Aula03.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Aula03.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOdrXNJWzRkw5nCDGjOijH4",
      "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/malumelo7/imersaoDados/blob/main/Aula03.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aI6J8rJyzwaG"
      },
      "source": [
        "###Tratamento da database"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "id": "h0PrtDCPzgzU",
        "outputId": "145c472b-bc66-432d-cbeb-ebb5860249d2"
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "dados = pd.read_csv('https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true', compression = 'zip')\n",
        "dados"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <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",
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              "      <th>c-61</th>\n",
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              "      <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",
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              "      <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": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "id": "Ao7f_Ng7znJu",
        "outputId": "f500867a-8e80-4476-b644-9be7b3ed96df"
      },
      "source": [
        "dados.rename(columns = {'droga':'composto'}, inplace = True)\n",
        "dados"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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",
              "    <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": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 252
        },
        "id": "n22LDRbkzrld",
        "outputId": "b43150c6-2593-4a42-ca06-9e02b394b22f"
      },
      "source": [
        "novo_nome_coluna = []\n",
        "nome_das_colunas = dados.columns\n",
        "for coluna in nome_das_colunas:\n",
        "  coluna = coluna.replace('-','_')\n",
        "  novo_nome_coluna.append(coluna)\n",
        "dados.columns = novo_nome_coluna\n",
        "\n",
        "dados.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "</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": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JV6tdXtc04o6"
      },
      "source": [
        "###Making Crosstab between 'dose' and 'tempo'"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "id": "9Z_Czm491BuW",
        "outputId": "8bfc1a7d-4f49-4c8b-f46d-84e4c423c096"
      },
      "source": [
        "pd.crosstab(dados['dose'], dados['tempo'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>tempo</th>\n",
              "      <th>24</th>\n",
              "      <th>48</th>\n",
              "      <th>72</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>D1</th>\n",
              "      <td>3886</td>\n",
              "      <td>4354</td>\n",
              "      <td>3907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>3886</td>\n",
              "      <td>3896</td>\n",
              "      <td>3885</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tempo    24    48    72\n",
              "dose                   \n",
              "D1     3886  4354  3907\n",
              "D2     3886  3896  3885"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "Jq2YBOVl1Tml",
        "outputId": "190348a2-899a-4a38-d6fe-12fc3805daeb"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>301</td>\n",
              "      <td>3585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>343</td>\n",
              "      <td>4011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>307</td>\n",
              "      <td>3600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>305</td>\n",
              "      <td>3581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>305</td>\n",
              "      <td>3591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>305</td>\n",
              "      <td>3580</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24              301       3585\n",
              "     48              343       4011\n",
              "     72              307       3600\n",
              "D2   24              305       3581\n",
              "     48              305       3591\n",
              "     72              305       3580"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-wPKclhC42Th"
      },
      "source": [
        "Nesse caso, podemos observar o quantitativo para com dose e com controle, e podemos ver que eles são balanceados na coluna, mas quando comparamos \"com dose\" e \"com controle\" não é balanceado (10x mais)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "8QPhHcbY2ac1",
        "outputId": "c344be1f-9cf3-40b2-f86f-26681de15c2c"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.012640</td>\n",
              "      <td>0.150542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.014403</td>\n",
              "      <td>0.168430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.012892</td>\n",
              "      <td>0.151172</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150374</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150332</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.012640   0.150542\n",
              "     48         0.014403   0.168430\n",
              "     72         0.012892   0.151172\n",
              "D2   24         0.012808   0.150374\n",
              "     48         0.012808   0.150794\n",
              "     72         0.012808   0.150332"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xmYU48S85Kf7"
      },
      "source": [
        "Nesse caso, o normaliza = True indica que o valor de 100% são todos os dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "768UL6na3gJl",
        "outputId": "d69cc64b-17a7-4fae-9c3d-438bfbbb6ca1"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize='index')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.077458</td>\n",
              "      <td>0.922542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.078778</td>\n",
              "      <td>0.921222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.078577</td>\n",
              "      <td>0.921423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.078487</td>\n",
              "      <td>0.921513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.078285</td>\n",
              "      <td>0.921715</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.078507</td>\n",
              "      <td>0.921493</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.077458   0.922542\n",
              "     48         0.078778   0.921222\n",
              "     72         0.078577   0.921423\n",
              "D2   24         0.078487   0.921513\n",
              "     48         0.078285   0.921715\n",
              "     72         0.078507   0.921493"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "awJ301tM5Q_M"
      },
      "source": [
        "Nesse caso o somatório da linha tem que dá 100%"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "f9Sn62mj4rXd",
        "outputId": "b2a46c7e-aac8-440e-b080-ed578dba2ea6"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g_0'],aggfunc='mean')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>-0.251760</td>\n",
              "      <td>0.367996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>-0.122773</td>\n",
              "      <td>0.412469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>-0.295271</td>\n",
              "      <td>0.286250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.010754</td>\n",
              "      <td>0.115253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.013174</td>\n",
              "      <td>0.214480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.070250</td>\n",
              "      <td>0.253439</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24        -0.251760   0.367996\n",
              "     48        -0.122773   0.412469\n",
              "     72        -0.295271   0.286250\n",
              "D2   24         0.010754   0.115253\n",
              "     48         0.013174   0.214480\n",
              "     72         0.070250   0.253439"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "mIJ7zjfzB6yt",
        "outputId": "3789def7-e6c4-4381-faef-bb2375e92883"
      },
      "source": [
        "dados[['g_0', 'g_3']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g_0</th>\n",
              "      <th>g_3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0620</td>\n",
              "      <td>-0.6208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.0604</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6280</td>\n",
              "      <td>-0.0764</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.5138</td>\n",
              "      <td>0.5288</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.3254</td>\n",
              "      <td>0.6919</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>-0.5080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.9905</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>0.3942</td>\n",
              "      <td>-0.7389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2044</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>-0.8598</td>\n",
              "      <td>0.7952</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          g_0     g_3\n",
              "0      1.0620 -0.6208\n",
              "1      0.0743  0.0604\n",
              "2      0.6280 -0.0764\n",
              "3     -0.5138  0.5288\n",
              "4     -0.3254  0.6919\n",
              "...       ...     ...\n",
              "23809  0.1394 -0.5080\n",
              "23810 -1.3260  0.9905\n",
              "23811  0.3942 -0.7389\n",
              "23812  0.6660  0.2044\n",
              "23813 -0.8598  0.7952\n",
              "\n",
              "[23814 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "ARnYyx6R-XCt",
        "outputId": "bd506012-b26a-41bf-cacc-62d7b1384293"
      },
      "source": [
        "sns.scatterplot(x='g_0', y='g_3', data=dados)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa390314a50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "--JH2EYtCvfj",
        "outputId": "e0289086-59d1-4af9-8af1-b609e9963b6a"
      },
      "source": [
        "sns.scatterplot(x='g_0', y='g_8', data=dados)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa38538d110>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "tMNl4LH5Da4T",
        "outputId": "d88a7963-d731-4bb6-cd26-19acd089150f"
      },
      "source": [
        "sns.lmplot(data=dados, x='g_0', y='g_8', line_kws={'color':'red'})"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fa385903ed0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 975
        },
        "id": "CM6oCzrRD_Xa",
        "outputId": "798ba76b-45eb-4ff8-81f3-d215f04af41c"
      },
      "source": [
        "sns.lmplot(data=dados, x='g_0', y='g_8', line_kws={'color':'red'}, col='tratamento', row='tempo')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fa3854f3110>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x1080 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uso5MiLVF8FX"
      },
      "source": [
        "Com o passar do tempo, a inclinação foi aumentando, consequentemente o efeito do tratamento foi aumentando. E a com controle foi ficando estável, que é o que busca!!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZJXFETOdKJcg"
      },
      "source": [
        "###Fazendo correlações"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "id": "W6-m6ExnE5eM",
        "outputId": "129fd8f1-9182-45b4-a18b-bce4290b8b19"
      },
      "source": [
        "dados.loc[:, 'g_0':'g_771'].corr()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>g_0</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.086032</td>\n",
              "      <td>0.176188</td>\n",
              "      <td>0.011266</td>\n",
              "      <td>0.403153</td>\n",
              "      <td>-0.165478</td>\n",
              "      <td>0.238348</td>\n",
              "      <td>-0.374451</td>\n",
              "      <td>-0.604212</td>\n",
              "      <td>-0.428779</td>\n",
              "      <td>-0.547606</td>\n",
              "      <td>0.219762</td>\n",
              "      <td>-0.199453</td>\n",
              "      <td>0.472223</td>\n",
              "      <td>-0.346179</td>\n",
              "      <td>-0.201323</td>\n",
              "      <td>-0.513026</td>\n",
              "      <td>-0.433536</td>\n",
              "      <td>-0.002073</td>\n",
              "      <td>-0.074622</td>\n",
              "      <td>-0.468599</td>\n",
              "      <td>0.052445</td>\n",
              "      <td>0.022269</td>\n",
              "      <td>-0.076298</td>\n",
              "      <td>-0.337522</td>\n",
              "      <td>-0.235191</td>\n",
              "      <td>-0.422814</td>\n",
              "      <td>0.148432</td>\n",
              "      <td>-0.471092</td>\n",
              "      <td>-0.296871</td>\n",
              "      <td>-0.528327</td>\n",
              "      <td>0.558136</td>\n",
              "      <td>-0.133229</td>\n",
              "      <td>-0.155987</td>\n",
              "      <td>-0.120247</td>\n",
              "      <td>0.327593</td>\n",
              "      <td>-0.147800</td>\n",
              "      <td>-0.591868</td>\n",
              "      <td>0.602623</td>\n",
              "      <td>0.450769</td>\n",
              "      <td>...</td>\n",
              "      <td>0.365095</td>\n",
              "      <td>-0.528006</td>\n",
              "      <td>0.295970</td>\n",
              "      <td>0.067108</td>\n",
              "      <td>-0.250243</td>\n",
              "      <td>-0.110665</td>\n",
              "      <td>-0.214344</td>\n",
              "      <td>-0.280492</td>\n",
              "      <td>-0.036098</td>\n",
              "      <td>-0.128288</td>\n",
              "      <td>-0.498922</td>\n",
              "      <td>-0.469595</td>\n",
              "      <td>0.673664</td>\n",
              "      <td>0.538050</td>\n",
              "      <td>0.297528</td>\n",
              "      <td>0.066530</td>\n",
              "      <td>0.240252</td>\n",
              "      <td>-0.170949</td>\n",
              "      <td>0.485924</td>\n",
              "      <td>-0.093815</td>\n",
              "      <td>0.397476</td>\n",
              "      <td>0.017923</td>\n",
              "      <td>0.321260</td>\n",
              "      <td>-0.131709</td>\n",
              "      <td>-0.133430</td>\n",
              "      <td>0.178220</td>\n",
              "      <td>0.201902</td>\n",
              "      <td>-0.205648</td>\n",
              "      <td>-0.676835</td>\n",
              "      <td>-0.433554</td>\n",
              "      <td>0.005085</td>\n",
              "      <td>-0.239410</td>\n",
              "      <td>0.548401</td>\n",
              "      <td>0.425222</td>\n",
              "      <td>-0.308095</td>\n",
              "      <td>-0.052622</td>\n",
              "      <td>0.300241</td>\n",
              "      <td>-0.127375</td>\n",
              "      <td>-0.514201</td>\n",
              "      <td>0.405908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_1</th>\n",
              "      <td>0.086032</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.054518</td>\n",
              "      <td>-0.027855</td>\n",
              "      <td>0.193647</td>\n",
              "      <td>-0.151590</td>\n",
              "      <td>-0.122541</td>\n",
              "      <td>0.144537</td>\n",
              "      <td>-0.009973</td>\n",
              "      <td>-0.047558</td>\n",
              "      <td>-0.009051</td>\n",
              "      <td>0.161274</td>\n",
              "      <td>0.037178</td>\n",
              "      <td>-0.009256</td>\n",
              "      <td>0.002632</td>\n",
              "      <td>-0.070193</td>\n",
              "      <td>-0.063414</td>\n",
              "      <td>-0.000944</td>\n",
              "      <td>-0.023748</td>\n",
              "      <td>-0.034714</td>\n",
              "      <td>-0.131031</td>\n",
              "      <td>0.196596</td>\n",
              "      <td>-0.061441</td>\n",
              "      <td>0.090620</td>\n",
              "      <td>-0.004299</td>\n",
              "      <td>-0.032600</td>\n",
              "      <td>-0.019435</td>\n",
              "      <td>0.015661</td>\n",
              "      <td>-0.098907</td>\n",
              "      <td>-0.091071</td>\n",
              "      <td>-0.053331</td>\n",
              "      <td>-0.049514</td>\n",
              "      <td>0.187382</td>\n",
              "      <td>-0.091232</td>\n",
              "      <td>0.045417</td>\n",
              "      <td>0.044373</td>\n",
              "      <td>-0.077671</td>\n",
              "      <td>-0.005265</td>\n",
              "      <td>-0.042213</td>\n",
              "      <td>0.050546</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.015556</td>\n",
              "      <td>-0.017184</td>\n",
              "      <td>0.043104</td>\n",
              "      <td>-0.189662</td>\n",
              "      <td>-0.050194</td>\n",
              "      <td>-0.007878</td>\n",
              "      <td>-0.083539</td>\n",
              "      <td>-0.042175</td>\n",
              "      <td>0.014307</td>\n",
              "      <td>-0.134166</td>\n",
              "      <td>-0.026985</td>\n",
              "      <td>0.088382</td>\n",
              "      <td>-0.077453</td>\n",
              "      <td>0.015545</td>\n",
              "      <td>-0.027527</td>\n",
              "      <td>-0.071078</td>\n",
              "      <td>-0.095445</td>\n",
              "      <td>0.049612</td>\n",
              "      <td>-0.040518</td>\n",
              "      <td>-0.074277</td>\n",
              "      <td>-0.022356</td>\n",
              "      <td>0.125763</td>\n",
              "      <td>-0.082779</td>\n",
              "      <td>0.020292</td>\n",
              "      <td>-0.023171</td>\n",
              "      <td>-0.207192</td>\n",
              "      <td>-0.066570</td>\n",
              "      <td>-0.057007</td>\n",
              "      <td>0.002062</td>\n",
              "      <td>0.029795</td>\n",
              "      <td>-0.205998</td>\n",
              "      <td>0.060051</td>\n",
              "      <td>0.115071</td>\n",
              "      <td>0.160140</td>\n",
              "      <td>0.015098</td>\n",
              "      <td>-0.003378</td>\n",
              "      <td>-0.030756</td>\n",
              "      <td>-0.006866</td>\n",
              "      <td>-0.095108</td>\n",
              "      <td>-0.032233</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_2</th>\n",
              "      <td>0.176188</td>\n",
              "      <td>-0.054518</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.042633</td>\n",
              "      <td>0.013968</td>\n",
              "      <td>0.018516</td>\n",
              "      <td>0.015190</td>\n",
              "      <td>-0.144205</td>\n",
              "      <td>-0.128029</td>\n",
              "      <td>-0.081332</td>\n",
              "      <td>-0.105050</td>\n",
              "      <td>0.011198</td>\n",
              "      <td>-0.063501</td>\n",
              "      <td>0.082011</td>\n",
              "      <td>-0.082204</td>\n",
              "      <td>-0.059607</td>\n",
              "      <td>-0.137811</td>\n",
              "      <td>-0.085491</td>\n",
              "      <td>0.053335</td>\n",
              "      <td>0.028813</td>\n",
              "      <td>-0.061160</td>\n",
              "      <td>-0.129131</td>\n",
              "      <td>-0.007426</td>\n",
              "      <td>-0.034230</td>\n",
              "      <td>-0.128312</td>\n",
              "      <td>-0.067363</td>\n",
              "      <td>-0.126554</td>\n",
              "      <td>0.036984</td>\n",
              "      <td>-0.129481</td>\n",
              "      <td>-0.017941</td>\n",
              "      <td>-0.152288</td>\n",
              "      <td>0.172191</td>\n",
              "      <td>-0.100086</td>\n",
              "      <td>-0.033010</td>\n",
              "      <td>-0.015481</td>\n",
              "      <td>0.001098</td>\n",
              "      <td>-0.020374</td>\n",
              "      <td>-0.157977</td>\n",
              "      <td>0.169464</td>\n",
              "      <td>0.144449</td>\n",
              "      <td>...</td>\n",
              "      <td>0.089525</td>\n",
              "      <td>-0.140916</td>\n",
              "      <td>0.008587</td>\n",
              "      <td>0.042106</td>\n",
              "      <td>-0.018846</td>\n",
              "      <td>-0.008093</td>\n",
              "      <td>-0.074404</td>\n",
              "      <td>-0.080120</td>\n",
              "      <td>-0.020085</td>\n",
              "      <td>-0.028099</td>\n",
              "      <td>-0.098775</td>\n",
              "      <td>-0.113000</td>\n",
              "      <td>0.175916</td>\n",
              "      <td>0.119166</td>\n",
              "      <td>0.071051</td>\n",
              "      <td>0.025358</td>\n",
              "      <td>0.078971</td>\n",
              "      <td>-0.086326</td>\n",
              "      <td>0.149456</td>\n",
              "      <td>0.033432</td>\n",
              "      <td>0.124239</td>\n",
              "      <td>-0.006327</td>\n",
              "      <td>0.120148</td>\n",
              "      <td>-0.041162</td>\n",
              "      <td>-0.030040</td>\n",
              "      <td>0.048549</td>\n",
              "      <td>0.096369</td>\n",
              "      <td>0.000494</td>\n",
              "      <td>-0.172627</td>\n",
              "      <td>-0.130200</td>\n",
              "      <td>0.090115</td>\n",
              "      <td>-0.055655</td>\n",
              "      <td>0.138085</td>\n",
              "      <td>0.061574</td>\n",
              "      <td>-0.093631</td>\n",
              "      <td>-0.053149</td>\n",
              "      <td>0.115415</td>\n",
              "      <td>0.014489</td>\n",
              "      <td>-0.078661</td>\n",
              "      <td>0.103985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_3</th>\n",
              "      <td>0.011266</td>\n",
              "      <td>-0.027855</td>\n",
              "      <td>0.042633</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.033039</td>\n",
              "      <td>0.042231</td>\n",
              "      <td>-0.043177</td>\n",
              "      <td>-0.175692</td>\n",
              "      <td>-0.086167</td>\n",
              "      <td>-0.014052</td>\n",
              "      <td>-0.074101</td>\n",
              "      <td>0.181024</td>\n",
              "      <td>0.030539</td>\n",
              "      <td>0.192727</td>\n",
              "      <td>0.128792</td>\n",
              "      <td>-0.045688</td>\n",
              "      <td>0.033974</td>\n",
              "      <td>-0.070920</td>\n",
              "      <td>0.237669</td>\n",
              "      <td>0.112392</td>\n",
              "      <td>0.027867</td>\n",
              "      <td>-0.167263</td>\n",
              "      <td>0.197013</td>\n",
              "      <td>-0.049480</td>\n",
              "      <td>-0.113336</td>\n",
              "      <td>0.175615</td>\n",
              "      <td>0.111355</td>\n",
              "      <td>0.007168</td>\n",
              "      <td>-0.022381</td>\n",
              "      <td>-0.128269</td>\n",
              "      <td>-0.042827</td>\n",
              "      <td>0.098416</td>\n",
              "      <td>-0.091962</td>\n",
              "      <td>-0.083806</td>\n",
              "      <td>0.184985</td>\n",
              "      <td>-0.070933</td>\n",
              "      <td>-0.317859</td>\n",
              "      <td>-0.228039</td>\n",
              "      <td>0.084346</td>\n",
              "      <td>0.054827</td>\n",
              "      <td>...</td>\n",
              "      <td>0.039519</td>\n",
              "      <td>0.000851</td>\n",
              "      <td>0.011655</td>\n",
              "      <td>-0.116724</td>\n",
              "      <td>0.304819</td>\n",
              "      <td>-0.087159</td>\n",
              "      <td>-0.134135</td>\n",
              "      <td>-0.031211</td>\n",
              "      <td>0.174116</td>\n",
              "      <td>0.060289</td>\n",
              "      <td>-0.119276</td>\n",
              "      <td>-0.140391</td>\n",
              "      <td>0.110547</td>\n",
              "      <td>0.145925</td>\n",
              "      <td>0.155011</td>\n",
              "      <td>0.049182</td>\n",
              "      <td>-0.007754</td>\n",
              "      <td>-0.128488</td>\n",
              "      <td>0.078139</td>\n",
              "      <td>0.012422</td>\n",
              "      <td>0.040728</td>\n",
              "      <td>0.164467</td>\n",
              "      <td>0.171886</td>\n",
              "      <td>-0.069777</td>\n",
              "      <td>0.066560</td>\n",
              "      <td>0.102111</td>\n",
              "      <td>-0.036922</td>\n",
              "      <td>0.111994</td>\n",
              "      <td>-0.133740</td>\n",
              "      <td>-0.226928</td>\n",
              "      <td>0.075982</td>\n",
              "      <td>0.178422</td>\n",
              "      <td>0.016467</td>\n",
              "      <td>-0.089317</td>\n",
              "      <td>-0.166426</td>\n",
              "      <td>-0.179370</td>\n",
              "      <td>0.028452</td>\n",
              "      <td>-0.206077</td>\n",
              "      <td>-0.002142</td>\n",
              "      <td>0.058219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_4</th>\n",
              "      <td>0.403153</td>\n",
              "      <td>0.193647</td>\n",
              "      <td>0.013968</td>\n",
              "      <td>-0.033039</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.057449</td>\n",
              "      <td>0.206405</td>\n",
              "      <td>-0.032748</td>\n",
              "      <td>-0.474828</td>\n",
              "      <td>-0.274167</td>\n",
              "      <td>-0.458021</td>\n",
              "      <td>0.116467</td>\n",
              "      <td>-0.207078</td>\n",
              "      <td>0.210440</td>\n",
              "      <td>-0.307280</td>\n",
              "      <td>0.019531</td>\n",
              "      <td>-0.275700</td>\n",
              "      <td>-0.422889</td>\n",
              "      <td>-0.012207</td>\n",
              "      <td>-0.088152</td>\n",
              "      <td>-0.311798</td>\n",
              "      <td>0.286106</td>\n",
              "      <td>-0.055368</td>\n",
              "      <td>-0.113396</td>\n",
              "      <td>-0.120743</td>\n",
              "      <td>-0.233682</td>\n",
              "      <td>-0.340708</td>\n",
              "      <td>0.070292</td>\n",
              "      <td>-0.360274</td>\n",
              "      <td>-0.225461</td>\n",
              "      <td>-0.402256</td>\n",
              "      <td>0.324362</td>\n",
              "      <td>0.091731</td>\n",
              "      <td>-0.052787</td>\n",
              "      <td>-0.073490</td>\n",
              "      <td>0.195062</td>\n",
              "      <td>-0.124394</td>\n",
              "      <td>-0.277002</td>\n",
              "      <td>0.285256</td>\n",
              "      <td>0.300517</td>\n",
              "      <td>...</td>\n",
              "      <td>0.215930</td>\n",
              "      <td>-0.292602</td>\n",
              "      <td>-0.008241</td>\n",
              "      <td>-0.005070</td>\n",
              "      <td>-0.284391</td>\n",
              "      <td>-0.116918</td>\n",
              "      <td>-0.252399</td>\n",
              "      <td>-0.250280</td>\n",
              "      <td>0.000141</td>\n",
              "      <td>-0.172896</td>\n",
              "      <td>-0.324769</td>\n",
              "      <td>-0.291644</td>\n",
              "      <td>0.302912</td>\n",
              "      <td>0.222951</td>\n",
              "      <td>0.144028</td>\n",
              "      <td>-0.020950</td>\n",
              "      <td>0.129354</td>\n",
              "      <td>-0.141319</td>\n",
              "      <td>0.215713</td>\n",
              "      <td>-0.060261</td>\n",
              "      <td>0.240649</td>\n",
              "      <td>-0.250950</td>\n",
              "      <td>0.144547</td>\n",
              "      <td>-0.045769</td>\n",
              "      <td>-0.083932</td>\n",
              "      <td>-0.100498</td>\n",
              "      <td>0.118725</td>\n",
              "      <td>-0.257704</td>\n",
              "      <td>-0.386764</td>\n",
              "      <td>-0.172222</td>\n",
              "      <td>-0.023752</td>\n",
              "      <td>-0.164868</td>\n",
              "      <td>0.404440</td>\n",
              "      <td>0.317500</td>\n",
              "      <td>-0.225094</td>\n",
              "      <td>0.124425</td>\n",
              "      <td>0.115579</td>\n",
              "      <td>-0.172727</td>\n",
              "      <td>-0.363673</td>\n",
              "      <td>0.250713</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>g_767</th>\n",
              "      <td>-0.052622</td>\n",
              "      <td>-0.003378</td>\n",
              "      <td>-0.053149</td>\n",
              "      <td>-0.179370</td>\n",
              "      <td>0.124425</td>\n",
              "      <td>-0.081016</td>\n",
              "      <td>-0.000886</td>\n",
              "      <td>0.137336</td>\n",
              "      <td>-0.101191</td>\n",
              "      <td>-0.013157</td>\n",
              "      <td>-0.016431</td>\n",
              "      <td>-0.009570</td>\n",
              "      <td>-0.102954</td>\n",
              "      <td>-0.066698</td>\n",
              "      <td>-0.093822</td>\n",
              "      <td>0.244340</td>\n",
              "      <td>-0.069415</td>\n",
              "      <td>-0.094064</td>\n",
              "      <td>-0.127133</td>\n",
              "      <td>-0.080124</td>\n",
              "      <td>0.043800</td>\n",
              "      <td>0.077647</td>\n",
              "      <td>-0.163991</td>\n",
              "      <td>-0.007126</td>\n",
              "      <td>-0.059084</td>\n",
              "      <td>-0.105259</td>\n",
              "      <td>-0.023880</td>\n",
              "      <td>0.128335</td>\n",
              "      <td>-0.119971</td>\n",
              "      <td>-0.107446</td>\n",
              "      <td>-0.035556</td>\n",
              "      <td>0.094170</td>\n",
              "      <td>0.158429</td>\n",
              "      <td>0.108885</td>\n",
              "      <td>-0.077054</td>\n",
              "      <td>-0.067268</td>\n",
              "      <td>0.334189</td>\n",
              "      <td>0.217292</td>\n",
              "      <td>0.049036</td>\n",
              "      <td>-0.031135</td>\n",
              "      <td>...</td>\n",
              "      <td>0.052898</td>\n",
              "      <td>0.121333</td>\n",
              "      <td>-0.038647</td>\n",
              "      <td>0.140140</td>\n",
              "      <td>-0.246716</td>\n",
              "      <td>0.000084</td>\n",
              "      <td>-0.021733</td>\n",
              "      <td>-0.003739</td>\n",
              "      <td>-0.010499</td>\n",
              "      <td>-0.045364</td>\n",
              "      <td>0.103892</td>\n",
              "      <td>0.056790</td>\n",
              "      <td>-0.046818</td>\n",
              "      <td>-0.082454</td>\n",
              "      <td>-0.050249</td>\n",
              "      <td>0.043764</td>\n",
              "      <td>0.028057</td>\n",
              "      <td>0.107099</td>\n",
              "      <td>0.006368</td>\n",
              "      <td>0.071568</td>\n",
              "      <td>-0.041222</td>\n",
              "      <td>-0.271532</td>\n",
              "      <td>-0.134224</td>\n",
              "      <td>0.100008</td>\n",
              "      <td>0.023745</td>\n",
              "      <td>-0.179493</td>\n",
              "      <td>0.113520</td>\n",
              "      <td>-0.331936</td>\n",
              "      <td>-0.050898</td>\n",
              "      <td>0.190015</td>\n",
              "      <td>-0.010391</td>\n",
              "      <td>-0.180252</td>\n",
              "      <td>0.003976</td>\n",
              "      <td>-0.027425</td>\n",
              "      <td>0.153722</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.048393</td>\n",
              "      <td>0.065450</td>\n",
              "      <td>0.008603</td>\n",
              "      <td>-0.001136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_768</th>\n",
              "      <td>0.300241</td>\n",
              "      <td>-0.030756</td>\n",
              "      <td>0.115415</td>\n",
              "      <td>0.028452</td>\n",
              "      <td>0.115579</td>\n",
              "      <td>-0.139000</td>\n",
              "      <td>-0.005791</td>\n",
              "      <td>-0.419437</td>\n",
              "      <td>-0.209968</td>\n",
              "      <td>-0.291836</td>\n",
              "      <td>-0.279889</td>\n",
              "      <td>0.208202</td>\n",
              "      <td>-0.166361</td>\n",
              "      <td>0.243048</td>\n",
              "      <td>-0.241234</td>\n",
              "      <td>-0.042026</td>\n",
              "      <td>-0.363465</td>\n",
              "      <td>-0.247474</td>\n",
              "      <td>0.078093</td>\n",
              "      <td>-0.055035</td>\n",
              "      <td>-0.155576</td>\n",
              "      <td>-0.164930</td>\n",
              "      <td>-0.086306</td>\n",
              "      <td>-0.125517</td>\n",
              "      <td>-0.286908</td>\n",
              "      <td>-0.139057</td>\n",
              "      <td>-0.341518</td>\n",
              "      <td>0.102919</td>\n",
              "      <td>-0.257007</td>\n",
              "      <td>-0.141094</td>\n",
              "      <td>-0.372977</td>\n",
              "      <td>0.369303</td>\n",
              "      <td>-0.365516</td>\n",
              "      <td>0.058365</td>\n",
              "      <td>-0.062415</td>\n",
              "      <td>0.076001</td>\n",
              "      <td>-0.208400</td>\n",
              "      <td>-0.450344</td>\n",
              "      <td>0.463732</td>\n",
              "      <td>0.451185</td>\n",
              "      <td>...</td>\n",
              "      <td>0.234354</td>\n",
              "      <td>-0.463277</td>\n",
              "      <td>0.073003</td>\n",
              "      <td>0.006763</td>\n",
              "      <td>-0.143979</td>\n",
              "      <td>-0.034694</td>\n",
              "      <td>-0.171279</td>\n",
              "      <td>-0.200669</td>\n",
              "      <td>-0.031907</td>\n",
              "      <td>-0.057287</td>\n",
              "      <td>-0.288026</td>\n",
              "      <td>-0.177108</td>\n",
              "      <td>0.459642</td>\n",
              "      <td>0.291729</td>\n",
              "      <td>0.202785</td>\n",
              "      <td>-0.028499</td>\n",
              "      <td>0.130907</td>\n",
              "      <td>-0.233472</td>\n",
              "      <td>0.455238</td>\n",
              "      <td>0.141002</td>\n",
              "      <td>0.222363</td>\n",
              "      <td>0.074620</td>\n",
              "      <td>0.087545</td>\n",
              "      <td>-0.203831</td>\n",
              "      <td>-0.095647</td>\n",
              "      <td>0.048008</td>\n",
              "      <td>0.253031</td>\n",
              "      <td>0.087674</td>\n",
              "      <td>-0.403336</td>\n",
              "      <td>-0.394520</td>\n",
              "      <td>0.077292</td>\n",
              "      <td>0.000048</td>\n",
              "      <td>0.403211</td>\n",
              "      <td>0.241509</td>\n",
              "      <td>-0.250512</td>\n",
              "      <td>-0.048393</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.079364</td>\n",
              "      <td>-0.382607</td>\n",
              "      <td>0.351651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_769</th>\n",
              "      <td>-0.127375</td>\n",
              "      <td>-0.006866</td>\n",
              "      <td>0.014489</td>\n",
              "      <td>-0.206077</td>\n",
              "      <td>-0.172727</td>\n",
              "      <td>-0.068537</td>\n",
              "      <td>-0.278587</td>\n",
              "      <td>-0.082554</td>\n",
              "      <td>0.268571</td>\n",
              "      <td>0.037013</td>\n",
              "      <td>0.184833</td>\n",
              "      <td>0.029409</td>\n",
              "      <td>0.052328</td>\n",
              "      <td>-0.137248</td>\n",
              "      <td>-0.016769</td>\n",
              "      <td>0.006056</td>\n",
              "      <td>-0.010654</td>\n",
              "      <td>0.164345</td>\n",
              "      <td>-0.161975</td>\n",
              "      <td>-0.096549</td>\n",
              "      <td>0.043702</td>\n",
              "      <td>-0.160018</td>\n",
              "      <td>-0.104794</td>\n",
              "      <td>0.011050</td>\n",
              "      <td>-0.057823</td>\n",
              "      <td>-0.046833</td>\n",
              "      <td>0.015717</td>\n",
              "      <td>0.061872</td>\n",
              "      <td>0.107534</td>\n",
              "      <td>-0.032060</td>\n",
              "      <td>0.086102</td>\n",
              "      <td>-0.108052</td>\n",
              "      <td>-0.154845</td>\n",
              "      <td>0.120802</td>\n",
              "      <td>0.040181</td>\n",
              "      <td>-0.082272</td>\n",
              "      <td>0.087573</td>\n",
              "      <td>0.078753</td>\n",
              "      <td>-0.032600</td>\n",
              "      <td>-0.061331</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.049599</td>\n",
              "      <td>0.017176</td>\n",
              "      <td>-0.005283</td>\n",
              "      <td>0.017348</td>\n",
              "      <td>-0.014663</td>\n",
              "      <td>0.101831</td>\n",
              "      <td>0.063218</td>\n",
              "      <td>0.151088</td>\n",
              "      <td>-0.116813</td>\n",
              "      <td>0.060308</td>\n",
              "      <td>0.087342</td>\n",
              "      <td>0.214832</td>\n",
              "      <td>-0.118092</td>\n",
              "      <td>-0.038540</td>\n",
              "      <td>-0.095170</td>\n",
              "      <td>-0.031114</td>\n",
              "      <td>-0.064939</td>\n",
              "      <td>0.044082</td>\n",
              "      <td>0.009613</td>\n",
              "      <td>0.146667</td>\n",
              "      <td>-0.059447</td>\n",
              "      <td>0.087822</td>\n",
              "      <td>-0.160610</td>\n",
              "      <td>0.041946</td>\n",
              "      <td>-0.001705</td>\n",
              "      <td>-0.116414</td>\n",
              "      <td>-0.033614</td>\n",
              "      <td>-0.029173</td>\n",
              "      <td>0.106610</td>\n",
              "      <td>-0.002356</td>\n",
              "      <td>0.020662</td>\n",
              "      <td>0.071082</td>\n",
              "      <td>0.013235</td>\n",
              "      <td>0.021152</td>\n",
              "      <td>0.151940</td>\n",
              "      <td>0.065450</td>\n",
              "      <td>0.079364</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.135853</td>\n",
              "      <td>-0.083713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_770</th>\n",
              "      <td>-0.514201</td>\n",
              "      <td>-0.095108</td>\n",
              "      <td>-0.078661</td>\n",
              "      <td>-0.002142</td>\n",
              "      <td>-0.363673</td>\n",
              "      <td>0.144631</td>\n",
              "      <td>-0.143428</td>\n",
              "      <td>0.402451</td>\n",
              "      <td>0.441011</td>\n",
              "      <td>0.415967</td>\n",
              "      <td>0.550963</td>\n",
              "      <td>-0.238657</td>\n",
              "      <td>0.230249</td>\n",
              "      <td>-0.406279</td>\n",
              "      <td>0.386103</td>\n",
              "      <td>0.102904</td>\n",
              "      <td>0.406267</td>\n",
              "      <td>0.312653</td>\n",
              "      <td>-0.034036</td>\n",
              "      <td>0.091171</td>\n",
              "      <td>0.263679</td>\n",
              "      <td>-0.092925</td>\n",
              "      <td>0.008841</td>\n",
              "      <td>0.085105</td>\n",
              "      <td>0.370410</td>\n",
              "      <td>0.246689</td>\n",
              "      <td>0.550753</td>\n",
              "      <td>-0.190110</td>\n",
              "      <td>0.393393</td>\n",
              "      <td>0.295798</td>\n",
              "      <td>0.596868</td>\n",
              "      <td>-0.526634</td>\n",
              "      <td>0.231931</td>\n",
              "      <td>-0.039510</td>\n",
              "      <td>0.260259</td>\n",
              "      <td>-0.366389</td>\n",
              "      <td>0.228281</td>\n",
              "      <td>0.571426</td>\n",
              "      <td>-0.592994</td>\n",
              "      <td>-0.429418</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.370370</td>\n",
              "      <td>0.514880</td>\n",
              "      <td>-0.155936</td>\n",
              "      <td>-0.010076</td>\n",
              "      <td>0.375338</td>\n",
              "      <td>0.014833</td>\n",
              "      <td>0.343938</td>\n",
              "      <td>0.369822</td>\n",
              "      <td>0.077286</td>\n",
              "      <td>0.246165</td>\n",
              "      <td>0.439648</td>\n",
              "      <td>0.367189</td>\n",
              "      <td>-0.618890</td>\n",
              "      <td>-0.378256</td>\n",
              "      <td>-0.264342</td>\n",
              "      <td>0.081357</td>\n",
              "      <td>-0.240273</td>\n",
              "      <td>0.285457</td>\n",
              "      <td>-0.468321</td>\n",
              "      <td>0.077384</td>\n",
              "      <td>-0.270256</td>\n",
              "      <td>-0.015109</td>\n",
              "      <td>-0.077811</td>\n",
              "      <td>0.206666</td>\n",
              "      <td>0.238529</td>\n",
              "      <td>-0.184568</td>\n",
              "      <td>-0.126731</td>\n",
              "      <td>0.034281</td>\n",
              "      <td>0.601289</td>\n",
              "      <td>0.488580</td>\n",
              "      <td>0.014331</td>\n",
              "      <td>-0.010849</td>\n",
              "      <td>-0.498222</td>\n",
              "      <td>-0.489116</td>\n",
              "      <td>0.284882</td>\n",
              "      <td>0.008603</td>\n",
              "      <td>-0.382607</td>\n",
              "      <td>0.135853</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.425063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_771</th>\n",
              "      <td>0.405908</td>\n",
              "      <td>-0.032233</td>\n",
              "      <td>0.103985</td>\n",
              "      <td>0.058219</td>\n",
              "      <td>0.250713</td>\n",
              "      <td>-0.093237</td>\n",
              "      <td>0.075019</td>\n",
              "      <td>-0.441309</td>\n",
              "      <td>-0.450561</td>\n",
              "      <td>-0.295420</td>\n",
              "      <td>-0.432786</td>\n",
              "      <td>0.144358</td>\n",
              "      <td>-0.229938</td>\n",
              "      <td>0.404019</td>\n",
              "      <td>-0.298917</td>\n",
              "      <td>0.004588</td>\n",
              "      <td>-0.385330</td>\n",
              "      <td>-0.372534</td>\n",
              "      <td>0.073349</td>\n",
              "      <td>-0.110113</td>\n",
              "      <td>-0.288734</td>\n",
              "      <td>-0.127502</td>\n",
              "      <td>0.003787</td>\n",
              "      <td>-0.162129</td>\n",
              "      <td>-0.302231</td>\n",
              "      <td>-0.223294</td>\n",
              "      <td>-0.362299</td>\n",
              "      <td>0.158596</td>\n",
              "      <td>-0.392234</td>\n",
              "      <td>-0.138101</td>\n",
              "      <td>-0.419937</td>\n",
              "      <td>0.447443</td>\n",
              "      <td>-0.303933</td>\n",
              "      <td>0.048098</td>\n",
              "      <td>-0.040134</td>\n",
              "      <td>0.175169</td>\n",
              "      <td>-0.187705</td>\n",
              "      <td>-0.481214</td>\n",
              "      <td>0.540181</td>\n",
              "      <td>0.453666</td>\n",
              "      <td>...</td>\n",
              "      <td>0.269242</td>\n",
              "      <td>-0.542694</td>\n",
              "      <td>0.130851</td>\n",
              "      <td>0.026660</td>\n",
              "      <td>-0.232375</td>\n",
              "      <td>-0.079203</td>\n",
              "      <td>-0.154633</td>\n",
              "      <td>-0.212674</td>\n",
              "      <td>-0.012768</td>\n",
              "      <td>-0.035397</td>\n",
              "      <td>-0.358442</td>\n",
              "      <td>-0.379846</td>\n",
              "      <td>0.561525</td>\n",
              "      <td>0.327231</td>\n",
              "      <td>0.283659</td>\n",
              "      <td>0.083172</td>\n",
              "      <td>0.193545</td>\n",
              "      <td>-0.195285</td>\n",
              "      <td>0.459616</td>\n",
              "      <td>0.099866</td>\n",
              "      <td>0.318208</td>\n",
              "      <td>-0.046797</td>\n",
              "      <td>0.190287</td>\n",
              "      <td>-0.175624</td>\n",
              "      <td>-0.081839</td>\n",
              "      <td>0.175881</td>\n",
              "      <td>0.237110</td>\n",
              "      <td>-0.035015</td>\n",
              "      <td>-0.551324</td>\n",
              "      <td>-0.341807</td>\n",
              "      <td>0.076596</td>\n",
              "      <td>-0.085319</td>\n",
              "      <td>0.426342</td>\n",
              "      <td>0.337007</td>\n",
              "      <td>-0.249602</td>\n",
              "      <td>-0.001136</td>\n",
              "      <td>0.351651</td>\n",
              "      <td>-0.083713</td>\n",
              "      <td>-0.425063</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>772 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            g_0       g_1       g_2  ...     g_769     g_770     g_771\n",
              "g_0    1.000000  0.086032  0.176188  ... -0.127375 -0.514201  0.405908\n",
              "g_1    0.086032  1.000000 -0.054518  ... -0.006866 -0.095108 -0.032233\n",
              "g_2    0.176188 -0.054518  1.000000  ...  0.014489 -0.078661  0.103985\n",
              "g_3    0.011266 -0.027855  0.042633  ... -0.206077 -0.002142  0.058219\n",
              "g_4    0.403153  0.193647  0.013968  ... -0.172727 -0.363673  0.250713\n",
              "...         ...       ...       ...  ...       ...       ...       ...\n",
              "g_767 -0.052622 -0.003378 -0.053149  ...  0.065450  0.008603 -0.001136\n",
              "g_768  0.300241 -0.030756  0.115415  ...  0.079364 -0.382607  0.351651\n",
              "g_769 -0.127375 -0.006866  0.014489  ...  1.000000  0.135853 -0.083713\n",
              "g_770 -0.514201 -0.095108 -0.078661  ...  0.135853  1.000000 -0.425063\n",
              "g_771  0.405908 -0.032233  0.103985  ... -0.083713 -0.425063  1.000000\n",
              "\n",
              "[772 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DzKKPAVWKD_b"
      },
      "source": [
        "###Gerando mapa de calor"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "-gy_I3wJG-Z9",
        "outputId": "340c045d-5cde-4dc4-f259-02917af0f670"
      },
      "source": [
        "# Compute the correlation matrix\n",
        "corr = dados.loc[:, 'g_0':'g_50'].corr()\n",
        "\n",
        "# Generate a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa384f05e10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V-ePHNNSJft7"
      },
      "source": [
        "corr_celular = dados.loc[:, 'c_0':'c_50'].corr()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 568
        },
        "id": "bBZREu9dMmg8",
        "outputId": "056c58c1-c31c-425e-c809-5b006b33f141"
      },
      "source": [
        "# Generate a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(corr_celular, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr_celular, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa384c1bd10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cGQkEulXMrRS"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}