJGiOEnbHzgJ2O3uav2A2Zd7EMZcqY6Xqg23vg7bFsHc4XZDbWOMyeXS\n6mr8j/u7CFAfWAMIkOJwQQAAIABJREFUEAaswGm9Sss1wCR3nFcBYLqqfi0i64FPRWQ08BvwwWXE\nb4yJ6AUHN8DPr0H5WtDoAV9HZIwxJhVp3auxFYCIfAbUVdX/uc9DgOj0ClbV34E6Kby+FWiYyXiN\nMSmJjHKmmZg3AsrcADXa+DoiY4wxKcjIdBJBSUkXgKquBWplX0jGmEtWoAB0fxfKB8PMAXDgT19H\nZIwxJgUZSbx+F5H3RaSl+/Me8Ht2B2aMuUSFi0PPqVCwCEy9C04e9nVExhhjkslI4jUAWIdzr8ZH\ngfXua8aY3KZUJbj7E4jdB9P7QsLfvo7IGGOMl4xMJxGvqmNVtbv7M1ZV43MiOGNMJlRqAF3fhh0/\nw5zH7UpHY4zJRVIdXC8i01X1ThH5H86tfi6gqmHZGpkxJvPC7oBDG2DRGAisBTcN9XVExhhjSHs6\niUfd351zIhBjTBZr+bQzzcR3zzg31A7q4OuIjDHmipfWdBL73N87ci4cY0yWKVAAuo+DYztg1r1w\n73dwdfD/t3fncXJVZf7HP09V9b5kIZ09EMAQCAECCftiRxZBWUQ2ERR0HBzHBRl38acwgzO4o8Io\ni1FGUBbBgQFlC0b2JUA2IIEQwCRkhWydpJfqOr8/zqmu25XqTifpqurq/r5fr/uqe89d6tynbtV9\n6txTt4pdKxGRAa27O9dvMrONOYZNZraxkJUUkZ1UXgPn3wbltfCHj0HTmmLXSERkQOsy8XLO1Tnn\n6nMMdc65+kJWUkR2Qf1of5uJzavh9gsg2VLsGomIDFg9uZ0EAGY23Mx2Tw/5rJSI9LIxh8BHfgVL\nn4V7v6RfOoqIFEl3nesBMLPT8f/bOBpYDeyB/7NrdRYRKSWTPwprX4dZ/wmJcjj1GojFi10rEZEB\nZbuJF/AfwBHAI865g81sOnBhfqslInnx/q9Deys8/mNo2QRn3uCTMBERKYieJF5tzrl3zSxmZjHn\n3N/M7Jq810xEep8ZHP//oLIeHv6uT77O/T2UVxe7ZiIiA0JP+nitN7Na4DHgVjP7ObA5v9USkbw6\n+lI47eeweCbc8lFo3lDsGomIDAg9SbzOALYAlwEPAG+gm6qKlL6pF8PZv4Flz8PvTtWtJkRECqAn\nidd3nXMp51zSOXezc+4XwDfyXTERKYDJZ/n7fK19HX57CmxYVuwaiYj0az1JvE7MUXZKb1dERIpk\nwonwibuhaRXMOBnWLi52jURE+q3u7lz/ufAH2RPNbF5keBOYV7gqikje7XEUXPR/0LYFfnsyrJxf\n7BqJiPRL3bV4/QE4Dbg3PKaHqc453U5CpL8ZPQU+9QDEy+G3H4Z/PFvsGomI9Dvd/WXQBufcW865\n84FxwAfCH2bHzGzPgtVQRAqnYR/49ANQsxv8/iP+V48iItJrttvHy8y+h+9M/61QVA7cks9KiUgR\nDd4dPv0gDN0L/nAevHJPsWskItJv9KRz/ZnA6YR7dznn3gHq8lkpESmy2uFw8X0w+mC482J4Sd+1\nRER6Q08Sr1bnnAMcgJnV5LdKItInVA2BT/4v7Pl+uOfz8JevwZb3il0rEZGS1pPE6w4zux4YbGb/\nDDwC3JjfaolIn1BeAx+/HQ79DDx/E/xyqn9sTxa7ZiIiJWm7iZdz7sfAn4C7gIn4G6r+Mt8VE5E+\nIlEBH/4JfPYxGD4J7v8KXH8cvPlYsWsmIlJyetLihXPuYefc15xzX3XOPZzvSolIHzTyAN/v69z/\n8X+uffNpcPuFsO6tYtdMRKRkJLqaYWabCP26smcBzjlXn7daiUjfZAaTzoAJJ8FT18ITP4XXHoKj\nvgjHXAYVtcWuoYhIn9bdfbzqnHP1OYY6JV0iA1xZFbz/a/CF2T4Re/zHcO00mHcHuFzf10REBHp4\nqVFEJKdBY+CsG+HTD0HdSLj7n+E3J8HyF4tdMxGRPkmJl4jsut0Ph888Cmf8t+/zdeN0+N/Pw6aV\nxa6ZiEifosRLRHpHLAYHXwBffAGOvhTm3Q7XHAj3XQbvvVns2omI9AlKvESkd1XWw4n/Dl94Hqac\n7+96/8upcNdnYNXLxa6diEhRKfESkfwYuiec9nO4dB4c+a+w6K/wq6P8/z/+45li105EpCiUeIlI\nftWPgpOugi/Ph+mXw9LnYMYHYcYp8PrD+hWkiAwoSrxEpDCqh8L7vw6XLYCTr4b1b8OtZ8P1x8KC\nuyDVXuwaiojkXd4SLzMbZ2Z/M7NXzOxlM7s0lA81s4fN7PXwOCRfdRCRPqi8Bo74HHxpDpxxHbQ1\nw58+7fuBzf4tJFuKXUMRkbzJZ4tXEviKc24ScATweTObBHwTmOmcmwDMDNMiMtAkyuHgC+Hzz/q/\nIaocBPd9Ga45AB79PmxYXuwaioj0urwlXs65Fc65F8P4JuBVYAxwBnBzWOxm4CP5qoOIlIBY3N/9\n/pJZ8Ik/w6iD4LEfwTWT4bYLYPFMSKWKXUsRkV7R5X819iYzGw8cDDwLjHDOrQizVgIjClEHEenj\nzGDvD/hh3Vv+suNLv4eF98HQvWDap2HKBb6vmIhIiTKX518UmVkt8Hfg+865u81svXNucGT+Oufc\nNv28zOwS4BKAhoaGqXfccUde61kKmpqaqK3VnxCDYpHW3+NgqTYa1jzJmOUPMGjjq7THylnTcAzL\nx5zCproJPlkL+nssekpx8BSHDMXCK2Qcpk+f/oJzblqueXlNvMysDLgPeNA599NQtghodM6tMLNR\nwCzn3MTutjNx4kS3aNGivNWzVMyaNYvGxsZiV6NPUCy8ARWHlQtg9m9g7u3Qttlfkjz0MzD5bCiv\nHlix6Ibi4CkOGYqFV8g4mFmXiVc+f9VowG+AV9NJV3AvcFEYvwi4J191EJF+ZORkOPVn8JWF8KEf\nQ3sb3PtF+Mm+8NdvUrl1xfa3ISJSZPns43U08AlgvpnNCWXfBq4G7jCzfwLeBs7NYx1EpL+prIfD\n/tm3dv3jaXj+N/D8TRyeaoemB+GoL8GYQ4pdSxGRnPKWeDnnngCsi9nH5+t5RWSAMIM9jvLDxqtY\neue32X3xI/Dyn2H8sXD0l+F9x3fqByYiUmy6c72IlL76USzZ+yK47GX/90TvvgG3ngW/Ohrm3uYv\nS4qI9AFKvESk/6ish6O+CJfOhY/8ClwK/vxZ+PkUeOpaaNlU7BqKyACnxEtE+p9EOUz5OPzr0/Dx\nO2HIeHjocvjp/vDIFbBpZbFrKCIDVEFuoCoiUhRmsM9Jflj2Ajz1c3jy5/D0dXDgeTB2GqSS/g+6\nU8nI0O4vT0an0+PDJviO/fGyYu+diJQgJV4iMjCMner/E/LdN3ziNedWf2f87sTKIJYIQxwsBlvf\ng7l/hI/8GkZMKkzdRaTfUOIlIgPLbnvDqT+FE6/0fb6iiVXHeBnEuuiJ8cq9cN9lcP1x0PgNOPoy\niOujVER6Rp8WIjIwVdT5YUdNOh32OBr+8lV49CpYeL/vyD98v96vo4j0O+pcLyKyo2p2g3N+C+fc\nDOuX+tavx38C7cli10xE+jglXiIiO2v/j8Dnn4WJH4KZ/w6/ORFWLyx2rUSkD1PiJSKyK2qGwbk3\nwzm/g/Vvw/XHwuM/VeuXiOSkxEtEpDfsfyb867Owz8kw80qYcZJav0RkG0q8RER6S22Dv2XF2TPg\nvTd9368nfqbWLxHpoMRLRKQ3mcHks3zfr31O8nfKv+l4eObXsHYxOFfsGopIEel2EiIi+VA7HM79\nPSy4C2ZdDQ98w5cP3h3ed4If9jxu525pISIlS4mXiEi+mMEBZ/th3VuweKYf5t0Bs2f4m7WOOwLe\nd7xPxEYe4NcRkX5LiZeISCEMGQ+H/pMfkq2w9Fl4YyYsfsR3xp95JdSOgL2P94nYXtP9/cJEpF9R\n4iUiUmiJctjzWD+ccAVsWglvPOpbw157AOb+ATAYfwwccA5MOgOqBhe50iLSG5R4iYgUW91ImPJx\nP6Ta4Z058PqDMP9P8H9f8n9PNOEkOPBcmPBBKKssdo1FZCcp8RIR6UticRg71Q+N34J3XoL5d/pO\n+gvvg4p62O90OPAcGH+sX15ESoYSLxGRvsoMxhzih5Ougjf/7lvBXrkH5twCtSP9rSsOPAdGTVHH\nfJESoMRLRKQUxOKw9wf88OGf+L5g8+6E526AZ66D3SbAAedQuXX3YtdURLqhxEtEpNSUVfm/KNr/\nTNi6zreAzbsTZv0nRwAsnwEHnQf7fxSqhxa7tiISoTvXi4iUsqohMPVi+NT9cNnLvLHXJ6FlE9z/\nFfjxPnDbBfDq/0Gypdg1FRHU4iUi0n8MGsvS3c9i7/f/AlbOg7m3+Y75C++DysEw+aNw0Pkw9lD1\nBxMpEiVeIiL9jRmMOsgPJ/4HLPmbT8Lm/NHfMX/oXnDgef72FEP3KnZtRQYUJV4iIv1ZPAETTvRD\n80Z/2XHebf7/I2f9F4w73P8ycvcjYfgkv7yI5I3eYSIiA0VlPRx8gR82LPP/GTnvdvjr1/38shp/\n64qxh8K4w/xjzbDi1lmkn1HiJSIyEA0aC8f+GxxzGax/G5Y+D8ueh2XPwVO/gFTSLzdkz0wSNvZQ\nGDFZrWIiu0DvHhGRgczM/4H3kPH+RqwArVtgxVyfhC19DpbM8i1jAGXVMPrgkIhNgzHToH5UkSov\nUnqUeImISGfl1bDHkX4AcA42LPVJ2LLZPiF7+jpItfn59WPCHfan+WRs1BSoqC1e/UX6MCVeIiLS\nPTMYvLsfDjjbl7U1w8r5sHy2T8aWz/Yd9wEs5jvqj5nqh7HToGFf/a+kCEq8RERkZ5RVwrhD/ZC2\neS0sfzGTjL1yD7x4s59XXusvUaaTsTFTYdCY4tRdpIiUeImISO+oGQb7nOQH8Jco31uSaRFbNrvz\nJcq6USEJO8Q/jj4YKgcVr/4iBaDES0RE8sMMdtvbDwed58uSLbByASx/wSdjy1/wd9b3K8CwfTon\nYyMmQ6K8aLsg0tuUeImISOEkKmDsVD9wiS/bug7eeQmWveATscUPw9w/+HnxCmiY6PuXDRoLg8b5\nx8Hj/HhNg/7+SEqKEi8RESmuqiGw9wf8AOFXlMsylyfXLIJ33/C3tWht6rxuvCKSiI2FQT5BG7R+\nA7QfDfGygu+OSHfylniZ2QzgVGC1c25yKBsK3A6MB94CznXOrctXHUREpASZ+URq8DjY/8xMuXPQ\nvN4nZeuX+scN/8hMv/4INK0E4GCAhT+AiR+C/U71SV1ZVVF2RyQqny1evwOuBf4nUvZNYKZz7moz\n+2aY/kYe6yAiIv2FmW8dqxoCIw/IvUyyBTYuZ8HM25mceBsW3e8vW5bVwIQTYL/T/f9WqhO/FEne\nEi/n3GNmNj6r+AygMYzfDMxCiZeIiPSWRAUM3Yu1DUdC47egvQ3eesLfY2zhff4WF7Ey2KsR9jvN\nt4jVNhS71jKAmHMufxv3idd9kUuN651zg8O4AevS0znWvYTQ87KhoWHqHXfckbd6loqmpiZqa3U3\naFAs0hSHDMXCUxy8nHFwKeo3vsawtU/TsOYZqppX4oixYdB+rGk4krXDDqelov911tcx4RUyDtOn\nT3/BOTct17yiJV5hep1zbsj2tjNx4kS3aNGivNWzVMyaNYvGxsZiV6NPUCw8xSFDsfAUB2+7cXAO\nVi2AV+/zrWGrX/blsYS/2WtFXXisjTzW5Ziu83+xlKjyfcjKqiBRmTVe7VviipTQ6ZjwChkHM+sy\n8Sr0rxpXmdko59wKMxsFrC7w84uIiPgkaOQBfpj+Lf+rydcfgqbV/peTLU3QuglawrBpRaSsCVz7\njj5h54Ssaqh/7tFT/H9bjjzAJ3DS7xU68boXuAi4OjzeU+DnFxER2dZue8Nun+vZss5BsjmTiLVu\n8dNtW/x/WLalp7f6Ibl12/KmVZ3vV2YxGDYxk4iNTidjNfnbZymKfN5O4o/4jvTDzGwZ8D18wnWH\nmf0T8DZwbr6eX0REJC/MMi1X7ELHfOdg4zuwYg68M8c/Lp4Jc/8Ynifm7+Q/6qBMMjZ8P/+rTilZ\n+fxV4/ldzDo+X88pIiJSMsz8H4UPGgP7fjhTvnFF52Rsyd9h3u2Z+bUj/d38G/aF4fv6x4Z9oXpo\n4fdBdpjuXC8iItKX1I/yw8RTMmWbVsKKubBmob+T/+pX4aVboG1zZpma4ZmErGGibx1r2Lfw9Zdu\nKfESERHp6+pG+mGfD2bKUinYuNwnYmtezSRlc2/zfc+CI8uHwLKpmR8TjDwQhu4FsXgRdkSUeImI\niJSiWCzz10oTTsiUp/uOrVkIaxby3txHGNW0Cp76O6Ta/DJl1TBi/87J2PBJ+mVlASjxEhER6U+i\nfcfedzyLWvZnVGMjJFth7SJYOd8PK+bB/Ltg9oywXgx2e59PxEZMDo/7Q92ofndT2WJS4iUiIjIQ\nJMozLVxpzsH6f2SSsZXzYelzsOCuzDJVQ2HkZJ+MjZjsk7GGfaGssvD70A8o8RIRERmozGDIHn7Y\n79RM+db1sOplf3f/VQtg5QKY/Vt/TzIAi8OwCaFlLCRkwyf51rFYrDj7UiKUeImIiEhnVYNh/NF+\nSEu1w3tLfKtYOilb+iws+FNmmXg5DBoHg3ePDCGxG7y7/+XlAE/MlHiJiIjI9sVCK9ewCTD5o5ny\nretg1Suw+hV/2TI9LLwftqztvI14RfhBQCQxqx8L9aN9n7S60f3+EqYSLxEREdl5VUO2bR1La90M\n65eGZOztzonZinnbJmYA1btB/Rg/DBrjk7L0dP1oP5RV5X+/8kSJl4iIiORHeY2/u/7wLm7k2rrZ\n36l/4zJ/C4wNy/29yTYuhw1LYekzvkUtW8UgqB7ik76qof6u/VVD/XR6vHpI5zLn8ruvPaTES0RE\nRIqjvAaGvc8PXcmVnG1eA1vfgy3v+cTsvTdgyzpo2dDlZt5PDJ4bDJWDuhgG+75t2eUV9VBRB+W1\nvdI/TYmXiIiI9F09Sc7S2pPQvD4kZCEpC+P/WDiHPUYM8fObN/hh7arMeNuW7WzcMklYZX0344O6\n3YoSLxEREekf4gmoGeaHLG+2zmKPxsau1022QsvGkIit97fUaN7gy1o2QfPGyHgo37LW/9IzXZ5s\n3m4VlXiJiIiIJMohkTtp67F08nZlQ9dPs/NbFxEREZEO6eStGwP7LmYiIiIiBaTES0RERKRAlHiJ\niIiIFIgSLxEREZECUeIlIiIiUiBKvEREREQKRImXiIiISIEo8RIREREpEN1AVUREpJc559jc2s6m\n5jY2NSfZuDU8NrexsTnJlpYkbe0p2todbe0pkikXplMk2x2t4TGZStGa9I/p6VQK2p2jPeVIhceO\nwTlSHY/QnnK0tLRQ8dTMTvUz61zfrEkAUg4cDufAgX90Loy7jrJUWMBF9h0y04TlfJnrNJ2uS9yM\nmBmxmBGPGTHDT5ufNiOU+3npbaRcZl+dc6Scj016PB0f5yCZTBJ/9AHMDAvPa+a37acz5ZAp79jf\nsD0HpFKuU0zSsUq5rB3PoSQSry1Jx9yl6xlRX8mw2nIScTXUiYhIzzjnaGpJsmFrW8ewMTKeKUvS\n7ro+a+ZKTgBakqmOxGpTi99OU0uS9tR2zsBBImYk4kZZPBYGIxGLUZ6IkYhZpiweIx4Sk/JYzCcp\nkYQkHguJS3rcjHgMVq5cyaiRmb+wcVmZQa5ddkDMwNIJiHVOTNLlsZDBRcuisYomeJZeNiugzhFJ\nFjsnT+1hOpVOMsM4HYlZJkHrGI91LrMQj2XLljJ27LiQSLqsRHLbJJMwnU7O0vGIdUrY0tMhFqHs\nW9293ts7IPqC1VscZ1z3JOB3fFhtBSPqK8NQwcgwPry+gpGDKhlRV8mgqjIgk6mmx6HrzDvlHE3N\nSTa1JGlq9m+c9LeVplC2qSUZmW5jc0s7dZUJGuoqGF5XQUNdBQ11lZ2mK8viO7Xf7Sn/YbG5xT/f\n8k0pmtvad3p7IiKF4pxvtdnS0s6Wtna2tCTZ0trO5pYkm1vb2dLqP9e2tLT7x1ZfvrklyeYW/5gu\na02mOk6q0RNu9OQfi3U+KW7YuJUrZ8/qSKq6S4LiMaO+MkF9VRmJmOVcpsu1HZQnYtRXljF6cCV1\nlXXUVSaoryyjrjJBXWUZ9VX+MV1eX5mguiJBeUiozHI/Z2+ZNWsdjY0H5vU5SsGsWatpbJxUkOcq\n+cRrdE2MGz85jZUbm1m9sZlVG1tYubGZZeu28MLb77FuS1vB6lJZFqO2Iv2GSlBVFmfFhmbmLtvA\nu5tbcn5zqK9MMLy+kobaCobXV9BQW0EiHutIqDY1Z5KrzS2ZxG9rW/s22/rOUw8welAVezXUsHdD\nLXs11LDXMP84alBl3t/AIlL6nHO0hctWbUlHS3s7za0ptrb5hGhrWztbW9vDdDvN4TFdtrU1TLf5\nJGlrazubW5Mdj1vC/J62+ABUlcWpqUhQUxGnptw/Dq4uZ+yQBGVx85d3XOdLPqmO8fTlHtexXPtW\nY/yYQQyqSjCoqqzTUJ81XVuR0GenFExJJF7lcThh0ogu5ze3tbNmUwurIknZpuY2jGgTKB3j/rHz\nmyz9ram2widU/rGs03RtZYKybi5zJttTvLe5ldWbWlgThtWbmsOjn37pH+tZvamZ9pSjrrKMmoo4\ntRVl1FbEGVZbzh67VVNXmaCm3D9fbUXmuRcseIXK4buzZM1mlqxt4o7ZS9nSmknOqsri7Dmsxidj\nDbXs3VDDnsNqGFpTTn1VGbXlCWJdfJsTKaS2dn+Sb27zJ/zmZOak3hwGf4LPLNdx0m9rp7m1PWud\nFBs3buWal5/M2V/DSLeUdL50UlWWYHB15gScHq+vKmNw1sm5t7o4pFKuowUo3fKTbglKJyxbWn1C\n05pMdfT7aU0/Jn2/oNb2FG0d8x2tSb/Mug1bqXzpMV8eEqv0NjqSrfaeJ0TZKstiVJXFqSqLU12R\noKY8TlV5nJH1lVSV+6SpuiJOdXmc6vIE1TnKaitCeUWCmgr/BTbey59Ns2bNorHx4F7dpkhvKInE\na3sqy+KMG1rNuKHVRa1HIh5jeH0lw+sr87L92vdeo7Fxn45p5xyrNrawZE0Tb6zdzJI1TSxZs5m5\ny9Zz//wV27S+xQzqKtMnFv8t0Dd7lzGo2jd/p086lWVxyhMxKuK+n0HHEJmuiMc7xtMfmulv0p1P\nFo5kx0mj87xku8t5ORi37aXgzCViWLA6Sdsrq7rtxMk2cyDaYTJ6Ys5cm+9cHjfrtP8ViXinOFSE\n8b6e0GZ3NG1JpjpO1G3hsTWZ6lTe2jHe3jHeElmmJTK/pW3bbbQk22lJptjakSSlOpKq5A60hKTF\nzH+5qCqPUxlO/OnxusoEya1GXWUi7G+0D0dm3LeMpDr6cbzbtIVX3mlj/da2Tl9icqmt8O+PqvJ4\nR0yjx2vkYZvjsj3lOlqDmttSO7zf5Qnf96c83QcoYR3j6XllcaOuLIFrNkYNqyER98tk9x0qi8dI\nxGOUhz5DZWG8KiRJVWU+ptUhoUrHubo8TmUi3uePdZG+rl8kXgOVmTFyUCUjB1Vy1PuGdZrX3NbO\n2+9u4a13N7NhSxsbm7ftULqxOcmqjU0dZS3JHTshRKV/hbIr36R32IuzC/dc21EWTnIVZXHK4r5z\na6ZDZuSRTCfVjj4r+MfoL2cyiULuX86kE4qtzc0knnyk0y+bnNv2F087kedsV6ckPJKYV5RlEtOh\nNeVUDfYn8nSy1NFiUh6nIp1ARcor0if9dGKViFNZ7rfZ3eUg38Jx+E7vT2syxcbmNtZv6fxeWb+l\nlQ1bfcfs9VtbaW5r72hBg2hrumVNZ+bHzHxrUGjpSbf81FRkWoU6pssyrUMViR1vCfJxmLrTcRCR\n/FLi1U9VlsWZOLKOiSPrerxOc1s7m5r9Caa5rb3LVpHWZIqWaItIaPVIuczJOPubdeYbd4zyRGY6\nEct0LN321zCW4yTmR154YTbTpk3rVP9Ov56J/P4oXR5NaLKnfb+Q9LxMWXvKRfbRt+Lkav1pzYpH\nKitJyvRFcZ0SrI7lnIPIr2OMTGfhaKLW0SIXllm9aiVjRg/v9EumdEtd9BdOHY8G8XSSmMi0mGzT\nmpmIUR5p0SzFVr4dVZ6IMay2gmG1FcWuioj0Y0q8pEO6VaKhru+feN5dHGfymEHFrkbR6ddKIiKl\nRTfEEhERESkQJV4iIiIiBaLES0RERKRAlHiJiIiIFEhREi8zO9nMFpnZYjP7ZjHqICIiIlJoBU+8\nzCwOXAecAkwCzjezwvx5koiIiEgRFaPF6zBgsXNuiXOuFbgNOKMI9RAREREpKEv/tUXBntDsbOBk\n59xnwvQngMOdc1/IWu4S4BKAhoaGqXfccUdB69kXNTU1UVtbW+xq9AmKhac4ZCgWnuLgKQ4ZioVX\nyDhMnz79BefctFzz+uwNVJ1zNwA3AEycONE1NjYWt0J9gP8rkMZiV6NPUCw8xSFDsfAUB09xyFAs\nvL4Sh2JcalwOjItMjw1lIiIiIv1aMS41JoDXgOPxCdfzwMedcy93s84mYFFhatinDQPWFrsSfYRi\n4SkOGYqFpzh4ikOGYuEVMg57OOcacs0o+KVG51zSzL4APAjEgRndJV3Boq6ulQ4kZjZbcfAUC09x\nyFAsPMXBUxwyFAuvr8ShKH28nHN/Af5SjOcWERERKRbduV5ERESkQEol8bqh2BXoIxSHDMXCUxwy\nFAtPcfAUhwzFwusTcSh453oRERGRgapUWrxERERESp4SLxEREZECyWviZWYzzGy1mS3IKj/CzG40\nsxPN7AUzmx8ePxDmV5vZ/Wa20MxeNrOrs9YfZWYPmdkUM3s6LDPPzM6LLLOnmT1rZovN7HYzK8/n\nvnZnF+JQZ2ZzIsNaM7smsn5JxSHKzMaZ2d/M7JVQ70sj89Jx2S0s02Rm1+bYxjfN7AIz+7ewnXlm\nNtPM9ogsc5GZvR6Giwq1fzuiJ7EI4wdGXuf5ZlYZWa4kY7Grx4GZfd/MlppZU45tl8z7oxfiUG5m\nN5jZa+Y/N8/qhAb7AAARgUlEQVSKzCuZOIS69CQWOT8zwzID6ZjoLg795piIMrNKM3vOzOaGel8Z\nmfcxM7vc/GfhvBCXp8zsoKxt/NrMjjazH4XYzDOzP5vZ4Mgy3wr7vsjMPtirO+Gcy9sAHAccAizI\nKr8SOAs4GBgdyiYDy8N4NTA9jJcDjwOnRNb/FPAVYB9gQigbDawABofpO4CPhfFfA5/L577mIw45\ntvMCcFypxiFrX0YBh4TxOvxNdSdlxaUGOAb4F+DaHNv4G9AATAeqQ9nngNvD+FBgSXgcEsaHFHvf\ndzIWCWAecFAo3w2Il3osdvU4AI4I22jKse2SeX/0QhyuBK4K4zFgWCnGYQdi0eVn5gA7JrqLQ785\nJrLiYkBtGC8DngWOCNM3A1OBowifb8ApwLNZ25iDv4/oSUAilP0A+EEYnwTMBSqAPYE3iHze7vI+\nFCBI49k24XgCGJQjmO8BFTm28XPgnyPTt6cPwKzl5gITwrbWRgJ6JPBgkQ+WXYpDeIMsJfwgolTj\n0E187gFOzBUX4GK2PdHUA0/m2M7B6XLgfOD6yLzrgfOLva87EwvgQ8AtXSzfb2Kxo8dBZF6uk2zJ\nvj924v2wFKjpYlslG4ftxSKUdfWZOWCOiVxx6M/HRKS+1cCLwOGhznOJnCPDMkPonJDuB9yRY1tn\nAreG8W8B34rMexA4srfqXfA+XmY2DGhzzm3ImnUW8KJzriVr+cHAacDMMB0HJjrnXsla7jB869gb\n+NaA9c65ZJi9DBjT2/uyK3Y0DsDH8K0XLqzfL+IAYGbj8UnCs93EJdsJhGMiyz8Bfw3jY/AfPml9\ncv+juonFPoAzswfN7EUz+3pktX4Ri508DrraVsm+P3Y0DpHLI/8Rjo07zWxEmFeycYAex6Krz8zs\nbZVsLHY0Dv35mAC/D2Y2B1gNPOycexYfn7npc2RE9HMQfAvYAzk2+2kK9HlZjM71JwEPRQvMbH98\nM99ns8oTwB+BXzjnloTiw/FNi9HlRgG/Bz7lnEvlqd69rcdxCD6Gj0Vav4iDmdUCdwFfds5tJEdc\nunAynd9MmNmFwDTgR71dz0LYTiwS+MtMF4THM83s+DCv5GOxC8dBV0ry/bGTcUgAY4GnnHOHAE8D\nPw7zSjIO0LNYbOczM1tJxmIn49Avj4k051y7c24Kfh8PM7PJ5P4cnI5PvL4RKf4gWYmXmV0OJIFb\n81nvtGIkXp2yTTMbC/wZ+KRz7o2sZW8AXnfOXdPN+vXA/cDlzrlnQvG7wOCQuIF/cZb36l7suh7H\nIXQMTDjnXuhm/ZKLg5mV4T9QbnXO3R2Ku/o2ku0w4LnItk4ALgdOj3zzXQ6Mi6zTp/Y/qgexWAY8\n5pxb65zbgv/LrUPCvJKOxS4eB10puffHLsThXWALkF7nTjLHRsnFAXoWi+2cO3IpuVjsQhz63TGR\ni3NuPb5/68lkJaRmdiBwE3CGc+7dUFaN78P2TmS5i4FTgQsirWX5/bwswDXY8YS+TWRdgwUGh+mP\n5ljvKvwBF8sqfwqoC+Pl+EssX86x/p107hj4r/ne13zEIcy/GriyP8QhUi8D/ge4Jqss1zX6i4n0\naQH2B26LTB+Mbx6fkLXeUOBN/DX+IWF8aLH3fWdiEer/Ir5PQwJ4BPhwqcdiV46DrHlNWdMl9f7Y\n1TgAtwEfiMy/sxTj0NNYsJ3PzIFyTHQXh/50TGTVq4HMDwCq8D++OwN4IrLM7sBi4KisdT8MXB2Z\nPhl4BWjIWm5/OneuX0KpdK7HXxpbAbThv7F/A/hdZP53gM34Xxikh+H47NIBr0bKPxMC/mhk/QvD\ntqPrTwnz9sK3AiwOB9A2nfYLeKDsVBwi85cA+2YdeCUXh6yYHBNe43mROn83Gpew3Fv4DqNNIXaT\ngK8CF0eWeQRYFdnOvZF5nw77vhjfjF70fd+FWFwIvAwsAH4Yyko6FrtyHITyH4bpVHi8ohTfH70Q\nhz2Ax8L6M/EnnpKLQ09jQTefmQPpmNhOHPrNMZEVlwOBl8J+LQgxORu4IrLMTcC6yD7NDuXXAo2R\n5Rbj+3Kll/t1ZN7l+C+xi4jcVaE3hoL+ZZCZfQdY7Jy7bSfXvxAY65y7ersL92GKQ249jYuZPYxv\nVl9RmJoV3kCOhd4fnuKQoVh4ikNuZnYTcJPLXCrtarkXgcOdc22FqVkX9Shk4iUiIiIykOkvg0RE\nREQKRImXiIiISIEo8RIREREpECVeIiIiIgWixEtERESkQJR4iYiIiBSIEi8RERGRAlHiJSIiIlIg\nSrxERERECkSJl4gMKGZWa2afL3Y9RGRgUuIlfYqZtZvZnMgwfie38+2dWGeWmU3bzjJNO1OfHXle\nMxtvZgt2cls51zWzaWb2i12pZ2RbXzWzheH1ed7MPhnKTzWzl8xsrpm9YmafDeUTwz7OMbNXzeyG\nUN5oZhuyXu8TunjOb5rZBTnKTzaz5yL1ud3Mdt/OLnwfeD2yjQozeySsf56Z3WRmk3Y2PjvCzEaa\n2W1m9oaZvWBmfzGzfbpZvuP1DfG7bzvbv9jMru3teufDrhz3xVbKdZfCSxS7AiJZtjrnpvTCdr4N\n/GcvbKdfcM7NBmbv6nbM7F+AE4HDnHMbzaweONPMyoAbQvkyM6sAxofVfgH8zDl3T9jGAZFNPu6c\nO7UHT/1B4NysukwGfgmc7px7NZSdHp73H1nLJpxzSTOrBp5wzj0UmX0wQOS4u70H9dllZmbAn4Gb\nnXMfC2UHASOA1wpRh1JnZnHnXHux69FTpVZfyQ+1eEmfZ2aVZvZbM5sfWlSmh/KLzexuM3vAzF43\nsx+G8quBqtCCcWsouzC0jMwxs+vNLL6d5zw/PN8CM/tB1rzvh1adZ8xsRCj7nZn9wsyeMrMlZnZ2\nKB9lZo+F511gZsf24r7fE1qSXjez7+VYd6+wzqHR1hEzu8LMZoR1l5jZl0J5jZndH/ZtgZmdl6NK\n3wY+55zbCOCc2+icuxmow3+RezeUtzjnFoV1RgHL0htwzs3fwRjUA+XOuTVZs74B/Gc66Qrbvtc5\n91hYb5aZXWNms4FLzew04G/A5aGFa4SZDQduAQ4Nr9HeFmmBDC1qL4aYzAxlQ83sf81sXjgGDsxR\n57iZ/ch8i+A8C61/WaYDbc65X0fqP9c597h5Pwqvw/wuXovo8x1mZk+H1/spM5sYmT1uO8fJOWb2\n0zB+qZktCeN7mdmT4fi5O5SdYWZbzaw8HJtLzGy4mb0Q5h9kZs5Cq6P5lrzqrOcbb2aPh7i+aGZH\n5ahTp5Y6M7vPzBrDeJOZ/cTM5gJHmtl3Q5wXmNkNZmY5tlcbeR/NM7OzQnnO93l4jh+Z2cvhWDks\n8n45vYuXIWFmt5pv1f1Ter/N7C0z+4GZvQic08W6MpA45zRo6DMD0A7MCcOfQ9lXgBlhfF98a0Yl\ncDGwBBgUpt8GxoXlmiLb3A/4P6AsTP838Mkczz0LmAaMDs/RgE8mHgU+EpZxwGlh/IfAd8L474A7\n8V9mJgGLI3W/PIzHgbounndRZL9fARb0YN9XALsBVcCCUPfxYXwi8BJwUFi3EbgvjF8BPAVUAMPw\nyVIZcBZwY6Reg7LqWQ+s6+a1uwlYDfwRuACIhfJPARuAvwKXAYMjddoQ2e85wN45tvtR4N9zlL+Y\n3r8u6jML+O/I9BDAwvhngZ9kxybrOGgAlgJ7hvKh4fGXwPfC+AeAOTme+5LIsVGBb23cM2uZL+Fb\nAnPV/Szg4XDMjAiv+6j065vjNa0HEmH8BOCuMJ7zOMl6rpHA82H8T8DzwBjgIuC/8O+BJWH+j8P8\no4H3A38M5S+HOnwhzL8A2AN4Ose+VQOVYXwCMDuMR/ftYuDayDr3AY2R9+C5kXlDI+O/J7w/s57z\nB8A1WcfC9t7np4TxPwMP4d8jB3Xxeo8P6xwdpmcAXw3jbwFf743PRw39Y1CLl/Q1W51zU8JwZig7\nBt8qgXNuIT7BSveDmemc2+Cca8YnLHvk2ObxwFTgeTObE6b36qYOhwKznHNrnHNJ4FbguDCvFX8S\nAHiBzOU0gP91zqWcc6/gT5bgT0KfMrMrgAOcc5u6eM4L0vsNfChS3t2+P+yce9c5txW4OywL/kRy\nT9jm3C6e737nW6XW4pOlEcB84MTw7fxY59yGLtbNyTn3GXxsnwO+ij/54Jz7LT75vROfLDxj/lIk\n+EuNUyLDGzk2fTI+aeuSme0WWqxeM7OvRmZFLxuOBu41s8fxidH+29mlI4DHnHNvhv14L5Qfgz/B\n45x7FNgttMpFnQR8Mhxvz+ITnwnbeb6oY/BJTbtzbhXwd/xx2ZVBwJ3m+xn9jM771tVxQtiHlUCt\nmdUB44A/4I/3Y/GvTxJ4w8z2Aw4DfhqdHzbzFD4ZOw5/iT97flQZcKOZzccfEzvan64duCsyPd3M\nng3b+wC5X9cTgOsi+7yO7b/PHwjj84G/O+fawvj4Luq11Dn3ZBi/hc5xLsjlaykNSryk1LVExtvJ\n3W/R8P1o0if3ic65K3by+dqcc66L54vWxQCcv+x1HLAc+J2Fjui9xHUxvQH/Tf4YurZN3JxzrwGH\n4E8uV5nZdztt3F9ebDKzLpNW59x859zP8P3AzoqUv+Ocm+GcOwNIApO73bPODsMnc9leDvUlJBZT\n8P3MaiPLbI6MXwtc55w7Fp8YVu5AHXaUAV+MHHN7us79ysDXf2ovPd9/AH9zzk0GTqPzvnV1nEQ9\nhW+ZXIRPlo4FjgTSicRjwClAG/AI/tg6hkxi9VhYZw980n9Q1vyoy4BVYZlpQHmOZZJ0Pj9F96fZ\nhX5SZlaJb8E+2zl3AHAjvfO6Rt/nKcL7xTmXouu+0d3FeTMigRIvKQWP4y9dYP4XX7vjTxDdaTPf\n4RtgJnB26M+T7qOTq2Us7Tng/WY2zHxfsPPxLQ47LDzPKufcjfhLcYfs4Ca62/cTw75UAR8hc5Js\nBc7Et7h8fAfqOhrY4py7BfhRF3X9L+C6dAtP6DvzyfDYGFluCr51Lt1PqiyMj8S3/izvYZ32Bxa6\n3B2Sf4jvr7VfpKw6x3JpQ4B0P7GLevD0zwDHmdmeoS5DQ3n0NWkE1oakNOpB4HOR/d7HzGqylnkU\nqDCzS9IFZnag+X6AjwPnme8r1oBP3nMln2mDyMT04qx5XR0nUY/jk9HH8JeopwMtkVbPx4Ev4y8d\nrsG/hhPxly7T8y8EXg/JyXv4ltsnuqjrirDcJ/CXU7O9BUwxs5iZjcMn37mkk6y1ZlYLnN3Fcg8D\nHbcQMbMh9OL7PNjdzI4M4x8n976L6FeNUhL+G/hVuJSQBC52zrXk6EMbdQMwz8xedM5dYGbfAR4y\nsxj+W/vnCYlBRAJ/sllhZt/Ed8Q2/GW5e3ay7o3A18ysDWgCdrTFq7t9fw5/yWUscItzbraF2284\n5zab2anAw+ZvgZGdGORyAPAjM0vhY/S5HMv8Ct+i9HzYpzbgJ/g4fd3Mrge24r/hXxzWOQn4uZk1\nh+mvOedWmtm+wLHhclzaVc65P0WmTyFzyacT59x8M7sU+J+QCK7Ft/Rt04E8+HfgT2b2Hj7pGd/F\ncuntrwlJ0d3huFmNb8m7AphhZvOALeRO4m4K238xdPZeg096ott3ZnYmcI2ZfQNoxiccX8aftI8E\n5uJbTr4eYtZVnX8I3ByO8/uz5m1znORY/3H8ZcbHnHPtZrYUWBiZ/yz+cvRjYXoeMDLdKuSceyvs\nZ3r+E8DYcEkv/WvTac657+KP6btC6+8D5G4NehJ4E9994FV8f75tOOfWm9mN+ARwJf7SPuE5/yUs\n82vgKvwXhgX4Ft4rnXN378r7PHxRuck5l+4asAj4vJnNCPX+VU+3JQNLuqOpyIAW+hwtBibvaN+m\nYjCzi/Ensi8Uuy75ZGYP438IsaLYdRER6Q261CgDnvlbB8zB/wKuzyddA4lz7kQlXSLSn6jFS0RE\nRKRA1OIlIiIiUiBKvEREREQKRImXiIiISIEo8RIREREpECVeIiIiIgWixEtERESkQP4/yp3kGSmI\n9RYAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NveSf0Uw10Ca",
        "outputId": "2bc3cf25-6e48-41e8-bc90-78ce1cd6ca63",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "grouped_per_day[\"letality_rate_2\"].plot()\n",
        "plt.title(\"Mortes por casos recuperados ou mortos no mundo todo\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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GmAG8bofPB87vlIQqYEVHhPOb740i58AhXli+099xlOr2vOpDF5FwEVkL7AcW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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N_mp7BLc2oLS",
        "outputId": "8630d55a-4e28-4435-e19d-f8e51e4b7ec5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "grouped_per_day[\"letality_rate_1\"].plot()\n",
        "plt.title(\"Mortes por casos confirmados no mundo todo\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5owpjjMdHbb2ytYJup+Hi+daYMFkpsdqGrkaExzYcYFJ6vA6TOwqE5NWR8DBh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\nI4QmdKWUGiH+P1xqD3MN9y76AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K0dgl3NN2qGq"
      },
      "source": [],
      "execution_count": null,
      "outputs": []
    }
  ]
}