ImersaoDeDados_Aula02.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ImersaoDeDados_Aula02",
      "provenance": [],
      "authorship_tag": "ABX9TyPoIwe2ypKlV52MZJDSqPgb",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/nilmarlanna/imersao_de_dados/blob/main/ImersaoDeDados_Aula02.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ccC6-bQYY1pC"
      },
      "source": [
        "#Aula 02: Estatísticas, dados e distribuições "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j9BgNHhuQ9Wm"
      },
      "source": [
        "## Introdução\n",
        "\n",
        "Acesso a base de dados atraves: unique() e value_counts(). "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dujGlw9NRk6i"
      },
      "source": [
        "## Importando as bibliotecas a serem usadas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "dk9Rfq5DPGvZ",
        "outputId": "d32b3beb-271d-43fe-b4ab-4174a82c1ea3"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "\n",
        "dados = pd.read_csv(url_dados, compression = 'zip')\n",
        "dados"
      ],
      "execution_count": 9,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[23814 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T3OONC1wizml",
        "outputId": "223dfb99-2c07-48cf-c7f7-c8edf3c60e93"
      },
      "source": [
        "#Numero de linhas e colunas\n",
        "dados.shape"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(23814, 877)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HHW96LIajXj6",
        "outputId": "f8d688da-2e53-4b70-bdf5-6c5625261df2"
      },
      "source": [
        "#Ver apenas a coluna tratamento\n",
        "dados['tratamento']"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           com_droga\n",
              "1           com_droga\n",
              "2           com_droga\n",
              "3           com_droga\n",
              "4           com_droga\n",
              "             ...     \n",
              "23809       com_droga\n",
              "23810       com_droga\n",
              "23811    com_controle\n",
              "23812       com_droga\n",
              "23813       com_droga\n",
              "Name: tratamento, Length: 23814, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qcq9zzvqjcrc",
        "outputId": "297f7150-59b4-47e3-e2ff-a51eedc70f00"
      },
      "source": [
        "#Mostra os valores únicos(sem os repetidos)\n",
        "#Podemos ver que tratamento possui apenas dois tipos: com_droga e com_controle\n",
        "dados['tratamento'].unique()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['com_droga', 'com_controle'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i6WxWkP9khhO",
        "outputId": "288c07e5-358a-4fc1-abf7-b33beacd0822"
      },
      "source": [
        "#Tempo em horas \n",
        "dados['tempo'].unique()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([24, 72, 48])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K2LUJvf_n1fC",
        "outputId": "f06ccf0a-f6ff-4fd1-b858-16a2a34f9d72"
      },
      "source": [
        "dados['dose'].unique()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['D1', 'D2'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZU3EL0UPodIe",
        "outputId": "3cf6e123-aec2-464d-c575-5ff5b7f3f98b"
      },
      "source": [
        "#Os nomes das drogas foram preservadas para análise \n",
        "dados['droga'].unique()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['b68db1d53', 'df89a8e5a', '18bb41b2c', ..., '573c787a2',\n",
              "       'b2fe3eca7', 'dd4a96d16'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H8nU9thypFj1",
        "outputId": "32da7dc0-d86e-485a-a861-f96e0652391f"
      },
      "source": [
        "dados['g-0'].unique()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1.062 ,  0.0743,  0.628 , ...,  0.3942,  0.666 , -0.8598])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mmZmaRFDHijJ",
        "outputId": "920ed44f-7ef8-41a8-b7e5-eb1ba60ae9ef"
      },
      "source": [
        "dados['tratamento'].value_counts()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       21948\n",
              "com_controle     1866\n",
              "Name: tratamento, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g200f-uXOXHb",
        "outputId": "8110dbf6-60d6-430d-e0f4-f1172a23d569"
      },
      "source": [
        "dados['dose'].value_counts()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "D1    12147\n",
              "D2    11667\n",
              "Name: dose, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jM275LdzOdHe",
        "outputId": "e98f5174-b0b6-4c15-b59f-6c72270a0e0e"
      },
      "source": [
        "dados['tratamento'].value_counts(normalize = True)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       0.921643\n",
              "com_controle    0.078357\n",
              "Name: tratamento, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YVjviL6MOnHp",
        "outputId": "c9a4bd63-7229-45b0-cc14-976f8129c07b"
      },
      "source": [
        "dados['dose'].value_counts(normalize = True)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "D1    0.510078\n",
              "D2    0.489922\n",
              "Name: dose, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GyWAyqy_Qs8K"
      },
      "source": [
        ""
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "iPREv0HBRCRB",
        "outputId": "d65692bf-6f72-4e58-d5b4-8dedf024e291"
      },
      "source": [
        "dados_filtrados = dados[dados['g-0'] > 0]\n",
        "dados_filtrados.head()"
      ],
      "execution_count": 21,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>id_001bd861f</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>746ca1f5a</td>\n",
              "      <td>2.0440</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>5.9440</td>\n",
              "      <td>-2.1670</td>\n",
              "      <td>-4.0360</td>\n",
              "      <td>3.6950</td>\n",
              "      <td>1.4530</td>\n",
              "      <td>0.9724</td>\n",
              "      <td>-2.4380</td>\n",
              "      <td>5.1340</td>\n",
              "      <td>-4.6600</td>\n",
              "      <td>5.7960</td>\n",
              "      <td>4.9700</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>2.4790</td>\n",
              "      <td>-3.8010</td>\n",
              "      <td>-1.0230</td>\n",
              "      <td>5.3110</td>\n",
              "      <td>-0.5660</td>\n",
              "      <td>-4.4450</td>\n",
              "      <td>1.2210</td>\n",
              "      <td>1.3750</td>\n",
              "      <td>0.3932</td>\n",
              "      <td>0.3392</td>\n",
              "      <td>4.3510</td>\n",
              "      <td>5.7540</td>\n",
              "      <td>-1.6590</td>\n",
              "      <td>5.3000</td>\n",
              "      <td>5.6050</td>\n",
              "      <td>5.5320</td>\n",
              "      <td>3.7860</td>\n",
              "      <td>0.9197</td>\n",
              "      <td>1.9310</td>\n",
              "      <td>2.4870</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.8904</td>\n",
              "      <td>2.0590</td>\n",
              "      <td>0.5052</td>\n",
              "      <td>0.6890</td>\n",
              "      <td>0.5340</td>\n",
              "      <td>0.5135</td>\n",
              "      <td>0.6507</td>\n",
              "      <td>0.9838</td>\n",
              "      <td>0.4532</td>\n",
              "      <td>-0.3212</td>\n",
              "      <td>0.2662</td>\n",
              "      <td>0.6864</td>\n",
              "      <td>1.6300</td>\n",
              "      <td>1.3810</td>\n",
              "      <td>0.0061</td>\n",
              "      <td>0.2908</td>\n",
              "      <td>0.2598</td>\n",
              "      <td>0.1266</td>\n",
              "      <td>-0.3526</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>-1.1030</td>\n",
              "      <td>1.3650</td>\n",
              "      <td>1.0610</td>\n",
              "      <td>0.4034</td>\n",
              "      <td>1.0880</td>\n",
              "      <td>-0.4230</td>\n",
              "      <td>0.4013</td>\n",
              "      <td>0.1726</td>\n",
              "      <td>0.7464</td>\n",
              "      <td>0.9418</td>\n",
              "      <td>0.1855</td>\n",
              "      <td>1.1720</td>\n",
              "      <td>0.8325</td>\n",
              "      <td>0.6486</td>\n",
              "      <td>0.8090</td>\n",
              "      <td>1.5880</td>\n",
              "      <td>2.4670</td>\n",
              "      <td>0.0357</td>\n",
              "      <td>0.1351</td>\n",
              "      <td>-0.3179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "6  id_001bd861f  com_droga     24   D2  ...  2.4670  0.0357  0.1351 -0.3179\n",
              "7  id_0020d0484  com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f7zcfJM7j72_"
      },
      "source": [
        "mapa = {'droga': 'composto'}\n",
        "dados.rename(columns=mapa, inplace=True)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "3H8dsQ-MkQlD",
        "outputId": "86d49100-9def-493b-b225-90035e972f2c"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 23,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "plLaJvtulXJh"
      },
      "source": [
        "cod_compostos = dados['composto'].value_counts().index[0:5]"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JO3AeXY6mGg0",
        "outputId": "288e530e-722d-4403-e9ae-15f5696d7139"
      },
      "source": [
        "cod_compostos"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['cacb2b860', '87d714366', '9f80f3f77', '8b87a7a83', '5628cb3ee'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "M7pArA66mVVP",
        "outputId": "bafc874c-ac6d-4001-f97b-b2ee3a7c927d"
      },
      "source": [
        "dados.query('composto in @cod_compostos')"
      ],
      "execution_count": 26,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>id_002fb9c19</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>8.7380</td>\n",
              "      <td>0.1914</td>\n",
              "      <td>2.4380</td>\n",
              "      <td>-0.2930</td>\n",
              "      <td>3.2010</td>\n",
              "      <td>1.4910</td>\n",
              "      <td>5.3920</td>\n",
              "      <td>-1.0420</td>\n",
              "      <td>-8.4860</td>\n",
              "      <td>-2.5790</td>\n",
              "      <td>-6.7470</td>\n",
              "      <td>3.6150</td>\n",
              "      <td>-1.4510</td>\n",
              "      <td>0.6909</td>\n",
              "      <td>-0.7623</td>\n",
              "      <td>-2.9400</td>\n",
              "      <td>-9.2850</td>\n",
              "      <td>-6.7110</td>\n",
              "      <td>-0.4195</td>\n",
              "      <td>1.1600</td>\n",
              "      <td>-1.3180</td>\n",
              "      <td>1.3660</td>\n",
              "      <td>-1.4020</td>\n",
              "      <td>-2.6220</td>\n",
              "      <td>0.7204</td>\n",
              "      <td>-2.5930</td>\n",
              "      <td>-4.0630</td>\n",
              "      <td>-0.8282</td>\n",
              "      <td>-3.5000</td>\n",
              "      <td>0.9206</td>\n",
              "      <td>-5.1450</td>\n",
              "      <td>9.8040</td>\n",
              "      <td>-2.6840</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>-0.1427</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-9.5910</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.8870</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-4.9020</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-5.5520</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.7960</td>\n",
              "      <td>-8.1770</td>\n",
              "      <td>-9.8990</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-6.7840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\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",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23793</th>\n",
              "      <td>id_ffd26f361</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.6008</td>\n",
              "      <td>0.2781</td>\n",
              "      <td>-0.3319</td>\n",
              "      <td>-0.8782</td>\n",
              "      <td>0.9281</td>\n",
              "      <td>0.7535</td>\n",
              "      <td>0.5971</td>\n",
              "      <td>1.6350</td>\n",
              "      <td>-0.3146</td>\n",
              "      <td>0.4984</td>\n",
              "      <td>-1.1890</td>\n",
              "      <td>0.3772</td>\n",
              "      <td>-0.8196</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-2.0350</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.7586</td>\n",
              "      <td>-0.4024</td>\n",
              "      <td>-0.0449</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.2358</td>\n",
              "      <td>0.7919</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>0.4232</td>\n",
              "      <td>1.8460</td>\n",
              "      <td>-2.0940</td>\n",
              "      <td>0.1438</td>\n",
              "      <td>-0.6604</td>\n",
              "      <td>0.7243</td>\n",
              "      <td>0.0338</td>\n",
              "      <td>-0.0182</td>\n",
              "      <td>-0.2022</td>\n",
              "      <td>0.8827</td>\n",
              "      <td>0.3147</td>\n",
              "      <td>-0.9263</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1934</td>\n",
              "      <td>1.2240</td>\n",
              "      <td>-0.1178</td>\n",
              "      <td>0.1459</td>\n",
              "      <td>-0.1242</td>\n",
              "      <td>0.3106</td>\n",
              "      <td>-0.7959</td>\n",
              "      <td>0.5681</td>\n",
              "      <td>0.3663</td>\n",
              "      <td>0.4874</td>\n",
              "      <td>-0.0548</td>\n",
              "      <td>0.1810</td>\n",
              "      <td>1.3470</td>\n",
              "      <td>1.6210</td>\n",
              "      <td>-0.8260</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>0.3264</td>\n",
              "      <td>0.9241</td>\n",
              "      <td>0.3012</td>\n",
              "      <td>1.2980</td>\n",
              "      <td>-0.2789</td>\n",
              "      <td>0.7019</td>\n",
              "      <td>-0.3528</td>\n",
              "      <td>0.7383</td>\n",
              "      <td>1.0300</td>\n",
              "      <td>0.6527</td>\n",
              "      <td>1.6750</td>\n",
              "      <td>-0.5046</td>\n",
              "      <td>0.2942</td>\n",
              "      <td>0.2950</td>\n",
              "      <td>1.2470</td>\n",
              "      <td>0.9569</td>\n",
              "      <td>-0.2065</td>\n",
              "      <td>-0.4918</td>\n",
              "      <td>0.7863</td>\n",
              "      <td>0.0504</td>\n",
              "      <td>0.8813</td>\n",
              "      <td>0.7757</td>\n",
              "      <td>-0.5272</td>\n",
              "      <td>0.7082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23802</th>\n",
              "      <td>id_fff3976bd</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>3.2890</td>\n",
              "      <td>2.1270</td>\n",
              "      <td>0.9770</td>\n",
              "      <td>2.0490</td>\n",
              "      <td>2.3170</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>-0.6357</td>\n",
              "      <td>-6.9060</td>\n",
              "      <td>-4.4830</td>\n",
              "      <td>-2.8400</td>\n",
              "      <td>-5.3310</td>\n",
              "      <td>0.6547</td>\n",
              "      <td>-2.2080</td>\n",
              "      <td>3.6030</td>\n",
              "      <td>0.6380</td>\n",
              "      <td>-2.1280</td>\n",
              "      <td>-3.1680</td>\n",
              "      <td>-4.2180</td>\n",
              "      <td>-0.3170</td>\n",
              "      <td>0.2140</td>\n",
              "      <td>-1.7660</td>\n",
              "      <td>-1.9700</td>\n",
              "      <td>-1.4820</td>\n",
              "      <td>-1.3710</td>\n",
              "      <td>-0.2628</td>\n",
              "      <td>-0.5276</td>\n",
              "      <td>-2.4160</td>\n",
              "      <td>-0.4638</td>\n",
              "      <td>-3.8630</td>\n",
              "      <td>-0.8880</td>\n",
              "      <td>-1.9850</td>\n",
              "      <td>2.0530</td>\n",
              "      <td>-1.4700</td>\n",
              "      <td>-3.3220</td>\n",
              "      <td>1.8800</td>\n",
              "      <td>...</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.0200</td>\n",
              "      <td>-6.7560</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.1240</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-5.7500</td>\n",
              "      <td>-8.4760</td>\n",
              "      <td>-6.9470</td>\n",
              "      <td>-4.7650</td>\n",
              "      <td>-9.7690</td>\n",
              "      <td>-5.7900</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-5.7450</td>\n",
              "      <td>-2.3570</td>\n",
              "      <td>-9.1190</td>\n",
              "      <td>-4.5980</td>\n",
              "      <td>-8.7760</td>\n",
              "      <td>-7.7980</td>\n",
              "      <td>-4.1620</td>\n",
              "      <td>-6.1510</td>\n",
              "      <td>-5.7400</td>\n",
              "      <td>-6.8700</td>\n",
              "      <td>-9.1000</td>\n",
              "      <td>-3.3360</td>\n",
              "      <td>-6.6420</td>\n",
              "      <td>-2.2750</td>\n",
              "      <td>-3.4720</td>\n",
              "      <td>-6.2670</td>\n",
              "      <td>-6.3980</td>\n",
              "      <td>-8.6300</td>\n",
              "      <td>-8.1490</td>\n",
              "      <td>-6.2900</td>\n",
              "      <td>-8.0970</td>\n",
              "      <td>-8.7330</td>\n",
              "      <td>-2.3780</td>\n",
              "      <td>-8.4480</td>\n",
              "      <td>-4.4550</td>\n",
              "      <td>-5.7930</td>\n",
              "      <td>-3.7000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23805</th>\n",
              "      <td>id_fff6df1c5</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>5628cb3ee</td>\n",
              "      <td>1.7380</td>\n",
              "      <td>-1.2900</td>\n",
              "      <td>-0.4533</td>\n",
              "      <td>-1.1640</td>\n",
              "      <td>-0.4841</td>\n",
              "      <td>-0.2392</td>\n",
              "      <td>-0.1774</td>\n",
              "      <td>-1.3980</td>\n",
              "      <td>-0.4059</td>\n",
              "      <td>0.1553</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-0.8020</td>\n",
              "      <td>-0.5039</td>\n",
              "      <td>-0.7167</td>\n",
              "      <td>-0.5016</td>\n",
              "      <td>-0.9369</td>\n",
              "      <td>-0.5864</td>\n",
              "      <td>-0.1009</td>\n",
              "      <td>0.8987</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>-1.3460</td>\n",
              "      <td>-0.5087</td>\n",
              "      <td>-0.0892</td>\n",
              "      <td>-0.6559</td>\n",
              "      <td>0.0864</td>\n",
              "      <td>-0.6251</td>\n",
              "      <td>0.2471</td>\n",
              "      <td>-0.4523</td>\n",
              "      <td>-0.0389</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.0796</td>\n",
              "      <td>-0.2560</td>\n",
              "      <td>-0.7851</td>\n",
              "      <td>-0.1687</td>\n",
              "      <td>-1.2890</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2866</td>\n",
              "      <td>0.3854</td>\n",
              "      <td>-0.4986</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.5843</td>\n",
              "      <td>0.0907</td>\n",
              "      <td>-0.9303</td>\n",
              "      <td>0.1981</td>\n",
              "      <td>0.6515</td>\n",
              "      <td>0.2877</td>\n",
              "      <td>0.4389</td>\n",
              "      <td>-0.3859</td>\n",
              "      <td>0.5203</td>\n",
              "      <td>-1.1070</td>\n",
              "      <td>2.3870</td>\n",
              "      <td>0.1820</td>\n",
              "      <td>-0.6434</td>\n",
              "      <td>-0.9722</td>\n",
              "      <td>-0.4200</td>\n",
              "      <td>-0.5693</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>1.1110</td>\n",
              "      <td>-0.5117</td>\n",
              "      <td>-1.2130</td>\n",
              "      <td>0.3769</td>\n",
              "      <td>0.5296</td>\n",
              "      <td>1.0400</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>1.0150</td>\n",
              "      <td>-0.7669</td>\n",
              "      <td>0.2865</td>\n",
              "      <td>0.5974</td>\n",
              "      <td>-0.2727</td>\n",
              "      <td>0.1188</td>\n",
              "      <td>1.0770</td>\n",
              "      <td>-1.0250</td>\n",
              "      <td>0.1516</td>\n",
              "      <td>0.4503</td>\n",
              "      <td>-0.6312</td>\n",
              "      <td>-0.8302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3235 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "16     id_002fb9c19     com_droga     48   D1  ... -9.9840 -9.9840 -9.9840 -6.7840\n",
              "25     id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38     id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40     id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23793  id_ffd26f361  com_controle     48   D2  ...  0.8813  0.7757 -0.5272  0.7082\n",
              "23802  id_fff3976bd     com_droga     24   D1  ... -8.4480 -4.4550 -5.7930 -3.7000\n",
              "23805  id_fff6df1c5     com_droga     48   D2  ...  0.1516  0.4503 -0.6312 -0.8302\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "\n",
              "[3235 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "id": "6pHFlv-Qk5aR",
        "outputId": "5a51b736-39dc-4c8b-cfba-9d4f77324e03"
      },
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "sns.set()\n",
        "plt.figure(figsize=(8, 6))\n",
        "ax = sns.countplot(x = 'composto', data=dados.query('composto in @cod_compostos'))\n",
        "ax.set_title('Top 5 compostos')\n",
        "plt.show()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_w4vfLb-1Lgg",
        "outputId": "c0c0caa2-fa83-4718-f6bf-7def0156ddae"
      },
      "source": [
        "len(dados['g-0'].unique())"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14367"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NA7UdJWG1-G7",
        "outputId": "ec228e01-22ea-43d4-e5df-ef40d2b17f7b"
      },
      "source": [
        "dados['g-0'].min()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-5.513"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ux-n6itM2E-k",
        "outputId": "662d6eee-b125-425a-beb3-41ebe3e0eb60"
      },
      "source": [
        "dados['g-0'].max()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "HdkOpb1s2SWu",
        "outputId": "84317d5a-e27f-4e66-d511-f37c208e311a"
      },
      "source": [
        "dados['g-0'].hist(bins = 100)"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e1a2d6ad0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "fI5C0Qax7fX8",
        "outputId": "17183583-0a35-4a44-80a8-ad47f6602c7b"
      },
      "source": [
        "dados['g-19'].hist(bins = 100)"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e1a103110>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAD7CAYAAABnoJM0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAT0klEQVR4nO3df0zc9eHH8RdH4Wi/hZ2wqzuoSbeqHY5kTb1FY0aiML/cDJRs2QIj1kTRJk3aZLElomPg2hqlP1ym677dH3UmHbPqHyuBdqUubTaXTWONVS8sbdNQ/xhXiwekxyhg7z7fPxpOaIE7Du4+d7yfj7+Oe/OB19Hr5/X5+b4sy7IsAQCM5bA7AADAXhQBABiOIgAAw1EEAGA4igAADEcRAIDhKAIAMNwyuwMkamjov4pE5n8LRFHRSgWDI0lItPjImjyZlJesyZFJWaWF53U4snTbbf8z41jGFkEkYiVUBJPLZgqyJk8m5SVrcmRSVil5eTk0BACGowgAwHAUAQAYjiIAAMNRBABgOIoAAAxHEQCA4TL2PgIA6Wfiy7Dc7nxJ0tj4dYWuXrM5EeJBEQBYNLk52arZ3ilJ6tpfq5DNeRAfDg0BgOEoAgAwHEUAAIajCADAcBQBABiOIgAAw1EEAGA4igAADEcRAIDhYhbB0NCQnnrqKVVVVammpkZbt27V4OCgJOns2bPauHGjqqqq9MQTTygYDEaXS3QMAJBaMYsgKytLTz75pHp6etTV1aU77rhD+/btUyQSUVNTk1pbW9XT0yOv16t9+/ZJUsJjAIDUi1kELpdL9913X/Tr9evXq7+/X36/X06nU16vV5JUX1+vEydOSFLCYwCA1JvXpHORSERvvPGGKioqFAgEVFxcHB0rLCxUJBLR8PBwwmMulyvuLEVFK+cTfZrJ2REzAVmTJ5PyplvWiS/Dys3JvuXxzdIt983SPd/NkpV3XkWwa9curVixQo8++qjeeeedpASKVzA4okjEmvdybne+BgYyY05EsiZPJuVNx6xud/60WUYn8928okq33FOl4991LgvN63BkzboBHXcRtLe367PPPtPBgwflcDjk8XjU398fHR8cHJTD4ZDL5Up4DACQenFdPvryyy/L7/frwIEDys3NlSSVlZVpbGxMZ86ckSQdOXJEPp9vQWMAlo7JD6lxu/OVX7Dc7jiYQ8w9ggsXLuj3v/+91qxZo/r6eknS6tWrdeDAAe3Zs0dtbW0aHx9XSUmJ9u7dK0lyOBwJjQFYOviQmswRswjuuusunTt3bsaxDRs2qKura1HHAACpxZ3FAGA4igAADEcRAIDhKAIAMNy8bigDgJtNXiaKzMUeAYAFmbxMdPJSUWQeigAADEcRAIDhKAIAMBxFAACGowgAwHAUAQAYjiIAAMNRBABgOIoAAAxHEQCA4SgCADAcRQAAhqMIAMBwFAEAGI4iAADD8cE0AJJu6ofXjI1fV+jqNZsTYSqKAEDSTX54jSR17a9VyOY8mI5DQwBgOIoAAAxHEQCA4SgCADAcRQAAhqMIAMBwXD4KIC75BcuV52SVsRSxRwAgLnnOZarZ3hm9HwBLB0UAAIajCADAcBQBABiOIgAAw1EEAGA4igAADEcRAIDhKAIAMFxcRdDe3q6KigqtW7dO58+fjz5fUVEhn8+n2tpa1dbW6t13342OnT17Vhs3blRVVZWeeOIJBYPBuMYAAKkVVxFUVlaqo6NDJSUlt4y98sor6uzsVGdnp8rLyyVJkUhETU1Nam1tVU9Pj7xer/bt2xdzDACQenEVgdfrlcfjifuH+v1+OZ1Oeb1eSVJ9fb1OnDgRcwwAkHoLnkFqx44dsixL9957r55++mkVFBQoEAiouLg4+j2FhYWKRCIaHh6ec8zlci00DgBgnhZUBB0dHfJ4PJqYmNALL7ygnTt3puwwT1HRyoSXdbvzFzFJcpE1eTIpbyZljUe6vJ50yRGvZOVdUBFMHi7Kzc1VQ0ODtmzZEn2+v78/+n2Dg4NyOBxyuVxzjs1HMDiiSMSad2a3O18DA6F5L2cHsiZPJuVNl6yLuRJKl9eTDjnitdC8DkfWrBvQCV8+Ojo6qlDoRijLsnT8+HGVlpZKksrKyjQ2NqYzZ85Iko4cOSKfzxdzDACQenHtEezevVsnT57UF198occff1wul0sHDx7Utm3bFA6HFYlEtHbtWrW1tUmSHA6H9uzZo7a2No2Pj6ukpER79+6NOQYASL24iqClpUUtLS23PH/06NFZl9mwYYO6urrmPQYASC3uLAYAw/EBpABSauLLcPTE89j4dYWuXrM5ESgCACmVm5Md/dzjrv21ypzrdpYuigDArPILlivPyWpiqeMcAYBZ5TmXqWZ7Z3QLHksTRQAAhqMIAMBwFAEAGI4iAADDUQQAYDiKAAAMRxEAgOEoAgAwHEUAAIajCADAcBQBABiOIgAAw1EEAGA4igAADEcRAIDhKAIAMBxFAACGowgAwHAUAQAYjiIAAMNRBABgOIoAAAy3zO4AANJLfsFy5TlZNZiEPQIA0+Q5l6lme6dqtnfaHQUpQhEAgOEoAgAwHEUAAIajCADAcBQBABiOIgAAw1EEAGA47hoBYJuJL8Nyu/MlSWPj1xW6es3mRGaiCADYJjcnO3rjWtf+WoVszmMqDg0BgOFiFkF7e7sqKiq0bt06nT9/Pvp8X1+f6urqVFVVpbq6Ol26dGnBYwCA1ItZBJWVlero6FBJScm059va2tTQ0KCenh41NDSotbV1wWMAgNSLWQRer1cej2fac8FgUL29vaqurpYkVVdXq7e3V4ODgwmPAQDskdDJ4kAgoNtvv13Z2dmSpOzsbK1atUqBQECWZSU0VlhYuEgvCQAwHxl71VBR0cqEl528XC0TkDV5MilvJmVdiFS/zkz7uyYrb0JF4PF49PnnnyscDis7O1vhcFhXrlyRx+ORZVkJjc1XMDiiSMSa93Jud74GBjLjIjWyJk8m5U11VjtXjql+nZnyHpAWntfhyJp1Azqhy0eLiopUWlqq7u5uSVJ3d7dKS0tVWFiY8BgAwB4x9wh2796tkydP6osvvtDjjz8ul8ulY8eO6fnnn1dzc7N+97vfqaCgQO3t7dFlEh0DAKRezCJoaWlRS0vLLc+vXbtWb7/99ozLJDoGAEi9jD1ZDGBpYd4h+1AEANIC8w7Zh7mGAMBwFAEAGI4iAADDUQQAYDiKAAAMRxEAgOEoAgAwHEUAAIbjhjIAyi9YrjwnqwNTsUcAQHnOZarZ3hm9sxdmoQgAwHAUAQAYjiIAAMNRBABgOIoAAAzH9WKAobhkFJPYIwAMxSWjmEQRAIDhKAIAMBxFAACGowgAwHAUAQAYjiIAAMNRBABgOIoAAAxHEQCA4SgCADAcRQAAhqMIAMBwFAEAGI4iAADDUQQAYDg+lQJA2pn4Miy3O1+SNDZ+XaGr12xOtLRRBADSTm5OdvQDc7r21ypkc56ljkNDAGA4igAADEcRAIDhFnyOoKKiQrm5uXI6nZKkHTt2qLy8XGfPnlVra6vGx8dVUlKivXv3qqioSJLmHAMApNai7BG88sor6uzsVGdnp8rLyxWJRNTU1KTW1lb19PTI6/Vq3759kjTnGIDkyi9YLrc7P3pFDiAl6dCQ3++X0+mU1+uVJNXX1+vEiRMxxwAkV55zmWq2d0avyAGkRbp8dMeOHbIsS/fee6+efvppBQIBFRcXR8cLCwsViUQ0PDw855jL5VqMOACAeVhwEXR0dMjj8WhiYkIvvPCCdu7cqYcffngxss2pqGhlwstm0m4xWZMnk/JmUtZkSNbrz7S/a7LyLrgIPB6PJCk3N1cNDQ3asmWLHnvsMfX390e/Z3BwUA6HQy6XSx6PZ9ax+QgGRxSJWPPO63bna2AgM25PIWvyZFLexcyaaSu+Scn4t8qk94C08LwOR9asG9ALOkcwOjqqUOhGMMuydPz4cZWWlqqsrExjY2M6c+aMJOnIkSPy+XySNOcYACD1FrRHEAwGtW3bNoXDYUUiEa1du1ZtbW1yOBzas2eP2trapl0iKmnOMQBA6i2oCO644w4dPXp0xrENGzaoq6tr3mMAMBUT0CUfk84BSGtMQJd8TDEBAIajCADAcBQBABiOcwTAEpdfsFx5Tv6rY3bsEQBLHPMLIRaKAAAMRxEAgOEoAgAwHEUAAIajCADAcFxTBiBjMO9QclAEwBK0VO8dYN6h5ODQELAEce8A5oMiAADDUQQAYLildxARgBE4cbx4KAIAGYkTx4uHQ0MAYDiKAAAMRxEAgOEoAgAwHEUAAIbjqiFgiViq00og+dgjAJYIppVAoigCADAc+5FAhuJQ0Fe4y3hheBcBGWryUNCkrv21NqaxF3cZLwyHhgDAcBQBABiOIgAAw3GOAMggnCCObeqJY4mTx/HgHQWkuZtXbFNPiuJWU08cS5w8jgeHhoA0N7li40YxJAt7BACWNO4xiI0iANIQ5wIWD/cYxMahISANMW8QUolNDsBGU7f8xyfCcuZm25xoaZt6mGjiy7DNadIHRQDYaOo0EV37a7kiKMluPkyEGygCIAXY8k8/nET+im1F0NfXp+bmZg0PD8vlcqm9vV1r1qyxKw6QsNlW8lNXLmz5px9OIn/FtpPFbW1tamhoUE9PjxoaGtTa2mpXFGBBpp7YdeZ+dc2/w5Eltzt/2s1gSE+Tewdud74KvrYi+ji/YLnd0VLClj2CYDCo3t5e/eEPf5AkVVdXa9euXRocHFRhYWFcP8PhyEr49y9k2VQja2JWrsyTc3Irffy6RkbGbnm+4GsrolvvU7fk5/tYklbdtvyWx7k52WrcfVKSdKjlf2f8nsV8nKyfm+mP4/m+m/+tJh//3zOV0SKf9u8/5T2VSsla72VZlmUl/JMT5Pf79cwzz+jYsWPR5x555BHt3btX3/nOd1IdBwCMxn0EAGA4W4rA4/Ho888/Vzh84zrecDisK1euyOPx2BEHAIxmSxEUFRWptLRU3d3dkqTu7m6VlpbGfX4AALB4bDlHIEkXL15Uc3Ozrl69qoKCArW3t+tb3/qWHVEAwGi2FQEAID1wshgADEcRAIDhKAIAMBxFAACGM6IIOjs7VVNTo3vuuUd//OMfp41du3ZNP//5z/Xwww/L5/Pp9OnTNqWcWV9fnzZt2qTa2lr98Ic/1Kuvvmp3pDkdPnxYPp9PNTU1qq3NjAnV3n//fZWWlt7y3kgnv/rVr+Tz+bRx40bV19fr008/tTvSNH19faqrq1NVVZXq6up06dIluyPNamhoSE899ZSqqqpUU1OjrVu3anBw0O5YMf32t7/VunXrdP78+cX/4ZYBzp07Z124cMFqamqyDh8+PG3s1VdftX7xi19YlmVZfX191gMPPGCNjIzYEXNGW7ZsiWYeGRmxHnzwQevjjz+2OdXMenp6rIaGBisUClmWZVkDAwM2J4otFApZP/nJT6zNmzff8t5IJ6dOnbImJiaijysrK21ONN2mTZuso0ePWpZlWUePHrU2bdpkc6LZDQ0NWe+9917065deesl69tlnbUwUm9/vtxobG62HHnrIOnfu3KL/fCP2CO6++27deeedcjhufbl/+ctfVFdXJ0las2aNysrK9Pe//z3VEWeVlZWlUOjGBLljY2PKyspK2xvvXnvtNW3dulUrV66UJH3961+3OVFsL730khobG3XbbbfZHWVODz30kHJyciRJ69ev1+XLlxWJRGxOdcPkJJLV1dWSbkwi2dvbm7Zb2S6XS/fdd1/06/Xr16u/v9/GRHObmJjQzp079fzzzyftdxhRBHPp7+9XSUlJ9GuPx6PLly/bmGi65557TsePH1d5ebkqKirU2Nio1atX2x1rRhcvXtTHH3+s+vp6/fjHP9Zbb71ld6Q5/e1vf1MoFJLP57M7yrx0dHTowQcfnHHDxg6BQEC33367srNvzMyZnZ2tVatWKRAI2JwstkgkojfeeEMVFRV2R5nVb37zG23cuDGp/++XxCeU/ehHP5q10f/5z39G36DpKFb2N998U7W1tXryySd15coVbdq0SWVlZfrud7+b4qSxs4bDYQUCAf3pT3/S0NCQfvazn+mb3/ymvve976U46Q1z5T1x4oT2798fnQrdbvG+h48dO6auri51dHSkMt6StWvXLq1YsUKPPvqo3VFm9NFHH8nv92vHjh1J/T1Logj+/Oc/J7xscXGx/vOf/0QPtwQCgWm7jckWK/vhw4f117/+VZK0atUq3X///frggw9sKYJYWYuLi1VdXS2Hw6GioiI98MAD+uSTT2wrgrnynjlzRgMDA/rpT38q6cYJxNOnT2t4eFhbt25NVcSoeN7D77zzjn7961/r9ddfT6vDblMnkczOzs6YSSTb29v12Wef6eDBg2mzd3WzDz74QBcvXlRlZaUk6fLly2psbNSLL76o73//+4v2e9Lz1aeQz+fTm2++KUm6dOmSPv30U5WXl9uc6iurV6/Wu+++K0kaGRnRhx9+qLvuusvmVDOrrq6OZh0dHdWHH36ob3/72zanmpnX69W//vUvnTp1SqdOnVJVVZW2bdtmSwnE4/Tp03rxxRd16NChtDs0mImTSL788svy+/06cOCAcnNz7Y4zq82bN+sf//hH9H36jW98Q4cOHVrUEpAMmWuou7tbe/bs0dWrV5WTk6Ply5frtdde05133qnR0VE1Nzfr3//+txwOh5qamvSDH/zA7shRfr9fu3fv1ujoqK5fv65HHnkkbVdWY2Nj+uUvf6ne3l5JUm1trTZv3mxzqvg0NzerrKwsbQ8R3H///crJyZm2cn399dfT5iR3Jk0ieeHCBVVXV2vNmjXKy8uTdGOD68CBAzYni62iokIHDx7U3Xffvag/14giAADMzvhDQwBgOooAAAxHEQCA4SgCADAcRQAAhqMIAMBwFAEAGI4iAADD/T/vwhUQr40OmwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "EZdL3_ip8hUK",
        "outputId": "2325c7ed-e105-41c9-880f-cf4b719942a0"
      },
      "source": [
        "dados.describe()"
      ],
      "execution_count": 33,
      "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>tempo</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>48.020156</td>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.517397</td>\n",
              "      <td>-0.360770</td>\n",
              "      <td>-0.435752</td>\n",
              "      <td>-0.613591</td>\n",
              "      <td>-0.402083</td>\n",
              "      <td>-0.619682</td>\n",
              "      <td>-0.452265</td>\n",
              "      <td>-0.497164</td>\n",
              "      <td>-0.413836</td>\n",
              "      <td>-0.277029</td>\n",
              "      <td>-0.547845</td>\n",
              "      <td>-0.358611</td>\n",
              "      <td>-0.442906</td>\n",
              "      <td>-0.475194</td>\n",
              "      <td>-0.010404</td>\n",
              "      <td>-0.467001</td>\n",
              "      <td>-0.276963</td>\n",
              "      <td>-0.455848</td>\n",
              "      <td>-0.412918</td>\n",
              "      <td>-0.456404</td>\n",
              "      <td>-0.472514</td>\n",
              "      <td>-0.505481</td>\n",
              "      <td>-0.492735</td>\n",
              "      <td>-0.446836</td>\n",
              "      <td>-0.463029</td>\n",
              "      <td>-0.409310</td>\n",
              "      <td>-0.333124</td>\n",
              "      <td>-0.295009</td>\n",
              "      <td>-0.328342</td>\n",
              "      <td>-0.401615</td>\n",
              "      <td>-0.469244</td>\n",
              "      <td>-0.461411</td>\n",
              "      <td>-0.513256</td>\n",
              "      <td>-0.500142</td>\n",
              "      <td>-0.507093</td>\n",
              "      <td>-0.353726</td>\n",
              "      <td>-0.463485</td>\n",
              "      <td>-0.378241</td>\n",
              "      <td>-0.470252</td>\n",
              "      <td>-0.301505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>19.402807</td>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>...</td>\n",
              "      <td>2.122318</td>\n",
              "      <td>1.710725</td>\n",
              "      <td>1.898871</td>\n",
              "      <td>2.307820</td>\n",
              "      <td>1.785055</td>\n",
              "      <td>2.225596</td>\n",
              "      <td>1.991021</td>\n",
              "      <td>2.063896</td>\n",
              "      <td>1.887001</td>\n",
              "      <td>1.459639</td>\n",
              "      <td>2.187835</td>\n",
              "      <td>1.730634</td>\n",
              "      <td>1.924716</td>\n",
              "      <td>2.021927</td>\n",
              "      <td>1.029820</td>\n",
              "      <td>2.004317</td>\n",
              "      <td>1.429340</td>\n",
              "      <td>1.924263</td>\n",
              "      <td>1.888788</td>\n",
              "      <td>1.832863</td>\n",
              "      <td>2.011396</td>\n",
              "      <td>2.091353</td>\n",
              "      <td>2.055624</td>\n",
              "      <td>1.987476</td>\n",
              "      <td>2.014045</td>\n",
              "      <td>1.883974</td>\n",
              "      <td>1.647241</td>\n",
              "      <td>1.634073</td>\n",
              "      <td>1.663170</td>\n",
              "      <td>1.832794</td>\n",
              "      <td>2.000488</td>\n",
              "      <td>2.042475</td>\n",
              "      <td>2.001714</td>\n",
              "      <td>2.107105</td>\n",
              "      <td>2.159589</td>\n",
              "      <td>1.629291</td>\n",
              "      <td>2.059725</td>\n",
              "      <td>1.703615</td>\n",
              "      <td>1.834828</td>\n",
              "      <td>1.407918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.839000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.452000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.938000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.588075</td>\n",
              "      <td>-0.564025</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.583250</td>\n",
              "      <td>-0.566500</td>\n",
              "      <td>-0.603200</td>\n",
              "      <td>-0.541575</td>\n",
              "      <td>-0.560825</td>\n",
              "      <td>-0.555200</td>\n",
              "      <td>-0.534500</td>\n",
              "      <td>-0.569100</td>\n",
              "      <td>-0.558300</td>\n",
              "      <td>-0.573350</td>\n",
              "      <td>-0.594275</td>\n",
              "      <td>-0.389925</td>\n",
              "      <td>-0.551200</td>\n",
              "      <td>-0.544150</td>\n",
              "      <td>-0.575075</td>\n",
              "      <td>-0.568275</td>\n",
              "      <td>-0.582650</td>\n",
              "      <td>-0.558575</td>\n",
              "      <td>-0.562375</td>\n",
              "      <td>-0.572800</td>\n",
              "      <td>-0.561225</td>\n",
              "      <td>-0.560675</td>\n",
              "      <td>-0.560100</td>\n",
              "      <td>-0.533700</td>\n",
              "      <td>-0.504575</td>\n",
              "      <td>-0.544275</td>\n",
              "      <td>-0.569150</td>\n",
              "      <td>-0.566175</td>\n",
              "      <td>-0.565975</td>\n",
              "      <td>-0.589975</td>\n",
              "      <td>-0.568700</td>\n",
              "      <td>-0.563775</td>\n",
              "      <td>-0.567975</td>\n",
              "      <td>-0.552575</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.592600</td>\n",
              "      <td>-0.562900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.017650</td>\n",
              "      <td>-0.041550</td>\n",
              "      <td>-0.002950</td>\n",
              "      <td>-0.012650</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.004950</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.023800</td>\n",
              "      <td>-0.011450</td>\n",
              "      <td>-0.007100</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.009300</td>\n",
              "      <td>0.081550</td>\n",
              "      <td>-0.006900</td>\n",
              "      <td>0.018400</td>\n",
              "      <td>-0.014650</td>\n",
              "      <td>-0.014350</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>-0.005300</td>\n",
              "      <td>-0.004050</td>\n",
              "      <td>0.003300</td>\n",
              "      <td>-0.007900</td>\n",
              "      <td>-0.004600</td>\n",
              "      <td>-0.002400</td>\n",
              "      <td>0.007850</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>-0.020600</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>-0.009900</td>\n",
              "      <td>0.003250</td>\n",
              "      <td>-0.009100</td>\n",
              "      <td>-0.013750</td>\n",
              "      <td>-0.003300</td>\n",
              "      <td>-0.010250</td>\n",
              "      <td>-0.001250</td>\n",
              "      <td>-0.006800</td>\n",
              "      <td>0.014000</td>\n",
              "      <td>-0.019500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>...</td>\n",
              "      <td>0.452675</td>\n",
              "      <td>0.427675</td>\n",
              "      <td>0.462175</td>\n",
              "      <td>0.447975</td>\n",
              "      <td>0.447150</td>\n",
              "      <td>0.441250</td>\n",
              "      <td>0.470600</td>\n",
              "      <td>0.458550</td>\n",
              "      <td>0.441000</td>\n",
              "      <td>0.460075</td>\n",
              "      <td>0.460950</td>\n",
              "      <td>0.449975</td>\n",
              "      <td>0.445200</td>\n",
              "      <td>0.473200</td>\n",
              "      <td>0.563575</td>\n",
              "      <td>0.456350</td>\n",
              "      <td>0.493400</td>\n",
              "      <td>0.448375</td>\n",
              "      <td>0.451975</td>\n",
              "      <td>0.463075</td>\n",
              "      <td>0.447675</td>\n",
              "      <td>0.462000</td>\n",
              "      <td>0.468900</td>\n",
              "      <td>0.452375</td>\n",
              "      <td>0.460475</td>\n",
              "      <td>0.461675</td>\n",
              "      <td>0.465950</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.450075</td>\n",
              "      <td>0.430875</td>\n",
              "      <td>0.457750</td>\n",
              "      <td>0.461500</td>\n",
              "      <td>0.445675</td>\n",
              "      <td>0.452900</td>\n",
              "      <td>0.470900</td>\n",
              "      <td>0.444750</td>\n",
              "      <td>0.465225</td>\n",
              "      <td>0.446400</td>\n",
              "      <td>0.461275</td>\n",
              "      <td>0.438650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>3.888000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>4.857000</td>\n",
              "      <td>3.549000</td>\n",
              "      <td>3.382000</td>\n",
              "      <td>3.328000</td>\n",
              "      <td>4.157000</td>\n",
              "      <td>3.736000</td>\n",
              "      <td>3.582000</td>\n",
              "      <td>3.119000</td>\n",
              "      <td>3.323000</td>\n",
              "      <td>5.014000</td>\n",
              "      <td>2.898000</td>\n",
              "      <td>4.185000</td>\n",
              "      <td>3.170000</td>\n",
              "      <td>3.276000</td>\n",
              "      <td>4.992000</td>\n",
              "      <td>3.770000</td>\n",
              "      <td>2.851000</td>\n",
              "      <td>3.211000</td>\n",
              "      <td>4.534000</td>\n",
              "      <td>3.890000</td>\n",
              "      <td>3.994000</td>\n",
              "      <td>4.321000</td>\n",
              "      <td>4.020000</td>\n",
              "      <td>3.738000</td>\n",
              "      <td>3.252000</td>\n",
              "      <td>5.406000</td>\n",
              "      <td>3.110000</td>\n",
              "      <td>3.320000</td>\n",
              "      <td>4.069000</td>\n",
              "      <td>3.960000</td>\n",
              "      <td>3.927000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>3.747000</td>\n",
              "      <td>2.814000</td>\n",
              "      <td>3.505000</td>\n",
              "      <td>2.924000</td>\n",
              "      <td>3.111000</td>\n",
              "      <td>3.805000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 873 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              tempo           g-0  ...          c-98          c-99\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean      48.020156      0.248366  ...     -0.470252     -0.301505\n",
              "std       19.402807      1.393399  ...      1.834828      1.407918\n",
              "min       24.000000     -5.513000  ...    -10.000000    -10.000000\n",
              "25%       24.000000     -0.473075  ...     -0.592600     -0.562900\n",
              "50%       48.000000     -0.008850  ...      0.014000     -0.019500\n",
              "75%       72.000000      0.525700  ...      0.461275      0.438650\n",
              "max       72.000000     10.000000  ...      3.111000      3.805000\n",
              "\n",
              "[8 rows x 873 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "orSJLiGh8_eS",
        "outputId": "d6f414fe-21ed-47b2-ff19-26910a0f878c"
      },
      "source": [
        "#Slice\n",
        "dados[['g-0','g-1']]"
      ],
      "execution_count": 34,
      "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>g-0</th>\n",
              "      <th>g-1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          g-0     g-1\n",
              "0      1.0620  0.5577\n",
              "1      0.0743  0.4087\n",
              "2      0.6280  0.5817\n",
              "3     -0.5138 -0.2491\n",
              "4     -0.3254 -0.4009\n",
              "...       ...     ...\n",
              "23809  0.1394 -0.0636\n",
              "23810 -1.3260  0.3478\n",
              "23811  0.3942  0.3756\n",
              "23812  0.6660  0.2324\n",
              "23813 -0.8598  1.0240\n",
              "\n",
              "[23814 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Udr8_lZ-9M12",
        "outputId": "a8bcc1d8-48d3-4268-ecac-a23f6749f8f3"
      },
      "source": [
        "\n",
        "dados.loc[0,'g-0']"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.062"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "P8MTE3e79ef_",
        "outputId": "66f176c8-b920-43f7-febb-af67d2ded771"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe()"
      ],
      "execution_count": 36,
      "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>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>g-39</th>\n",
              "      <th>...</th>\n",
              "      <th>g-732</th>\n",
              "      <th>g-733</th>\n",
              "      <th>g-734</th>\n",
              "      <th>g-735</th>\n",
              "      <th>g-736</th>\n",
              "      <th>g-737</th>\n",
              "      <th>g-738</th>\n",
              "      <th>g-739</th>\n",
              "      <th>g-740</th>\n",
              "      <th>g-741</th>\n",
              "      <th>g-742</th>\n",
              "      <th>g-743</th>\n",
              "      <th>g-744</th>\n",
              "      <th>g-745</th>\n",
              "      <th>g-746</th>\n",
              "      <th>g-747</th>\n",
              "      <th>g-748</th>\n",
              "      <th>g-749</th>\n",
              "      <th>g-750</th>\n",
              "      <th>g-751</th>\n",
              "      <th>g-752</th>\n",
              "      <th>g-753</th>\n",
              "      <th>g-754</th>\n",
              "      <th>g-755</th>\n",
              "      <th>g-756</th>\n",
              "      <th>g-757</th>\n",
              "      <th>g-758</th>\n",
              "      <th>g-759</th>\n",
              "      <th>g-760</th>\n",
              "      <th>g-761</th>\n",
              "      <th>g-762</th>\n",
              "      <th>g-763</th>\n",
              "      <th>g-764</th>\n",
              "      <th>g-765</th>\n",
              "      <th>g-766</th>\n",
              "      <th>g-767</th>\n",
              "      <th>g-768</th>\n",
              "      <th>g-769</th>\n",
              "      <th>g-770</th>\n",
              "      <th>g-771</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>0.132026</td>\n",
              "      <td>...</td>\n",
              "      <td>0.263569</td>\n",
              "      <td>-0.242638</td>\n",
              "      <td>0.110180</td>\n",
              "      <td>-0.039868</td>\n",
              "      <td>-0.064056</td>\n",
              "      <td>0.193629</td>\n",
              "      <td>0.004470</td>\n",
              "      <td>-0.187085</td>\n",
              "      <td>0.067186</td>\n",
              "      <td>0.006159</td>\n",
              "      <td>-0.201189</td>\n",
              "      <td>-0.243317</td>\n",
              "      <td>0.548903</td>\n",
              "      <td>0.247065</td>\n",
              "      <td>0.085950</td>\n",
              "      <td>0.090544</td>\n",
              "      <td>0.215525</td>\n",
              "      <td>-0.007705</td>\n",
              "      <td>0.236954</td>\n",
              "      <td>0.022785</td>\n",
              "      <td>0.103224</td>\n",
              "      <td>0.048402</td>\n",
              "      <td>0.109367</td>\n",
              "      <td>-0.103262</td>\n",
              "      <td>0.004129</td>\n",
              "      <td>0.066211</td>\n",
              "      <td>0.072773</td>\n",
              "      <td>-0.033051</td>\n",
              "      <td>-0.400643</td>\n",
              "      <td>-0.338978</td>\n",
              "      <td>0.207299</td>\n",
              "      <td>0.009161</td>\n",
              "      <td>0.171027</td>\n",
              "      <td>0.002316</td>\n",
              "      <td>-0.209799</td>\n",
              "      <td>-0.076251</td>\n",
              "      <td>0.134162</td>\n",
              "      <td>-0.128018</td>\n",
              "      <td>-0.219210</td>\n",
              "      <td>0.101524</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>0.990477</td>\n",
              "      <td>...</td>\n",
              "      <td>1.075809</td>\n",
              "      <td>1.309482</td>\n",
              "      <td>0.881283</td>\n",
              "      <td>0.917119</td>\n",
              "      <td>1.186966</td>\n",
              "      <td>1.212621</td>\n",
              "      <td>1.175611</td>\n",
              "      <td>1.182180</td>\n",
              "      <td>1.057292</td>\n",
              "      <td>0.996940</td>\n",
              "      <td>1.029370</td>\n",
              "      <td>1.378815</td>\n",
              "      <td>2.023791</td>\n",
              "      <td>1.639307</td>\n",
              "      <td>1.238753</td>\n",
              "      <td>0.961212</td>\n",
              "      <td>1.293783</td>\n",
              "      <td>0.966213</td>\n",
              "      <td>1.284074</td>\n",
              "      <td>1.015557</td>\n",
              "      <td>1.035968</td>\n",
              "      <td>1.048645</td>\n",
              "      <td>0.856080</td>\n",
              "      <td>1.175372</td>\n",
              "      <td>0.701031</td>\n",
              "      <td>0.996914</td>\n",
              "      <td>1.077310</td>\n",
              "      <td>1.579948</td>\n",
              "      <td>1.913468</td>\n",
              "      <td>1.701554</td>\n",
              "      <td>1.096488</td>\n",
              "      <td>1.200395</td>\n",
              "      <td>1.357701</td>\n",
              "      <td>1.052771</td>\n",
              "      <td>1.201918</td>\n",
              "      <td>1.115477</td>\n",
              "      <td>0.951264</td>\n",
              "      <td>1.230636</td>\n",
              "      <td>1.326193</td>\n",
              "      <td>1.417674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.223000</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.504000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-3.790000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.920000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.462000</td>\n",
              "      <td>-6.634000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.912000</td>\n",
              "      <td>-9.833000</td>\n",
              "      <td>-7.227000</td>\n",
              "      <td>-5.561000</td>\n",
              "      <td>-8.393000</td>\n",
              "      <td>-5.790000</td>\n",
              "      <td>-4.915000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.918000</td>\n",
              "      <td>-5.255000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.264000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.505000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.193000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.795000</td>\n",
              "      <td>-8.180000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.269000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>-0.401700</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.390700</td>\n",
              "      <td>-0.565075</td>\n",
              "      <td>-0.433275</td>\n",
              "      <td>-0.498650</td>\n",
              "      <td>-0.526300</td>\n",
              "      <td>-0.430750</td>\n",
              "      <td>-0.488775</td>\n",
              "      <td>-0.593125</td>\n",
              "      <td>-0.498275</td>\n",
              "      <td>-0.489800</td>\n",
              "      <td>-0.564100</td>\n",
              "      <td>-0.538000</td>\n",
              "      <td>-0.464000</td>\n",
              "      <td>-0.521975</td>\n",
              "      <td>-0.488600</td>\n",
              "      <td>-0.442925</td>\n",
              "      <td>-0.457200</td>\n",
              "      <td>-0.477900</td>\n",
              "      <td>-0.458175</td>\n",
              "      <td>-0.479075</td>\n",
              "      <td>-0.478825</td>\n",
              "      <td>-0.489300</td>\n",
              "      <td>-0.327500</td>\n",
              "      <td>-0.576775</td>\n",
              "      <td>-0.278275</td>\n",
              "      <td>-0.492700</td>\n",
              "      <td>-0.501575</td>\n",
              "      <td>-0.526450</td>\n",
              "      <td>-0.507375</td>\n",
              "      <td>-0.559175</td>\n",
              "      <td>-0.433875</td>\n",
              "      <td>-0.502250</td>\n",
              "      <td>-0.537075</td>\n",
              "      <td>-0.508775</td>\n",
              "      <td>-0.606175</td>\n",
              "      <td>-0.506200</td>\n",
              "      <td>-0.353100</td>\n",
              "      <td>-0.544600</td>\n",
              "      <td>-0.554400</td>\n",
              "      <td>-0.523800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>0.007400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.065650</td>\n",
              "      <td>-0.014100</td>\n",
              "      <td>0.030850</td>\n",
              "      <td>-0.001800</td>\n",
              "      <td>-0.008400</td>\n",
              "      <td>0.101400</td>\n",
              "      <td>0.033400</td>\n",
              "      <td>-0.001600</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>0.014800</td>\n",
              "      <td>-0.044000</td>\n",
              "      <td>0.017400</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>-0.015550</td>\n",
              "      <td>0.025350</td>\n",
              "      <td>0.017750</td>\n",
              "      <td>0.053450</td>\n",
              "      <td>0.027700</td>\n",
              "      <td>-0.002100</td>\n",
              "      <td>0.009500</td>\n",
              "      <td>-0.004450</td>\n",
              "      <td>-0.000050</td>\n",
              "      <td>0.002400</td>\n",
              "      <td>0.024250</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>0.013600</td>\n",
              "      <td>0.001350</td>\n",
              "      <td>0.007350</td>\n",
              "      <td>0.038700</td>\n",
              "      <td>0.059600</td>\n",
              "      <td>-0.005900</td>\n",
              "      <td>-0.013600</td>\n",
              "      <td>-0.027700</td>\n",
              "      <td>-0.011850</td>\n",
              "      <td>0.009900</td>\n",
              "      <td>0.005400</td>\n",
              "      <td>0.000600</td>\n",
              "      <td>0.028700</td>\n",
              "      <td>-0.006500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>0.439400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.646900</td>\n",
              "      <td>0.467900</td>\n",
              "      <td>0.543400</td>\n",
              "      <td>0.477200</td>\n",
              "      <td>0.497400</td>\n",
              "      <td>0.846400</td>\n",
              "      <td>0.573875</td>\n",
              "      <td>0.501675</td>\n",
              "      <td>0.519825</td>\n",
              "      <td>0.515000</td>\n",
              "      <td>0.412375</td>\n",
              "      <td>0.479400</td>\n",
              "      <td>0.646325</td>\n",
              "      <td>0.565200</td>\n",
              "      <td>0.610075</td>\n",
              "      <td>0.506975</td>\n",
              "      <td>0.671725</td>\n",
              "      <td>0.514175</td>\n",
              "      <td>0.524175</td>\n",
              "      <td>0.501325</td>\n",
              "      <td>0.516975</td>\n",
              "      <td>0.517475</td>\n",
              "      <td>0.375275</td>\n",
              "      <td>0.572250</td>\n",
              "      <td>0.251600</td>\n",
              "      <td>0.540950</td>\n",
              "      <td>0.530900</td>\n",
              "      <td>0.527900</td>\n",
              "      <td>0.475275</td>\n",
              "      <td>0.522075</td>\n",
              "      <td>0.648500</td>\n",
              "      <td>0.492150</td>\n",
              "      <td>0.522500</td>\n",
              "      <td>0.457000</td>\n",
              "      <td>0.483000</td>\n",
              "      <td>0.511175</td>\n",
              "      <td>0.409075</td>\n",
              "      <td>0.498500</td>\n",
              "      <td>0.496400</td>\n",
              "      <td>0.536950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.889000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.635000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.664000</td>\n",
              "      <td>9.566000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.497000</td>\n",
              "      <td>6.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.323000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.533000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.008000</td>\n",
              "      <td>5.900000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.552000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.346000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>6.317000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                g-0           g-1  ...         g-770         g-771\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean       0.248366     -0.095684  ...     -0.219210      0.101524\n",
              "std        1.393399      0.812363  ...      1.326193      1.417674\n",
              "min       -5.513000     -5.737000  ...    -10.000000    -10.000000\n",
              "25%       -0.473075     -0.562200  ...     -0.554400     -0.523800\n",
              "50%       -0.008850     -0.046600  ...      0.028700     -0.006500\n",
              "75%        0.525700      0.403075  ...      0.496400      0.536950\n",
              "max       10.000000      5.039000  ...     10.000000     10.000000\n",
              "\n",
              "[8 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yoWzleIZ9-ua",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "9d4ab1ad-495a-495f-e9f9-6bca7c82ed70"
      },
      "source": [
        "#Matriz Transposta\n",
        "dados.loc[:,'g-0':'g-771'].describe().T"
      ],
      "execution_count": 37,
      "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>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>g-0</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>0.248366</td>\n",
              "      <td>1.393399</td>\n",
              "      <td>-5.513</td>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.00885</td>\n",
              "      <td>0.525700</td>\n",
              "      <td>10.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-1</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>-5.737</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.04660</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>5.039</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-2</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>-9.104</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>0.07520</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>8.257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-3</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>-5.998</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>0.00805</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>10.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-4</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>-6.369</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.02690</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>10.000</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-767</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>-0.076251</td>\n",
              "      <td>1.115477</td>\n",
              "      <td>-10.000</td>\n",
              "      <td>-0.506200</td>\n",
              "      <td>0.00990</td>\n",
              "      <td>0.511175</td>\n",
              "      <td>6.317</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-768</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>0.134162</td>\n",
              "      <td>0.951264</td>\n",
              "      <td>-4.269</td>\n",
              "      <td>-0.353100</td>\n",
              "      <td>0.00540</td>\n",
              "      <td>0.409075</td>\n",
              "      <td>10.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-769</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>-0.128018</td>\n",
              "      <td>1.230636</td>\n",
              "      <td>-10.000</td>\n",
              "      <td>-0.544600</td>\n",
              "      <td>0.00060</td>\n",
              "      <td>0.498500</td>\n",
              "      <td>5.911</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-770</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>-0.219210</td>\n",
              "      <td>1.326193</td>\n",
              "      <td>-10.000</td>\n",
              "      <td>-0.554400</td>\n",
              "      <td>0.02870</td>\n",
              "      <td>0.496400</td>\n",
              "      <td>10.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-771</th>\n",
              "      <td>23814.0</td>\n",
              "      <td>0.101524</td>\n",
              "      <td>1.417674</td>\n",
              "      <td>-10.000</td>\n",
              "      <td>-0.523800</td>\n",
              "      <td>-0.00650</td>\n",
              "      <td>0.536950</td>\n",
              "      <td>10.000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>772 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         count      mean       std     min       25%      50%       75%     max\n",
              "g-0    23814.0  0.248366  1.393399  -5.513 -0.473075 -0.00885  0.525700  10.000\n",
              "g-1    23814.0 -0.095684  0.812363  -5.737 -0.562200 -0.04660  0.403075   5.039\n",
              "g-2    23814.0  0.152253  1.035731  -9.104 -0.437750  0.07520  0.663925   8.257\n",
              "g-3    23814.0  0.081971  0.950012  -5.998 -0.429575  0.00805  0.463400  10.000\n",
              "g-4    23814.0  0.057347  1.032091  -6.369 -0.470925 -0.02690  0.465375  10.000\n",
              "...        ...       ...       ...     ...       ...      ...       ...     ...\n",
              "g-767  23814.0 -0.076251  1.115477 -10.000 -0.506200  0.00990  0.511175   6.317\n",
              "g-768  23814.0  0.134162  0.951264  -4.269 -0.353100  0.00540  0.409075  10.000\n",
              "g-769  23814.0 -0.128018  1.230636 -10.000 -0.544600  0.00060  0.498500   5.911\n",
              "g-770  23814.0 -0.219210  1.326193 -10.000 -0.554400  0.02870  0.496400  10.000\n",
              "g-771  23814.0  0.101524  1.417674 -10.000 -0.523800 -0.00650  0.536950  10.000\n",
              "\n",
              "[772 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "8tlmfesT-WeG",
        "outputId": "433ed414-0d1b-4371-e4c8-2ebd720bfeaf"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['mean'].hist(bins=30)"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e19cda490>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "IQ0flQP3-5SL",
        "outputId": "8a404bf9-0d81-4e22-98ab-d65ff006d542"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['min'].hist(bins=30)"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e1a108790>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "uChXoovN_Bhj",
        "outputId": "7ced283c-f929-4d56-f41b-16b8ff190c06"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['max'].hist(bins=30)"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e29d80cd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "W-Z83vTZA5O3",
        "outputId": "6c92417b-46af-463a-e05d-c8473dbd5fc1"
      },
      "source": [
        "dados.loc[:,'c-0':'c-99'].describe().T['mean'].hist(bins=30)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e19c9a050>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "FH_Rw2sCGvfe",
        "outputId": "10f1e4be-33cf-44b5-a899-db91c3babcf8"
      },
      "source": [
        "sns.boxplot(x='g-0', data=dados)"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e19acaf50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "TluogkCuoyjj",
        "outputId": "1da6aee8-82ba-4446-8bc4-2d1be5953428"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.boxplot(y='g-0', x='tratamento', data=dados)"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e19b41e10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z2HxipcqlMBj"
      },
      "source": [
        "##Desafio 01: \n",
        "### Ordenar o grafico countplot."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "id": "xzghIGKgpkFn",
        "outputId": "6fcabb8b-e821-4f02-c25f-71c2449b1f31"
      },
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "sns.set()\n",
        "plt.figure (figsize=(8,6))\n",
        "ax = sns.countplot(x = 'composto', data = dados.query('composto in @cod_compostos'), order = cod_compostos)\n",
        "ax.set_title ('Top 5 compostos')\n",
        "plt.show()"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VuJfCocXsAxp"
      },
      "source": [
        "##Desafio 02:\n",
        " ### Melhorar a visualização alterando tamanho da fonte..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "rwrYbxoXsL-B",
        "outputId": "93e315b6-f3de-4189-fcda-ed96b2468892"
      },
      "source": [
        "cod_compostos = dados['composto'].value_counts().index[0:5:1] #crescente\n",
        "\n",
        "sns.set()\n",
        "plt.figure(figsize=(8,6))\n",
        "data=dados.query('composto in @cod_compostos')\n",
        "\n",
        "ax = sns.countplot(x = 'composto', data=data, order=cod_compostos, palette = 'pastel')\n",
        "ax.set_title('Top 5 compostos', fontsize=16, color='black')\n",
        "ax.set_ylabel('Count', fontsize=16, color='black')\n",
        "ax.set_xlabel('Composto', fontsize=16, color='black')\n",
        "plt.show()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hGc3klN00cQM"
      },
      "source": [
        "## Desafio 03: \n",
        "### Plotar os histogramas com seaborn"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "ZmA9f_0-0riT",
        "outputId": "1a3b93d7-eb72-418f-a7a1-484218079724"
      },
      "source": [
        "plt.figure(figsize=(12, 6))\n",
        "hist = sns.histplot(dados, x = dados['g-0'], bins = 50, color = 'darkblue', kde = True)\n",
        "hist.set_title('G-0', fontsize=16, color='black')\n",
        "plt.show()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7kfASxxI6tt2"
      },
      "source": [
        "##Desafio 04: \n",
        "### Estudar sobre as estaticas retornadas no .describe()"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pY1s_4Jw8_wZ",
        "outputId": "63b977cc-0aa3-482b-9db8-2df0625f8bcd"
      },
      "source": [
        "dados['g-0'].describe()"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    23814.000000\n",
              "mean         0.248366\n",
              "std          1.393399\n",
              "min         -5.513000\n",
              "25%         -0.473075\n",
              "50%         -0.008850\n",
              "75%          0.525700\n",
              "max         10.000000\n",
              "Name: g-0, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZWxQ1Fwi7sZo"
      },
      "source": [
        "\n",
        "*   count = contagem de quantos elementos existem na série.\n",
        "*   mean = média aritmética dos valores da série.\n",
        "*   std = desvio-padrão amostral dos valores da série.\n",
        "*   min = menor valor da série.\n",
        "*   25% = valor cuja posição separa os dados na proporção (25%,75%), ou seja, 25% dos valores da série são menores que este valor e 75% dos valores são maiores que este. Em estatística, este valor é chamado de 1º quantil.\n",
        "*   50% = valor cuja posição separa os dados na proporção (50%,50%). Chamado de 2º quantil ou mediana.\n",
        "\n",
        "*   75% = valor cuja posição separa os dados na proporção (75%,25%). Chamado de 3º quantil.\n",
        "*   max = maior valor da série.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eA6WQPkV9Mft"
      },
      "source": [
        "##Desafio 05:\n",
        "### Refletir sobre a manipulação do tamanho das visualizações."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uvefVg2nT4F5"
      },
      "source": [
        "Quando está desenvolvendo um grafico para analises e necessario observar as mudanças no tamanho dos graficos pois pode ocasionar efeitos visuais que levam a interpretações errôneas.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_R7lkjfTOQ9T"
      },
      "source": [
        "##Desafio 06: \n",
        "### Fazer outras analises com o boxplot e até com o histograma.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "JFXCeERDOoRF",
        "outputId": "bbb6ff3a-ea01-4b49-d92f-3bdde8f70434"
      },
      "source": [
        "fig, ax = plt.subplots(3, constrained_layout=True, figsize =(12,15))\n",
        "\n",
        "ax1 = sns.boxplot(x='g-10', y='tratamento', data=dados, ax=ax[0], color='lightsalmon')\n",
        "ax[0].set_xlabel('\\ng-10', fontsize=12)\n",
        "ax[0].set_ylabel('Tratamentos\\n', fontsize=12)\n",
        "ax[0].set_title('Distribuição dos Tratamentos', family='san-serif', fontsize=20)\n",
        "\n",
        "ax2 = sns.boxplot(x='g-10', y='dose', data=dados, ax=ax[1], color='lightblue')\n",
        "ax[1].set_xlabel('\\ng-10', fontsize=12)\n",
        "ax[1].set_ylabel('Doses\\n', fontsize=12)\n",
        "ax[1].set_title('Distribuição dos Doses', family='san-serif', fontsize=20)\n",
        "\n",
        "ax3 = sns.boxplot(x='tempo', y='g-10', data=dados, ax=ax[2], color='lightgreen')\n",
        "ax[2].set_xlabel('\\nTempos', fontsize=12)\n",
        "ax[2].set_ylabel('g-10\\n', fontsize=12)\n",
        "ax[2].set_title('Distribuição dos Tempos', family='san-serif', fontsize=20)"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distribuição dos Tempos')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "stream",
          "text": [
            "findfont: Font family ['san-serif'] not found. Falling back to DejaVu Sans.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x1080 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EoxAPzX_TWav"
      },
      "source": [
        "##Desafio 07: \n",
        "###Resumo do que você aprendeu com os dados."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W9SJ0SpTTaFA"
      },
      "source": [
        "\n",
        "\n",
        "*   Uso da ferramenta seaborn para graficos em Python.\n",
        "*   Entender oque e informado pela função describe.\n",
        "*   O tamanho do gráfico é um parâmetro importante para uma boa visualização. Existem boas práticas para isso. Deve-se buscar um bom tamanho para que o mesmo não fique distorcido, e não oculte ou dificulte a visão das informações que são relevantes.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    }
  ]
}