The_ways_to_get_the_STOCK_data.ipynb

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      "authorship_tag": "ABX9TyMl7JPUP6Xd21DKoS393XXa",
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      "cell_type": "markdown",
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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/YigitBCesur/Finance-and-Trading/blob/main/The_ways_to_get_the_STOCK_data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    },
    {
      "cell_type": "code",
      "source": [
        "! pip install yfinance\n",
        "! pip install --upgrade pandas_datareader"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-4ljU4TGJnJN",
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      },
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      "outputs": [
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          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting yfinance\n",
            "  Downloading yfinance-0.1.85-py2.py3-none-any.whl (29 kB)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.11)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.21.6)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
            "Collecting requests>=2.26\n",
            "  Downloading requests-2.28.1-py3-none-any.whl (62 kB)\n",
            "\u001b[K     |████████████████████████████████| 62 kB 1.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: appdirs>=1.4.4 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.4.4)\n",
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            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2022.6)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24.0->yfinance) (1.15.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2022.9.24)\n",
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            "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.1.1)\n",
            "Installing collected packages: requests, yfinance\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "Successfully installed requests-2.28.1 yfinance-0.1.85\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pandas_datareader in /usr/local/lib/python3.7/dist-packages (0.9.0)\n",
            "Collecting pandas_datareader\n",
            "  Downloading pandas_datareader-0.10.0-py3-none-any.whl (109 kB)\n",
            "\u001b[K     |████████████████████████████████| 109 kB 7.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: lxml in /usr/local/lib/python3.7/dist-packages (from pandas_datareader) (4.9.1)\n",
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            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.23->pandas_datareader) (1.21.6)\n",
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            "Installing collected packages: pandas-datareader\n",
            "  Attempting uninstall: pandas-datareader\n",
            "    Found existing installation: pandas-datareader 0.9.0\n",
            "    Uninstalling pandas-datareader-0.9.0:\n",
            "      Successfully uninstalled pandas-datareader-0.9.0\n",
            "Successfully installed pandas-datareader-0.10.0\n"
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    {
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      "execution_count": null,
      "metadata": {
        "id": "1WMS2nt1I948"
      },
      "outputs": [],
      "source": [
        "#import yfinance as yf\n",
        "from pandas_datareader.data import DataReader"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**# by YAHOO FINANCE **"
      ],
      "metadata": {
        "id": "9j7TmlrLLHld"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data= yf.download('AAPL', '2019-01-01', '2109-01-31')\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "yZ1203mbKCkL",
        "outputId": "c9592da9-cf33-4bd9-bd39-fb7bfce449ba"
      },
      "execution_count": null,
      "outputs": [
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          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
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          "metadata": {},
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    {
      "cell_type": "markdown",
      "source": [
        "**# by PANDAS**"
      ],
      "metadata": {
        "id": "htP7EViWLBE4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data= DataReader (name='AAPL', data_source='yahoo', start='2019-01-01', end='2109-01-31')\n",
        "data"
      ],
      "metadata": {
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        "outputId": "bf7175f0-f8a7-4522-9c55-9d0cce640add"
      },
      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
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              "                  High         Low  ...       Volume   Adj Close\n",
              "Date                                ...                         \n",
              "2019-01-02   39.712502   38.557499  ...  148158800.0   38.105137\n",
              "2019-01-03   36.430000   35.500000  ...  365248800.0   34.309586\n",
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              "2022-11-09  138.550003  134.589996  ...   74917800.0  134.869995\n",
              "2022-11-10  146.869995  139.500000  ...  118854000.0  146.869995\n",
              "2022-11-11  150.009995  144.369995  ...   93903800.0  149.699997\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-01-02</th>\n",
              "      <td>39.712502</td>\n",
              "      <td>38.557499</td>\n",
              "      <td>38.722500</td>\n",
              "      <td>39.480000</td>\n",
              "      <td>148158800.0</td>\n",
              "      <td>38.105137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-03</th>\n",
              "      <td>36.430000</td>\n",
              "      <td>35.500000</td>\n",
              "      <td>35.994999</td>\n",
              "      <td>35.547501</td>\n",
              "      <td>365248800.0</td>\n",
              "      <td>34.309586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-04</th>\n",
              "      <td>37.137501</td>\n",
              "      <td>35.950001</td>\n",
              "      <td>36.132500</td>\n",
              "      <td>37.064999</td>\n",
              "      <td>234428400.0</td>\n",
              "      <td>35.774239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-07</th>\n",
              "      <td>37.207500</td>\n",
              "      <td>36.474998</td>\n",
              "      <td>37.174999</td>\n",
              "      <td>36.982498</td>\n",
              "      <td>219111200.0</td>\n",
              "      <td>35.694607</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-08</th>\n",
              "      <td>37.955002</td>\n",
              "      <td>37.130001</td>\n",
              "      <td>37.389999</td>\n",
              "      <td>37.687500</td>\n",
              "      <td>164101200.0</td>\n",
              "      <td>36.375057</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>2022-11-07</th>\n",
              "      <td>139.149994</td>\n",
              "      <td>135.669998</td>\n",
              "      <td>137.110001</td>\n",
              "      <td>138.919998</td>\n",
              "      <td>83374600.0</td>\n",
              "      <td>138.919998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-11-08</th>\n",
              "      <td>141.429993</td>\n",
              "      <td>137.490005</td>\n",
              "      <td>140.410004</td>\n",
              "      <td>139.500000</td>\n",
              "      <td>89908500.0</td>\n",
              "      <td>139.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-11-09</th>\n",
              "      <td>138.550003</td>\n",
              "      <td>134.589996</td>\n",
              "      <td>138.500000</td>\n",
              "      <td>134.869995</td>\n",
              "      <td>74917800.0</td>\n",
              "      <td>134.869995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-11-10</th>\n",
              "      <td>146.869995</td>\n",
              "      <td>139.500000</td>\n",
              "      <td>141.240005</td>\n",
              "      <td>146.869995</td>\n",
              "      <td>118854000.0</td>\n",
              "      <td>146.869995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-11-11</th>\n",
              "      <td>150.009995</td>\n",
              "      <td>144.369995</td>\n",
              "      <td>145.820007</td>\n",
              "      <td>149.699997</td>\n",
              "      <td>93903800.0</td>\n",
              "      <td>149.699997</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>975 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e615f0b5-4a74-4306-9546-b2625f7c961e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e615f0b5-4a74-4306-9546-b2625f7c961e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e615f0b5-4a74-4306-9546-b2625f7c961e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**# POLONIEX Api**\n",
        "[link text](https://docs.poloniex.com/#introduction)\n",
        "\n",
        "https://docs.poloniex.com/#public-endpoints-market-data\n",
        "\n",
        "\n",
        "API Methods:\n",
        "returnChartData"
      ],
      "metadata": {
        "id": "AJISToV0LfFF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "import json\n",
        "import pandas as pd\n",
        "\n",
        "\n",
        "\n",
        "# BITCOIN\n",
        "req= requests.get('https://poloniex.com/public?command=returnChartData&currencyPair=BTC_XMR&start=1405699200&end=9999999999&period=14400')\n",
        "data= json.loads(req.text)\n",
        "\n",
        "df=pd.DataFrame(data)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "_SQDUfqHMJBa",
        "outputId": "e4197ded-f5db-4e31-8b30-b09dcf4c2bea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              date      high  ...           quoteVolume       weightedAverage\n",
              "0    1661040000000  0.007117  ...  0.521088270000000000  0.007095445114644319\n",
              "1    1661054400000  0.007212  ...  0.942499960000000000  0.007171758468170018\n",
              "2    1661068800000  0.007182  ...  0.644868500000000000  0.007101328941605818\n",
              "3    1661083200000  0.007186  ...  0.470057670000000000  0.007126473210255090\n",
              "4    1661097600000  0.007299  ...  0.587891790000000000  0.007249019817354349\n",
              "..             ...       ...  ...                   ...                   ...\n",
              "495  1668168000000  0.007531  ...  0.886397500000000000  0.007470804811385287\n",
              "496  1668182400000  0.007532  ...  0.572828820000000000  0.007482345099151851\n",
              "497  1668196800000  0.007601  ...  0.712247290000000000  0.007539470754139177\n",
              "498  1668211200000  0.007650  ...  0.773768860000000000  0.007615349279886903\n",
              "499  1668225600000  0.007650  ...  0.058592900000000000  0.007599849112776423\n",
              "\n",
              "[500 rows x 8 columns]"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>open</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
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              "      <th>0</th>\n",
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              "      <td>0.007117</td>\n",
              "      <td>0.007026</td>\n",
              "      <td>0.007034</td>\n",
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              "      <td>73.440000000000000000</td>\n",
              "      <td>0.521088270000000000</td>\n",
              "      <td>0.007095445114644319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1661054400000</td>\n",
              "      <td>0.007212</td>\n",
              "      <td>0.007103</td>\n",
              "      <td>0.007107</td>\n",
              "      <td>0.007154</td>\n",
              "      <td>131.420000000000000000</td>\n",
              "      <td>0.942499960000000000</td>\n",
              "      <td>0.007171758468170018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1661068800000</td>\n",
              "      <td>0.007182</td>\n",
              "      <td>0.007062</td>\n",
              "      <td>0.007153</td>\n",
              "      <td>0.007062</td>\n",
              "      <td>90.810000000000000000</td>\n",
              "      <td>0.644868500000000000</td>\n",
              "      <td>0.007101328941605818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1661083200000</td>\n",
              "      <td>0.007186</td>\n",
              "      <td>0.007052</td>\n",
              "      <td>0.007062</td>\n",
              "      <td>0.007147</td>\n",
              "      <td>65.960000000000000000</td>\n",
              "      <td>0.470057670000000000</td>\n",
              "      <td>0.007126473210255090</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1661097600000</td>\n",
              "      <td>0.007299</td>\n",
              "      <td>0.007158</td>\n",
              "      <td>0.007158</td>\n",
              "      <td>0.007252</td>\n",
              "      <td>81.100000000000000000</td>\n",
              "      <td>0.587891790000000000</td>\n",
              "      <td>0.007249019817354349</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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>495</th>\n",
              "      <td>1668168000000</td>\n",
              "      <td>0.007531</td>\n",
              "      <td>0.007387</td>\n",
              "      <td>0.007393</td>\n",
              "      <td>0.007503</td>\n",
              "      <td>118.65</td>\n",
              "      <td>0.886397500000000000</td>\n",
              "      <td>0.007470804811385287</td>\n",
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              "    <tr>\n",
              "      <th>496</th>\n",
              "      <td>1668182400000</td>\n",
              "      <td>0.007532</td>\n",
              "      <td>0.007401</td>\n",
              "      <td>0.007506</td>\n",
              "      <td>0.007489</td>\n",
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              "      <td>0.572828820000000000</td>\n",
              "      <td>0.007482345099151851</td>\n",
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              "    <tr>\n",
              "      <th>497</th>\n",
              "      <td>1668196800000</td>\n",
              "      <td>0.007601</td>\n",
              "      <td>0.007485</td>\n",
              "      <td>0.007504</td>\n",
              "      <td>0.007510</td>\n",
              "      <td>94.47</td>\n",
              "      <td>0.712247290000000000</td>\n",
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              "    <tr>\n",
              "      <th>498</th>\n",
              "      <td>1668211200000</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.007463</td>\n",
              "      <td>0.007510</td>\n",
              "      <td>0.007640</td>\n",
              "      <td>101.61</td>\n",
              "      <td>0.773768860000000000</td>\n",
              "      <td>0.007615349279886903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>499</th>\n",
              "      <td>1668225600000</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.007538</td>\n",
              "      <td>0.007641</td>\n",
              "      <td>0.007560</td>\n",
              "      <td>7.71</td>\n",
              "      <td>0.058592900000000000</td>\n",
              "      <td>0.007599849112776423</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>500 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f2bc3f31-659c-4838-b986-392935e78b1d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f2bc3f31-659c-4838-b986-392935e78b1d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f2bc3f31-659c-4838-b986-392935e78b1d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**# QUANDL Api**\n",
        "\n",
        "\n",
        "https://rapidapi.com/zakutynsky/api/Quandl/details\n",
        "\n"
      ],
      "metadata": {
        "id": "bIMscV9bRCKb"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "X2TacnU4SL52"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### FINANCIAL MODELLING PREP"
      ],
      "metadata": {
        "id": "Fkh84gARBFPV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://site.financialmodelingprep.com/developer/docs/\n",
        "\n"
      ],
      "metadata": {
        "id": "9TSRI2R0Sk4v"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "jRmQwDyzSs_I"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "LAXNsoHtBH7d"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "X1HlY27zTOnG"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}