teste.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "teste.ipynb",
      "provenance": [],
      "mount_file_id": "1KkKBzNYVDSMRB4FzMd_iIRvtL9aeqzj6",
      "authorship_tag": "ABX9TyOJnmwiSbinSE1SxwW4+JLA",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Willian-R/Google_Colab/blob/master/teste.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b5oHUiDqO16k"
      },
      "source": [
        "# Análise de dados - parte 1"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QKWcsmUHO4am"
      },
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PEI2fZ4pPDm8"
      },
      "source": [
        "dados = pd.read_csv('/content/drive/My Drive/dadosparte1.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QAZN80wAPSjJ"
      },
      "source": [
        "correlacao = dados.corr()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GqM9ASgqPK0K"
      },
      "source": [
        "## Matriz de correlação de Pearson"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ckrF_u7WPfAB",
        "outputId": "c3bc5deb-ff0d-41ed-fe37-47cdc1778e66",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 662
        }
      },
      "source": [
        "plt.figure(figsize=(10,10))\n",
        "sns.heatmap(correlacao, annot=True, cbar=False, cmap='Blues')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f72250d8b70>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LiIBondyQCwA"
      },
      "source": [
        "colunas = ['umi_m', 'mv_m', 'cinzas_m', 'c_m', 'h_m', 'o_m', 'n_m', 'a_superf_bio', 'a_micro_bio']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e2iOtB0vlCfC"
      },
      "source": [
        "dados_features = pd.read_csv('/content/drive/My Drive/dadosparte1.csv', usecols=colunas)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YdT8EEeklJ9R",
        "outputId": "af09bf18-289b-4fce-a0fb-da466997b38b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 762
        }
      },
      "source": [
        "dados_features"
      ],
      "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>umi_m</th>\n",
              "      <th>mv_m</th>\n",
              "      <th>cinzas_m</th>\n",
              "      <th>c_m</th>\n",
              "      <th>h_m</th>\n",
              "      <th>o_m</th>\n",
              "      <th>n_m</th>\n",
              "      <th>a_superf_bio</th>\n",
              "      <th>a_micro_bio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>12.54</td>\n",
              "      <td>58.18</td>\n",
              "      <td>27.56</td>\n",
              "      <td>34.79</td>\n",
              "      <td>4.83</td>\n",
              "      <td>30.32</td>\n",
              "      <td>2.51</td>\n",
              "      <td>3.68</td>\n",
              "      <td>0.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>12.54</td>\n",
              "      <td>58.18</td>\n",
              "      <td>27.56</td>\n",
              "      <td>34.79</td>\n",
              "      <td>4.83</td>\n",
              "      <td>30.32</td>\n",
              "      <td>2.51</td>\n",
              "      <td>98.06</td>\n",
              "      <td>75.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>13.68</td>\n",
              "      <td>45.52</td>\n",
              "      <td>38.98</td>\n",
              "      <td>29.89</td>\n",
              "      <td>4.04</td>\n",
              "      <td>25.26</td>\n",
              "      <td>1.82</td>\n",
              "      <td>4.26</td>\n",
              "      <td>0.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>13.68</td>\n",
              "      <td>45.52</td>\n",
              "      <td>38.98</td>\n",
              "      <td>29.89</td>\n",
              "      <td>4.04</td>\n",
              "      <td>25.26</td>\n",
              "      <td>1.82</td>\n",
              "      <td>116.90</td>\n",
              "      <td>84.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>14.35</td>\n",
              "      <td>33.46</td>\n",
              "      <td>49.19</td>\n",
              "      <td>28.18</td>\n",
              "      <td>3.74</td>\n",
              "      <td>17.22</td>\n",
              "      <td>1.67</td>\n",
              "      <td>7.39</td>\n",
              "      <td>1.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>14.35</td>\n",
              "      <td>33.46</td>\n",
              "      <td>49.19</td>\n",
              "      <td>28.18</td>\n",
              "      <td>3.74</td>\n",
              "      <td>17.22</td>\n",
              "      <td>1.67</td>\n",
              "      <td>73.54</td>\n",
              "      <td>46.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>13.60</td>\n",
              "      <td>68.30</td>\n",
              "      <td>18.10</td>\n",
              "      <td>42.20</td>\n",
              "      <td>6.60</td>\n",
              "      <td>36.40</td>\n",
              "      <td>4.00</td>\n",
              "      <td>5.70</td>\n",
              "      <td>2.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>13.60</td>\n",
              "      <td>68.30</td>\n",
              "      <td>18.10</td>\n",
              "      <td>42.20</td>\n",
              "      <td>6.60</td>\n",
              "      <td>36.40</td>\n",
              "      <td>4.00</td>\n",
              "      <td>3.90</td>\n",
              "      <td>2.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>13.60</td>\n",
              "      <td>68.30</td>\n",
              "      <td>18.10</td>\n",
              "      <td>42.20</td>\n",
              "      <td>6.60</td>\n",
              "      <td>36.40</td>\n",
              "      <td>4.00</td>\n",
              "      <td>3.40</td>\n",
              "      <td>2.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>13.60</td>\n",
              "      <td>68.30</td>\n",
              "      <td>18.10</td>\n",
              "      <td>42.20</td>\n",
              "      <td>6.60</td>\n",
              "      <td>36.40</td>\n",
              "      <td>4.00</td>\n",
              "      <td>59.00</td>\n",
              "      <td>43.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>13.60</td>\n",
              "      <td>68.30</td>\n",
              "      <td>18.10</td>\n",
              "      <td>42.20</td>\n",
              "      <td>6.60</td>\n",
              "      <td>36.40</td>\n",
              "      <td>4.00</td>\n",
              "      <td>63.00</td>\n",
              "      <td>37.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1.10</td>\n",
              "      <td>81.50</td>\n",
              "      <td>0.10</td>\n",
              "      <td>47.10</td>\n",
              "      <td>7.34</td>\n",
              "      <td>45.14</td>\n",
              "      <td>0.24</td>\n",
              "      <td>351.64</td>\n",
              "      <td>244.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1.10</td>\n",
              "      <td>81.50</td>\n",
              "      <td>0.10</td>\n",
              "      <td>47.10</td>\n",
              "      <td>7.34</td>\n",
              "      <td>45.14</td>\n",
              "      <td>0.24</td>\n",
              "      <td>317.86</td>\n",
              "      <td>229.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>8.50</td>\n",
              "      <td>81.80</td>\n",
              "      <td>1.80</td>\n",
              "      <td>45.27</td>\n",
              "      <td>6.16</td>\n",
              "      <td>48.10</td>\n",
              "      <td>0.47</td>\n",
              "      <td>1.30</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>8.50</td>\n",
              "      <td>81.80</td>\n",
              "      <td>1.80</td>\n",
              "      <td>45.27</td>\n",
              "      <td>6.16</td>\n",
              "      <td>48.10</td>\n",
              "      <td>0.47</td>\n",
              "      <td>2.10</td>\n",
              "      <td>1.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>8.50</td>\n",
              "      <td>81.80</td>\n",
              "      <td>1.80</td>\n",
              "      <td>45.27</td>\n",
              "      <td>6.16</td>\n",
              "      <td>48.10</td>\n",
              "      <td>0.47</td>\n",
              "      <td>165.20</td>\n",
              "      <td>147.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>8.50</td>\n",
              "      <td>81.80</td>\n",
              "      <td>1.80</td>\n",
              "      <td>45.27</td>\n",
              "      <td>6.16</td>\n",
              "      <td>48.10</td>\n",
              "      <td>0.47</td>\n",
              "      <td>97.50</td>\n",
              "      <td>96.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>11.50</td>\n",
              "      <td>67.30</td>\n",
              "      <td>1.70</td>\n",
              "      <td>44.43</td>\n",
              "      <td>6.16</td>\n",
              "      <td>49.23</td>\n",
              "      <td>0.18</td>\n",
              "      <td>14.44</td>\n",
              "      <td>4.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>11.50</td>\n",
              "      <td>67.30</td>\n",
              "      <td>1.70</td>\n",
              "      <td>44.43</td>\n",
              "      <td>6.16</td>\n",
              "      <td>49.23</td>\n",
              "      <td>0.18</td>\n",
              "      <td>28.65</td>\n",
              "      <td>16.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>11.50</td>\n",
              "      <td>67.30</td>\n",
              "      <td>1.70</td>\n",
              "      <td>44.43</td>\n",
              "      <td>6.16</td>\n",
              "      <td>49.23</td>\n",
              "      <td>0.18</td>\n",
              "      <td>9.96</td>\n",
              "      <td>1.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>10.70</td>\n",
              "      <td>69.60</td>\n",
              "      <td>0.90</td>\n",
              "      <td>45.71</td>\n",
              "      <td>5.89</td>\n",
              "      <td>48.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>11.72</td>\n",
              "      <td>0.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>10.70</td>\n",
              "      <td>69.60</td>\n",
              "      <td>0.90</td>\n",
              "      <td>45.71</td>\n",
              "      <td>5.89</td>\n",
              "      <td>48.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>12.26</td>\n",
              "      <td>2.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>10.70</td>\n",
              "      <td>69.60</td>\n",
              "      <td>0.90</td>\n",
              "      <td>45.71</td>\n",
              "      <td>5.89</td>\n",
              "      <td>48.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>12.18</td>\n",
              "      <td>2.58</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    umi_m   mv_m  cinzas_m    c_m   h_m    o_m   n_m  a_superf_bio  a_micro_bio\n",
              "0   12.54  58.18     27.56  34.79  4.83  30.32  2.51          3.68         0.67\n",
              "1   12.54  58.18     27.56  34.79  4.83  30.32  2.51         98.06        75.72\n",
              "2   13.68  45.52     38.98  29.89  4.04  25.26  1.82          4.26         0.26\n",
              "3   13.68  45.52     38.98  29.89  4.04  25.26  1.82        116.90        84.83\n",
              "4   14.35  33.46     49.19  28.18  3.74  17.22  1.67          7.39         1.31\n",
              "5   14.35  33.46     49.19  28.18  3.74  17.22  1.67         73.54        46.11\n",
              "6   13.60  68.30     18.10  42.20  6.60  36.40  4.00          5.70         2.80\n",
              "7   13.60  68.30     18.10  42.20  6.60  36.40  4.00          3.90         2.00\n",
              "8   13.60  68.30     18.10  42.20  6.60  36.40  4.00          3.40         2.60\n",
              "9   13.60  68.30     18.10  42.20  6.60  36.40  4.00         59.00        43.00\n",
              "10  13.60  68.30     18.10  42.20  6.60  36.40  4.00         63.00        37.00\n",
              "11   1.10  81.50      0.10  47.10  7.34  45.14  0.24        351.64       244.50\n",
              "12   1.10  81.50      0.10  47.10  7.34  45.14  0.24        317.86       229.12\n",
              "13   8.50  81.80      1.80  45.27  6.16  48.10  0.47          1.30         0.10\n",
              "14   8.50  81.80      1.80  45.27  6.16  48.10  0.47          2.10         1.10\n",
              "15   8.50  81.80      1.80  45.27  6.16  48.10  0.47        165.20       147.80\n",
              "16   8.50  81.80      1.80  45.27  6.16  48.10  0.47         97.50        96.40\n",
              "17  11.50  67.30      1.70  44.43  6.16  49.23  0.18         14.44         4.89\n",
              "18  11.50  67.30      1.70  44.43  6.16  49.23  0.18         28.65        16.07\n",
              "19  11.50  67.30      1.70  44.43  6.16  49.23  0.18          9.96         1.63\n",
              "20  10.70  69.60      0.90  45.71  5.89  48.40  0.00         11.72         0.75\n",
              "21  10.70  69.60      0.90  45.71  5.89  48.40  0.00         12.26         2.97\n",
              "22  10.70  69.60      0.90  45.71  5.89  48.40  0.00         12.18         2.58"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FwZK0eYVlLNp"
      },
      "source": [
        "colunas = ['t_resid', 'tx_aquec', 'temp']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4xHc2SFglTNq"
      },
      "source": [
        "dados_target = pd.read_csv('/content/drive/My Drive/dadosparte1.csv', usecols=colunas)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4h8mBBuLlYix",
        "outputId": "e9af2aed-0b95-4164-df27-3f68e42ce186",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 762
        }
      },
      "source": [
        "dados_target"
      ],
      "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>t_resid</th>\n",
              "      <th>tx_aquec</th>\n",
              "      <th>temp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2.00</td>\n",
              "      <td>25.0</td>\n",
              "      <td>400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.00</td>\n",
              "      <td>25.0</td>\n",
              "      <td>700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2.00</td>\n",
              "      <td>25.0</td>\n",
              "      <td>400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2.00</td>\n",
              "      <td>25.0</td>\n",
              "      <td>700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2.00</td>\n",
              "      <td>25.0</td>\n",
              "      <td>400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2.00</td>\n",
              "      <td>25.0</td>\n",
              "      <td>700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.0</td>\n",
              "      <td>400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.0</td>\n",
              "      <td>500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.0</td>\n",
              "      <td>600.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.0</td>\n",
              "      <td>700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1.00</td>\n",
              "      <td>10.0</td>\n",
              "      <td>800.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>3.93</td>\n",
              "      <td>5.0</td>\n",
              "      <td>900.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1.00</td>\n",
              "      <td>128.0</td>\n",
              "      <td>900.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.19</td>\n",
              "      <td>25.0</td>\n",
              "      <td>300.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.25</td>\n",
              "      <td>25.0</td>\n",
              "      <td>400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.32</td>\n",
              "      <td>25.0</td>\n",
              "      <td>500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0.39</td>\n",
              "      <td>25.0</td>\n",
              "      <td>600.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1.00</td>\n",
              "      <td>24.5</td>\n",
              "      <td>348.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1.00</td>\n",
              "      <td>35.1</td>\n",
              "      <td>427.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1.00</td>\n",
              "      <td>42.8</td>\n",
              "      <td>659.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>1.00</td>\n",
              "      <td>25.4</td>\n",
              "      <td>398.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>1.00</td>\n",
              "      <td>35.5</td>\n",
              "      <td>528.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>1.00</td>\n",
              "      <td>49.1</td>\n",
              "      <td>604.2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    t_resid  tx_aquec   temp\n",
              "0      2.00      25.0  400.0\n",
              "1      2.00      25.0  700.0\n",
              "2      2.00      25.0  400.0\n",
              "3      2.00      25.0  700.0\n",
              "4      2.00      25.0  400.0\n",
              "5      2.00      25.0  700.0\n",
              "6      1.00      10.0  400.0\n",
              "7      1.00      10.0  500.0\n",
              "8      1.00      10.0  600.0\n",
              "9      1.00      10.0  700.0\n",
              "10     1.00      10.0  800.0\n",
              "11     3.93       5.0  900.0\n",
              "12     1.00     128.0  900.0\n",
              "13     0.19      25.0  300.0\n",
              "14     0.25      25.0  400.0\n",
              "15     0.32      25.0  500.0\n",
              "16     0.39      25.0  600.0\n",
              "17     1.00      24.5  348.4\n",
              "18     1.00      35.1  427.5\n",
              "19     1.00      42.8  659.8\n",
              "20     1.00      25.4  398.8\n",
              "21     1.00      35.5  528.7\n",
              "22     1.00      49.1  604.2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9SbNql34lZmI"
      },
      "source": [
        "dados_features_vetor = dados_features.to_numpy()\n",
        "dados_target_vetor = dados_target.to_numpy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TTc7P780qXOP"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}