baseline.ipynb

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  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.6"
    },
    "colab": {
      "name": "Baseline.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/vitorsr/ccd/blob/master/baseline.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bzvWppKXlyKp",
        "colab_type": "text"
      },
      "source": [
        "#Baseline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pvx0bOBsxBxW",
        "colab_type": "text"
      },
      "source": [
        "Este Notebook tem como objetivo a realização de um pré-processamento dos dados a serem utilizados de forma a permitir a obtenção de dois resultados para análise:\n",
        "\n",
        "\n",
        "*   Diferença dos Dados de Agosto de 2019 com relação a um Baseline Histórico (Dados de 1970 a 2018);\n",
        "*   Projeção dos Dados do dia 19 de Agosto de 2019 em um Sistema PCA calculado com base em todos os dados disponíveis\n",
        "\n",
        "Para isso, foram utilizados dois Datasets:\n",
        "\n",
        "\n",
        "*   Dataset com Dados Metereológicos entre os Anos de 1970 a 2018, fornecidos como dados principais da Competição;\n",
        "*   Dataset com Dados Metereológicos de 2019, da mesma fonte dos dados anteriores;\n",
        "\n",
        "Os resultados gerados aqui, a partir do uso da biblioteca Pandas, foram utilizados em outros Notebooks do Repositório para uma devida visualização dos resultados em Mapas.\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7O7eTnYGngk2",
        "colab_type": "text"
      },
      "source": [
        "## Bibliotecas Utilizadas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ch7Kv80Lnbu7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import os"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tsmhi3sRnk0R",
        "colab_type": "text"
      },
      "source": [
        "## Extração de Dados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dQJWsknnjVjn",
        "colab_type": "text"
      },
      "source": [
        "Extração dos Dados Históricos (1970-2018):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Udn_udEoH_co",
        "colab_type": "code",
        "outputId": "cf30f94d-96da-420d-ac87-20f648fdfb45",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "!wget -q -O ccd_2019.zip https://www.dropbox.com/s/7rriacb7c6vzf3m/ccd_2019.zip\n",
        "\n",
        "!unzip ccd_2019.zip"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Archive:  ccd_2019.zip\n",
            "replace bdmep_meta.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: N\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vj5VTrVej1Gx",
        "colab_type": "text"
      },
      "source": [
        "Extração dos Dados de 2019:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Abn2ryA4mhGW",
        "colab_type": "code",
        "outputId": "5dfe559b-f59a-4615-9e26-e075579cfbc2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        }
      },
      "source": [
        "!wget \"https://onedrive.live.com/download?cid=BCBADB0836C97273&resid=BCBADB0836C97273%21115485&authkey=AJlb41BWz0YiBd8\" -O 2019.zip\n",
        "!unzip 2019.zip"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2019-10-29 23:02:47--  https://onedrive.live.com/download?cid=BCBADB0836C97273&resid=BCBADB0836C97273%21115485&authkey=AJlb41BWz0YiBd8\n",
            "Resolving onedrive.live.com (onedrive.live.com)... 13.107.42.13\n",
            "Connecting to onedrive.live.com (onedrive.live.com)|13.107.42.13|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://c9quda.bn.files.1drv.com/y4mMptOcW79YXWTGWZ3CqE4a8euugSIOX2eHzJTVKh8Sw1Vj1caC89931VNBfV4sCC295lRu6U2erzC1POIPnZUSoNi5cmMFY6loqZP3N1r53PzLHB17FDyA6SJTjavp1idr27lVntyjxeg-N4QA0JtCa__JxxCzt2-oLh2afdm85r1LHNICcsPZWuMUcp43bAI_h8ZkhluwAGG0Wo6h_Ov9Q/2019.zip?download&psid=1 [following]\n",
            "--2019-10-29 23:02:47--  https://c9quda.bn.files.1drv.com/y4mMptOcW79YXWTGWZ3CqE4a8euugSIOX2eHzJTVKh8Sw1Vj1caC89931VNBfV4sCC295lRu6U2erzC1POIPnZUSoNi5cmMFY6loqZP3N1r53PzLHB17FDyA6SJTjavp1idr27lVntyjxeg-N4QA0JtCa__JxxCzt2-oLh2afdm85r1LHNICcsPZWuMUcp43bAI_h8ZkhluwAGG0Wo6h_Ov9Q/2019.zip?download&psid=1\n",
            "Resolving c9quda.bn.files.1drv.com (c9quda.bn.files.1drv.com)... 13.107.42.12\n",
            "Connecting to c9quda.bn.files.1drv.com (c9quda.bn.files.1drv.com)|13.107.42.12|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1857551 (1.8M) [application/zip]\n",
            "Saving to: ‘2019.zip’\n",
            "\n",
            "2019.zip            100%[===================>]   1.77M  --.-KB/s    in 0.05s   \n",
            "\n",
            "2019-10-29 23:02:48 (33.0 MB/s) - ‘2019.zip’ saved [1857551/1857551]\n",
            "\n",
            "Archive:  2019.zip\n",
            "replace 2019/82024.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: N\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hk-VTr62ml2Z",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "directory = '2019'\n",
        "files = []\n",
        "for filename in os.listdir(directory):\n",
        "    if filename.endswith(\".csv\"): \n",
        "        files.append(filename)\n",
        "        continue\n",
        "    else:\n",
        "        continue"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QUXlc1rDm5r8",
        "colab_type": "code",
        "outputId": "c2f8ab49-e9c0-448f-a7bc-4348164628eb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_2019 = pd.DataFrame()\n",
        "for file in files:\n",
        "    df_aux = pd.read_csv(directory+'/'+file, delimiter=',')\n",
        "    df_2019 = pd.concat([df_aux, df_2019], sort=True)\n",
        "id_2019 = pd.unique(df_2019['id'])\n",
        "id_2019"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([82487, 82768, 83013, 82578, 82990, 83442, 82590, 82113, 83632,\n",
              "       83437, 83393, 82476, 82382, 82181, 83744, 82353, 83676, 82994,\n",
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              "       82042, 82562, 83244, 83942, 82976, 83228])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9oN_ANc6qL9M",
        "colab_type": "text"
      },
      "source": [
        "Descrição dos Datasets\n",
        "\n",
        "<br><b>variável | descrição | unidade </b></br>\n",
        "<br>date | data e hora da coleta             -\n",
        "<br> id | ID da estação de coleta             -\n",
        "<br>prec | precipitação |       mm\n",
        "<br>tair | temperatura do ar  | graus Celsius\n",
        "<br>tw | temperatura de bulbo úmido |  graus Celsius\n",
        "<br>tmax | temperatura máxima do ar  | graus Celsius\n",
        "<br>tmin | temperatura mínima do ar  | graus Celsius\n",
        "<br>urmax | umidade relativa máxima  |             %\n",
        "<br>patm | pressão atmosférica         |    hPa\n",
        "<br>pnmm | pressão atmosférica média ao nível do mar  |           hPa\n",
        "<br>wd | direção do vento        |   graus\n",
        "<br>wsmax  |  rajadas de vento    |         m/s\n",
        "<br>n |  horas de sol          |     h\n",
        "<br>cc |   cobertura de nuvens    |           -\n",
        "<br>evap  |   evaporação        |      mm\n",
        "<br>ur  |   umidade relativa          |     %\n",
        "<br>ws   |   velocidade do vento       |      m/s"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bs4Iy16fkHWX",
        "colab_type": "text"
      },
      "source": [
        "Head do Dataset Histórico:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HgUnyTMUlyKy",
        "colab_type": "code",
        "outputId": "5f23e670-6679-4f26-db75-cf5eaa081ac7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df = pd.read_csv(\"inmetr.csv\")\n",
        "df.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tw</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>urmax</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>wd</th>\n",
              "      <th>wsmax</th>\n",
              "      <th>n</th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>ur</th>\n",
              "      <th>ws</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1970-05-04 00:00:00</td>\n",
              "      <td>83010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>32.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>89.75</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1970-05-04 12:00:00</td>\n",
              "      <td>83010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.3</td>\n",
              "      <td>24.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>23.7</td>\n",
              "      <td>90.0</td>\n",
              "      <td>1005.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1970-05-04 18:00:00</td>\n",
              "      <td>83010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29.2</td>\n",
              "      <td>27.1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>85.0</td>\n",
              "      <td>1004.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1970-05-05 00:00:00</td>\n",
              "      <td>83010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>32.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>92.0</td>\n",
              "      <td>1007.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.4</td>\n",
              "      <td>88.25</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1970-05-05 12:00:00</td>\n",
              "      <td>83010</td>\n",
              "      <td>0.0</td>\n",
              "      <td>25.9</td>\n",
              "      <td>24.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>23.0</td>\n",
              "      <td>91.0</td>\n",
              "      <td>1006.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  date     id  prec  tair    tw  ...   n   cc  evap     ur  ws\n",
              "0  1970-05-04 00:00:00  83010   NaN   NaN   NaN  ... NaN  NaN   NaN  89.75 NaN\n",
              "1  1970-05-04 12:00:00  83010   NaN  25.3  24.0  ... NaN  5.0   NaN    NaN NaN\n",
              "2  1970-05-04 18:00:00  83010   NaN  29.2  27.1  ... NaN  4.0   NaN    NaN NaN\n",
              "3  1970-05-05 00:00:00  83010   NaN  25.0  27.0  ... NaN  8.0   2.4  88.25 NaN\n",
              "4  1970-05-05 12:00:00  83010   0.0  25.9  24.8  ... NaN  4.0   NaN    NaN NaN\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JGDeLTSPkLgo",
        "colab_type": "text"
      },
      "source": [
        "Head do Dataset de 2019:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J-dg899qlyK2",
        "colab_type": "code",
        "outputId": "3e085751-dab3-498a-ff92-36aafb7c0d7b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_m = pd.read_csv(\"bdmep_meta.csv\")\n",
        "df_m.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "    }\n",
              "\n",
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              "    }\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>lon</th>\n",
              "      <th>lat</th>\n",
              "      <th>alt</th>\n",
              "      <th>name</th>\n",
              "      <th>state</th>\n",
              "      <th>uf</th>\n",
              "      <th>time_zone</th>\n",
              "      <th>offset_utc</th>\n",
              "      <th>time_zone.1</th>\n",
              "      <th>offset_utc.1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>83010</td>\n",
              "      <td>-68.733333</td>\n",
              "      <td>-11.016667</td>\n",
              "      <td>260.00</td>\n",
              "      <td>Brasiléia</td>\n",
              "      <td>Acre</td>\n",
              "      <td>AC</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>82704</td>\n",
              "      <td>-72.666667</td>\n",
              "      <td>-7.633333</td>\n",
              "      <td>170.00</td>\n",
              "      <td>Cruzeiro do Sul</td>\n",
              "      <td>Acre</td>\n",
              "      <td>AC</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>82915</td>\n",
              "      <td>-67.800000</td>\n",
              "      <td>-9.966667</td>\n",
              "      <td>160.00</td>\n",
              "      <td>Rio Branco</td>\n",
              "      <td>Acre</td>\n",
              "      <td>AC</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>82807</td>\n",
              "      <td>-70.766667</td>\n",
              "      <td>-8.166667</td>\n",
              "      <td>190.00</td>\n",
              "      <td>Tarauacá</td>\n",
              "      <td>Acre</td>\n",
              "      <td>AC</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "      <td>America/Rio_Branco</td>\n",
              "      <td>-5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>83098</td>\n",
              "      <td>-36.166667</td>\n",
              "      <td>-10.150000</td>\n",
              "      <td>56.13</td>\n",
              "      <td>Coruripe</td>\n",
              "      <td>Alagoas</td>\n",
              "      <td>AL</td>\n",
              "      <td>America/Maceio</td>\n",
              "      <td>-3</td>\n",
              "      <td>America/Maceio</td>\n",
              "      <td>-3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      id        lon        lat  ...  offset_utc         time_zone.1 offset_utc.1\n",
              "0  83010 -68.733333 -11.016667  ...          -5  America/Rio_Branco           -5\n",
              "1  82704 -72.666667  -7.633333  ...          -5  America/Rio_Branco           -5\n",
              "2  82915 -67.800000  -9.966667  ...          -5  America/Rio_Branco           -5\n",
              "3  82807 -70.766667  -8.166667  ...          -5  America/Rio_Branco           -5\n",
              "4  83098 -36.166667 -10.150000  ...          -3      America/Maceio           -3\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6-T67qrExccd",
        "colab_type": "text"
      },
      "source": [
        "## Processamento de Dados Históricos (Baseline)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uDaWQhLklyK4",
        "colab_type": "text"
      },
      "source": [
        "Os dados apresentados abragem o período entre os anos de 1970 e 2018.\n",
        "\n",
        "Filtrando apenas para o Mês de Agosto:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ontod82HhmqN",
        "colab_type": "code",
        "outputId": "caac031d-1e43-4141-8348-b282458385ed",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "mask = (df['date'].str.split('-',n=2,expand = True)[1]=='08')\n",
        "df = df.loc[mask]\n",
        "df.size"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "20944306"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uH9_BawVpqbF",
        "colab_type": "text"
      },
      "source": [
        "Filtrando apenas as Estações ainda Existentes em 2019:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xCggXWBfprue",
        "colab_type": "code",
        "outputId": "fa1ccabd-c5b8-424e-b121-17af5a546ff5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "mask = (df['id'].isin(id_2019))\n",
        "df = df.loc[mask]\n",
        "df.size"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "13499360"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XDcfKe8vh8jp",
        "colab_type": "text"
      },
      "source": [
        "Extraindo o Ano da Coluna Date:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7ukDsDUZz1vp",
        "colab_type": "code",
        "outputId": "a31d296c-aeb9-4b2b-da2f-ba7acb37109b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df['date'] = df['date'].str.split('-',n=1,expand = True)[1]\n",
        "df.head()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tw</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>urmax</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>wd</th>\n",
              "      <th>wsmax</th>\n",
              "      <th>n</th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>ur</th>\n",
              "      <th>ws</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>53402</th>\n",
              "      <td>08-01 00:00:00</td>\n",
              "      <td>82915</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.0</td>\n",
              "      <td>22.8</td>\n",
              "      <td>35.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>84.0</td>\n",
              "      <td>1010.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.6</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>74.75</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53403</th>\n",
              "      <td>08-01 12:00:00</td>\n",
              "      <td>82915</td>\n",
              "      <td>0.0</td>\n",
              "      <td>22.2</td>\n",
              "      <td>21.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19.7</td>\n",
              "      <td>94.0</td>\n",
              "      <td>1000.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53404</th>\n",
              "      <td>08-01 18:00:00</td>\n",
              "      <td>82915</td>\n",
              "      <td>NaN</td>\n",
              "      <td>33.8</td>\n",
              "      <td>27.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>57.0</td>\n",
              "      <td>999.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53405</th>\n",
              "      <td>08-02 00:00:00</td>\n",
              "      <td>82915</td>\n",
              "      <td>NaN</td>\n",
              "      <td>26.8</td>\n",
              "      <td>24.8</td>\n",
              "      <td>33.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>74.0</td>\n",
              "      <td>996.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.5</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.1</td>\n",
              "      <td>83.50</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53406</th>\n",
              "      <td>08-02 12:00:00</td>\n",
              "      <td>82915</td>\n",
              "      <td>21.9</td>\n",
              "      <td>11.8</td>\n",
              "      <td>11.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.2</td>\n",
              "      <td>90.0</td>\n",
              "      <td>1009.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 date     id  prec  tair    tw  ...    n   cc  evap     ur   ws\n",
              "53402  08-01 00:00:00  82915   NaN  25.0  22.8  ...  5.6  4.0   3.2  74.75  0.0\n",
              "53403  08-01 12:00:00  82915   0.0  22.2  21.6  ...  NaN  7.0   NaN    NaN  NaN\n",
              "53404  08-01 18:00:00  82915   NaN  33.8  27.0  ...  NaN  7.0   NaN    NaN  NaN\n",
              "53405  08-02 00:00:00  82915   NaN  26.8  24.8  ...  3.5  6.0   2.1  83.50  NaN\n",
              "53406  08-02 12:00:00  82915  21.9  11.8  11.0  ...  NaN  8.0   NaN    NaN  NaN\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MzfvAzNtigm5",
        "colab_type": "text"
      },
      "source": [
        "Extraindo a Hora de Medição da Coluna Date:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fVgFMm5HikLw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df['date'] = df['date'].str.split(' ',n=1,expand = True)[0]\n",
        "df.head()\n",
        "df_pre_gp = df #Extraindo para utilização no Cálculo do PCA"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nS7XfKvfo7zs",
        "colab_type": "text"
      },
      "source": [
        "Group By por Data e Estação com operação de Média:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aZB1_nGlY1Pq",
        "colab_type": "code",
        "outputId": "529233d3-c85d-4959-c946-941a03ef0cc5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df = df.groupby(by=['date','id']).mean()\n",
        "df.head(1000)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\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></th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tw</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>urmax</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>wd</th>\n",
              "      <th>wsmax</th>\n",
              "      <th>n</th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>ur</th>\n",
              "      <th>ws</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>6.219512</td>\n",
              "      <td>27.235246</td>\n",
              "      <td>24.882883</td>\n",
              "      <td>32.069231</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>82.653465</td>\n",
              "      <td>1001.716216</td>\n",
              "      <td>1012.100000</td>\n",
              "      <td>10.176471</td>\n",
              "      <td>1.075546</td>\n",
              "      <td>5.175000</td>\n",
              "      <td>5.283333</td>\n",
              "      <td>2.597143</td>\n",
              "      <td>84.051471</td>\n",
              "      <td>1.025690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82042</th>\n",
              "      <td>4.133333</td>\n",
              "      <td>26.858163</td>\n",
              "      <td>24.436145</td>\n",
              "      <td>32.003448</td>\n",
              "      <td>22.071875</td>\n",
              "      <td>83.881579</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.578947</td>\n",
              "      <td>0.445155</td>\n",
              "      <td>5.860000</td>\n",
              "      <td>5.754639</td>\n",
              "      <td>2.345455</td>\n",
              "      <td>83.840000</td>\n",
              "      <td>0.467799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>3.716327</td>\n",
              "      <td>28.204027</td>\n",
              "      <td>25.416779</td>\n",
              "      <td>31.976000</td>\n",
              "      <td>23.632000</td>\n",
              "      <td>79.320611</td>\n",
              "      <td>1010.518571</td>\n",
              "      <td>1012.216667</td>\n",
              "      <td>5.694656</td>\n",
              "      <td>1.385906</td>\n",
              "      <td>8.237500</td>\n",
              "      <td>4.687162</td>\n",
              "      <td>2.765306</td>\n",
              "      <td>81.761364</td>\n",
              "      <td>1.290667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>4.888889</td>\n",
              "      <td>25.806329</td>\n",
              "      <td>24.044521</td>\n",
              "      <td>30.796296</td>\n",
              "      <td>21.407547</td>\n",
              "      <td>87.307087</td>\n",
              "      <td>1003.087736</td>\n",
              "      <td>1007.000000</td>\n",
              "      <td>9.503937</td>\n",
              "      <td>1.180905</td>\n",
              "      <td>4.656250</td>\n",
              "      <td>5.431250</td>\n",
              "      <td>1.298000</td>\n",
              "      <td>88.738372</td>\n",
              "      <td>1.182592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82113</th>\n",
              "      <td>6.386538</td>\n",
              "      <td>26.638000</td>\n",
              "      <td>24.857746</td>\n",
              "      <td>32.082000</td>\n",
              "      <td>21.821569</td>\n",
              "      <td>86.439024</td>\n",
              "      <td>999.248611</td>\n",
              "      <td>NaN</td>\n",
              "      <td>13.333333</td>\n",
              "      <td>1.276955</td>\n",
              "      <td>6.700000</td>\n",
              "      <td>3.563333</td>\n",
              "      <td>1.847368</td>\n",
              "      <td>87.191860</td>\n",
              "      <td>1.266859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-06</th>\n",
              "      <th>82336</th>\n",
              "      <td>3.765116</td>\n",
              "      <td>28.311024</td>\n",
              "      <td>25.521930</td>\n",
              "      <td>32.833333</td>\n",
              "      <td>22.871795</td>\n",
              "      <td>79.203883</td>\n",
              "      <td>1009.350000</td>\n",
              "      <td>1039.600000</td>\n",
              "      <td>7.560000</td>\n",
              "      <td>0.999209</td>\n",
              "      <td>7.302857</td>\n",
              "      <td>4.403846</td>\n",
              "      <td>3.527778</td>\n",
              "      <td>80.323529</td>\n",
              "      <td>1.007813</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82353</th>\n",
              "      <td>1.214815</td>\n",
              "      <td>28.338961</td>\n",
              "      <td>24.939610</td>\n",
              "      <td>33.164706</td>\n",
              "      <td>21.482353</td>\n",
              "      <td>75.500000</td>\n",
              "      <td>1000.891000</td>\n",
              "      <td>1009.054348</td>\n",
              "      <td>13.027778</td>\n",
              "      <td>1.365041</td>\n",
              "      <td>7.980000</td>\n",
              "      <td>3.053659</td>\n",
              "      <td>2.410870</td>\n",
              "      <td>77.088889</td>\n",
              "      <td>1.326016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82361</th>\n",
              "      <td>1.113953</td>\n",
              "      <td>28.308462</td>\n",
              "      <td>25.276378</td>\n",
              "      <td>33.773810</td>\n",
              "      <td>22.064286</td>\n",
              "      <td>77.354545</td>\n",
              "      <td>1009.910236</td>\n",
              "      <td>1013.166667</td>\n",
              "      <td>17.079646</td>\n",
              "      <td>1.436923</td>\n",
              "      <td>8.793103</td>\n",
              "      <td>3.385385</td>\n",
              "      <td>3.400000</td>\n",
              "      <td>78.694444</td>\n",
              "      <td>1.404924</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82376</th>\n",
              "      <td>0.081395</td>\n",
              "      <td>28.585217</td>\n",
              "      <td>24.247826</td>\n",
              "      <td>32.978571</td>\n",
              "      <td>21.897619</td>\n",
              "      <td>70.400000</td>\n",
              "      <td>1006.997521</td>\n",
              "      <td>1012.564706</td>\n",
              "      <td>9.982143</td>\n",
              "      <td>2.162000</td>\n",
              "      <td>8.648780</td>\n",
              "      <td>3.991736</td>\n",
              "      <td>4.674419</td>\n",
              "      <td>72.789474</td>\n",
              "      <td>2.037037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82382</th>\n",
              "      <td>0.159524</td>\n",
              "      <td>28.420909</td>\n",
              "      <td>23.314545</td>\n",
              "      <td>33.130952</td>\n",
              "      <td>21.923684</td>\n",
              "      <td>65.618182</td>\n",
              "      <td>1000.401818</td>\n",
              "      <td>1012.833333</td>\n",
              "      <td>13.490741</td>\n",
              "      <td>2.089524</td>\n",
              "      <td>9.558537</td>\n",
              "      <td>2.427273</td>\n",
              "      <td>5.735714</td>\n",
              "      <td>68.409722</td>\n",
              "      <td>2.142157</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1000 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 prec       tair         tw  ...      evap         ur        ws\n",
              "date  id                                     ...                               \n",
              "08-01 82024  6.219512  27.235246  24.882883  ...  2.597143  84.051471  1.025690\n",
              "      82042  4.133333  26.858163  24.436145  ...  2.345455  83.840000  0.467799\n",
              "      82098  3.716327  28.204027  25.416779  ...  2.765306  81.761364  1.290667\n",
              "      82106  4.888889  25.806329  24.044521  ...  1.298000  88.738372  1.182592\n",
              "      82113  6.386538  26.638000  24.857746  ...  1.847368  87.191860  1.266859\n",
              "...               ...        ...        ...  ...       ...        ...       ...\n",
              "08-06 82336  3.765116  28.311024  25.521930  ...  3.527778  80.323529  1.007813\n",
              "      82353  1.214815  28.338961  24.939610  ...  2.410870  77.088889  1.326016\n",
              "      82361  1.113953  28.308462  25.276378  ...  3.400000  78.694444  1.404924\n",
              "      82376  0.081395  28.585217  24.247826  ...  4.674419  72.789474  2.037037\n",
              "      82382  0.159524  28.420909  23.314545  ...  5.735714  68.409722  2.142157\n",
              "\n",
              "[1000 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0HzDD5RaxhW6",
        "colab_type": "text"
      },
      "source": [
        "## Processamento de Dados Atuais"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J6JoLM1Xkahe",
        "colab_type": "text"
      },
      "source": [
        "Dados de 2019:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FAiW3JnDraLX",
        "colab_type": "code",
        "outputId": "f7e2f470-25ae-4eb1-86cf-a03a374215a9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_2019.head()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cc</th>\n",
              "      <th>date</th>\n",
              "      <th>evap</th>\n",
              "      <th>id</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>request_status</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.75</td>\n",
              "      <td>2019-01-01T00:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>5.3</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>1012.4</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>Success: (200) OK</td>\n",
              "      <td>20.9</td>\n",
              "      <td>28.8</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>75.5</td>\n",
              "      <td>85</td>\n",
              "      <td>5</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.00</td>\n",
              "      <td>2019-01-01T12:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>919.0</td>\n",
              "      <td>1014.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Success: (200) OK</td>\n",
              "      <td>21.3</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>19.7</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>91</td>\n",
              "      <td>9</td>\n",
              "      <td>-9999.00000</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6.25</td>\n",
              "      <td>2019-01-01T18:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>916.7</td>\n",
              "      <td>1011.1</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>Success: (200) OK</td>\n",
              "      <td>27.3</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>57</td>\n",
              "      <td>9</td>\n",
              "      <td>-9999.00000</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.75</td>\n",
              "      <td>2019-01-02T00:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>5.5</td>\n",
              "      <td>918.5</td>\n",
              "      <td>1013.9</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>Success: (200) OK</td>\n",
              "      <td>21.7</td>\n",
              "      <td>28.2</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>79.5</td>\n",
              "      <td>77</td>\n",
              "      <td>9</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10.00</td>\n",
              "      <td>2019-01-02T12:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>919.2</td>\n",
              "      <td>1014.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Success: (200) OK</td>\n",
              "      <td>20.9</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>19.7</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>91</td>\n",
              "      <td>9</td>\n",
              "      <td>-9999.00000</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      cc                  date    evap     id  ...  urmax  wd          ws    wsmax\n",
              "0   3.75  2019-01-01T00:00:00Z -9999.0  82487  ...     85   5     3.08664  3.08664\n",
              "1  10.00  2019-01-01T12:00:00Z -9999.0  82487  ...     91   9 -9999.00000  3.08664\n",
              "2   6.25  2019-01-01T18:00:00Z -9999.0  82487  ...     57   9 -9999.00000  3.08664\n",
              "3   3.75  2019-01-02T00:00:00Z -9999.0  82487  ...     77   9     3.08664  3.08664\n",
              "4  10.00  2019-01-02T12:00:00Z -9999.0  82487  ...     91   9 -9999.00000  3.08664\n",
              "\n",
              "[5 rows x 18 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HmomxG4Ckji_",
        "colab_type": "text"
      },
      "source": [
        "Removendo coluna de Status de Request:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CnFDV0Fcrb7R",
        "colab_type": "code",
        "outputId": "086c1de0-0889-44cc-b59a-9768c985db9e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_2019 = df_2019.drop(['request_status'],axis=1)\n",
        "df_2019.head()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cc</th>\n",
              "      <th>date</th>\n",
              "      <th>evap</th>\n",
              "      <th>id</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.75</td>\n",
              "      <td>2019-01-01T00:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>5.3</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>1012.4</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>20.9</td>\n",
              "      <td>28.8</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>75.5</td>\n",
              "      <td>85</td>\n",
              "      <td>5</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.00</td>\n",
              "      <td>2019-01-01T12:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>919.0</td>\n",
              "      <td>1014.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.3</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>19.7</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>91</td>\n",
              "      <td>9</td>\n",
              "      <td>-9999.00000</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6.25</td>\n",
              "      <td>2019-01-01T18:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>916.7</td>\n",
              "      <td>1011.1</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>27.3</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>57</td>\n",
              "      <td>9</td>\n",
              "      <td>-9999.00000</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.75</td>\n",
              "      <td>2019-01-02T00:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>5.5</td>\n",
              "      <td>918.5</td>\n",
              "      <td>1013.9</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>21.7</td>\n",
              "      <td>28.2</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>79.5</td>\n",
              "      <td>77</td>\n",
              "      <td>9</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10.00</td>\n",
              "      <td>2019-01-02T12:00:00Z</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>82487</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>919.2</td>\n",
              "      <td>1014.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.9</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>19.7</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>-9999.0</td>\n",
              "      <td>91</td>\n",
              "      <td>9</td>\n",
              "      <td>-9999.00000</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      cc                  date    evap     id  ...  urmax  wd          ws    wsmax\n",
              "0   3.75  2019-01-01T00:00:00Z -9999.0  82487  ...     85   5     3.08664  3.08664\n",
              "1  10.00  2019-01-01T12:00:00Z -9999.0  82487  ...     91   9 -9999.00000  3.08664\n",
              "2   6.25  2019-01-01T18:00:00Z -9999.0  82487  ...     57   9 -9999.00000  3.08664\n",
              "3   3.75  2019-01-02T00:00:00Z -9999.0  82487  ...     77   9     3.08664  3.08664\n",
              "4  10.00  2019-01-02T12:00:00Z -9999.0  82487  ...     91   9 -9999.00000  3.08664\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pXxbaEkUyHAE",
        "colab_type": "text"
      },
      "source": [
        "Substituindo Valores Inválidos (-9999.0):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SF_13ATix13D",
        "colab_type": "code",
        "outputId": "e93a8f55-5c7b-4cf9-d075-6ffd28050a89",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_2019 = df_2019.replace(-9999.0,np.nan)\n",
        "df_2019.head()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\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>cc</th>\n",
              "      <th>date</th>\n",
              "      <th>evap</th>\n",
              "      <th>id</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.75</td>\n",
              "      <td>2019-01-01T00:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>5.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1012.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20.9</td>\n",
              "      <td>28.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>75.5</td>\n",
              "      <td>85.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.00</td>\n",
              "      <td>2019-01-01T12:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>919.0</td>\n",
              "      <td>1014.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19.7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6.25</td>\n",
              "      <td>2019-01-01T18:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>916.7</td>\n",
              "      <td>1011.1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>27.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>57.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.75</td>\n",
              "      <td>2019-01-02T00:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>5.5</td>\n",
              "      <td>918.5</td>\n",
              "      <td>1013.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>21.7</td>\n",
              "      <td>28.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>79.5</td>\n",
              "      <td>77.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10.00</td>\n",
              "      <td>2019-01-02T12:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>919.2</td>\n",
              "      <td>1014.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19.7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>91.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      cc                  date  evap     id  ...  urmax   wd       ws    wsmax\n",
              "0   3.75  2019-01-01T00:00:00Z   NaN  82487  ...   85.0  5.0  3.08664  3.08664\n",
              "1  10.00  2019-01-01T12:00:00Z   NaN  82487  ...   91.0  9.0      NaN  3.08664\n",
              "2   6.25  2019-01-01T18:00:00Z   NaN  82487  ...   57.0  9.0      NaN  3.08664\n",
              "3   3.75  2019-01-02T00:00:00Z   NaN  82487  ...   77.0  9.0  3.08664  3.08664\n",
              "4  10.00  2019-01-02T12:00:00Z   NaN  82487  ...   91.0  9.0      NaN  3.08664\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V4etXmTGy12G",
        "colab_type": "text"
      },
      "source": [
        "Segue-se agora o mesmo Processo feito para os Dados Históricos.\n",
        "\n",
        "Filtrando apenas para o Mês de Agosto:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H3E81WE7yb1y",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "mask = (df_2019['date'].str.split('-',n=2,expand = True)[1]=='08')\n",
        "df_2019 = df_2019.loc[mask]\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_lUm8h5hzHmZ",
        "colab_type": "text"
      },
      "source": [
        "Os Dados aqui já contém naturalmente apenas Estações Existentes em 2019.\n",
        "\n",
        "O Ano também já é naturalmente o de 2019, mas seu valor será extraído para fins de padronização."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aPokQ5aO0iMz",
        "colab_type": "code",
        "outputId": "4563f570-39e1-4046-ef76-30d080fc07fb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_2019['date'] = df_2019['date'].str.split('-',n=1,expand = True)[1]\n",
        "df_2019.head()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th></th>\n",
              "      <th>cc</th>\n",
              "      <th>date</th>\n",
              "      <th>evap</th>\n",
              "      <th>id</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
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              "      <th>wsmax</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>573</th>\n",
              "      <td>6.25</td>\n",
              "      <td>08-01T00:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>6.4</td>\n",
              "      <td>919.4</td>\n",
              "      <td>1015.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19.9</td>\n",
              "      <td>25.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>87.50</td>\n",
              "      <td>95.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.25812</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>574</th>\n",
              "      <td>10.00</td>\n",
              "      <td>08-01T12:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>919.1</td>\n",
              "      <td>1015.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>92.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.60108</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>575</th>\n",
              "      <td>5.00</td>\n",
              "      <td>08-01T18:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>916.6</td>\n",
              "      <td>1011.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>68.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>576</th>\n",
              "      <td>10.00</td>\n",
              "      <td>08-02T00:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>6.3</td>\n",
              "      <td>918.3</td>\n",
              "      <td>1014.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20.1</td>\n",
              "      <td>25.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>87.75</td>\n",
              "      <td>95.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.08664</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>577</th>\n",
              "      <td>10.00</td>\n",
              "      <td>08-02T12:00:00Z</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82487</td>\n",
              "      <td>NaN</td>\n",
              "      <td>919.3</td>\n",
              "      <td>1015.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>93.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.08664</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        cc             date  evap     id  ...  urmax   wd       ws    wsmax\n",
              "573   6.25  08-01T00:00:00Z   NaN  82487  ...   95.0  9.0  3.25812  3.08664\n",
              "574  10.00  08-01T12:00:00Z   NaN  82487  ...   92.0  9.0      NaN  3.60108\n",
              "575   5.00  08-01T18:00:00Z   NaN  82487  ...   68.0  5.0      NaN  3.08664\n",
              "576  10.00  08-02T00:00:00Z   NaN  82487  ...   95.0  5.0  3.08664  3.08664\n",
              "577  10.00  08-02T12:00:00Z   NaN  82487  ...   93.0  9.0      NaN  3.08664\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UUowmUrgzXiv",
        "colab_type": "text"
      },
      "source": [
        "Extraindo a Hora de Medição da Coluna Date:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xEkde5xLza5W",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_2019['date'] = df_2019['date'].str.split('T',n=1,expand = True)[0]\n",
        "df_2019.head()\n",
        "df_2019_pre_gp = df_2019 #Extraindo para utilização no Cálculo do PCA"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PIQ97L4izevY",
        "colab_type": "text"
      },
      "source": [
        "Group By por Data e Estação com operação de Média:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4YbGuTEHzg9w",
        "colab_type": "code",
        "outputId": "1eea26ed-af83-48ba-e684-c6065470cc07",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "df_2019 = df_2019.groupby(by=['date','id']).mean()\n",
        "df_2019.head(1000)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "        text-align: right;\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></th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>6.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>47.8</td>\n",
              "      <td>24.100000</td>\n",
              "      <td>34.4</td>\n",
              "      <td>22.0</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>81.00</td>\n",
              "      <td>91.500000</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>3.7</td>\n",
              "      <td>8.9</td>\n",
              "      <td>1009.466667</td>\n",
              "      <td>1011.166667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.066667</td>\n",
              "      <td>33.2</td>\n",
              "      <td>26.6</td>\n",
              "      <td>26.400000</td>\n",
              "      <td>74.50</td>\n",
              "      <td>72.666667</td>\n",
              "      <td>7.666667</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>9.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.1</td>\n",
              "      <td>25.550000</td>\n",
              "      <td>30.9</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>93.00</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>4.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.5</td>\n",
              "      <td>1010.533333</td>\n",
              "      <td>1011.833333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.766667</td>\n",
              "      <td>32.0</td>\n",
              "      <td>27.4</td>\n",
              "      <td>26.300000</td>\n",
              "      <td>77.00</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>14.333333</td>\n",
              "      <td>2.733333</td>\n",
              "      <td>2.733333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>4.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.8</td>\n",
              "      <td>1007.500000</td>\n",
              "      <td>1011.766667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.133333</td>\n",
              "      <td>32.6</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.666667</td>\n",
              "      <td>84.00</td>\n",
              "      <td>82.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>0.533333</td>\n",
              "      <td>0.533333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-06</th>\n",
              "      <th>83565</th>\n",
              "      <td>9.666667</td>\n",
              "      <td>2.2</td>\n",
              "      <td>2.5</td>\n",
              "      <td>974.900000</td>\n",
              "      <td>1023.850000</td>\n",
              "      <td>43.0</td>\n",
              "      <td>19.166667</td>\n",
              "      <td>23.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17.266667</td>\n",
              "      <td>83.50</td>\n",
              "      <td>83.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>1.333333</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83579</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>4.2</td>\n",
              "      <td>0.5</td>\n",
              "      <td>910.600000</td>\n",
              "      <td>1025.333333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>17.266667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>13.4</td>\n",
              "      <td>14.733333</td>\n",
              "      <td>78.75</td>\n",
              "      <td>76.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83587</th>\n",
              "      <td>9.000000</td>\n",
              "      <td>4.7</td>\n",
              "      <td>1.3</td>\n",
              "      <td>922.700000</td>\n",
              "      <td>1025.166667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>18.533333</td>\n",
              "      <td>21.2</td>\n",
              "      <td>15.4</td>\n",
              "      <td>14.800000</td>\n",
              "      <td>67.00</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>7.666667</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>2.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83589</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.9</td>\n",
              "      <td>NaN</td>\n",
              "      <td>951.033333</td>\n",
              "      <td>1025.266667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19.433333</td>\n",
              "      <td>22.7</td>\n",
              "      <td>16.0</td>\n",
              "      <td>16.733333</td>\n",
              "      <td>79.75</td>\n",
              "      <td>74.333333</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83592</th>\n",
              "      <td>8.333333</td>\n",
              "      <td>3.4</td>\n",
              "      <td>0.1</td>\n",
              "      <td>957.000000</td>\n",
              "      <td>1026.633333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.533333</td>\n",
              "      <td>23.7</td>\n",
              "      <td>15.2</td>\n",
              "      <td>16.866667</td>\n",
              "      <td>76.50</td>\n",
              "      <td>68.333333</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>1.333333</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1000 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                    cc  evap     n  ...         wd        ws     wsmax\n",
              "date  id                            ...                               \n",
              "08-01 82024   6.250000   NaN   9.6  ...  11.500000  0.514440  0.514440\n",
              "      82098   6.333333   3.7   8.9  ...   7.666667  1.666667  2.000000\n",
              "      82106   9.000000   NaN   NaN  ...   4.500000  0.514440  0.514440\n",
              "      82141   5.000000   0.3  10.5  ...  14.333333  2.733333  2.733333\n",
              "      82145   4.333333   1.0   9.8  ...  15.000000  0.533333  0.533333\n",
              "...                ...   ...   ...  ...        ...       ...       ...\n",
              "08-06 83565   9.666667   2.2   2.5  ...  11.000000  1.333333  2.000000\n",
              "      83579   6.333333   4.2   0.5  ...        NaN       NaN       NaN\n",
              "      83587   9.000000   4.7   1.3  ...   7.666667  2.600000  2.700000\n",
              "      83589  10.000000   3.9   NaN  ...        NaN       NaN       NaN\n",
              "      83592   8.333333   3.4   0.1  ...  14.000000  1.666667  1.333333\n",
              "\n",
              "[1000 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fyw4QV8gAZ1Z",
        "colab_type": "text"
      },
      "source": [
        "## Cálculo da Diferença com Relação ao Baseline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7PlFYt_zkv45",
        "colab_type": "text"
      },
      "source": [
        "Head do Dataset Histórico (Baseline):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4P1f2Cgg2tzR",
        "colab_type": "code",
        "outputId": "a3ddeac8-5363-4fa3-dbc4-688e9af4a46b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tw</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>urmax</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>wd</th>\n",
              "      <th>wsmax</th>\n",
              "      <th>n</th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>ur</th>\n",
              "      <th>ws</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>6.219512</td>\n",
              "      <td>27.235246</td>\n",
              "      <td>24.882883</td>\n",
              "      <td>32.069231</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>82.653465</td>\n",
              "      <td>1001.716216</td>\n",
              "      <td>1012.100000</td>\n",
              "      <td>10.176471</td>\n",
              "      <td>1.075546</td>\n",
              "      <td>5.17500</td>\n",
              "      <td>5.283333</td>\n",
              "      <td>2.597143</td>\n",
              "      <td>84.051471</td>\n",
              "      <td>1.025690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82042</th>\n",
              "      <td>4.133333</td>\n",
              "      <td>26.858163</td>\n",
              "      <td>24.436145</td>\n",
              "      <td>32.003448</td>\n",
              "      <td>22.071875</td>\n",
              "      <td>83.881579</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.578947</td>\n",
              "      <td>0.445155</td>\n",
              "      <td>5.86000</td>\n",
              "      <td>5.754639</td>\n",
              "      <td>2.345455</td>\n",
              "      <td>83.840000</td>\n",
              "      <td>0.467799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>3.716327</td>\n",
              "      <td>28.204027</td>\n",
              "      <td>25.416779</td>\n",
              "      <td>31.976000</td>\n",
              "      <td>23.632000</td>\n",
              "      <td>79.320611</td>\n",
              "      <td>1010.518571</td>\n",
              "      <td>1012.216667</td>\n",
              "      <td>5.694656</td>\n",
              "      <td>1.385906</td>\n",
              "      <td>8.23750</td>\n",
              "      <td>4.687162</td>\n",
              "      <td>2.765306</td>\n",
              "      <td>81.761364</td>\n",
              "      <td>1.290667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>4.888889</td>\n",
              "      <td>25.806329</td>\n",
              "      <td>24.044521</td>\n",
              "      <td>30.796296</td>\n",
              "      <td>21.407547</td>\n",
              "      <td>87.307087</td>\n",
              "      <td>1003.087736</td>\n",
              "      <td>1007.000000</td>\n",
              "      <td>9.503937</td>\n",
              "      <td>1.180905</td>\n",
              "      <td>4.65625</td>\n",
              "      <td>5.431250</td>\n",
              "      <td>1.298000</td>\n",
              "      <td>88.738372</td>\n",
              "      <td>1.182592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82113</th>\n",
              "      <td>6.386538</td>\n",
              "      <td>26.638000</td>\n",
              "      <td>24.857746</td>\n",
              "      <td>32.082000</td>\n",
              "      <td>21.821569</td>\n",
              "      <td>86.439024</td>\n",
              "      <td>999.248611</td>\n",
              "      <td>NaN</td>\n",
              "      <td>13.333333</td>\n",
              "      <td>1.276955</td>\n",
              "      <td>6.70000</td>\n",
              "      <td>3.563333</td>\n",
              "      <td>1.847368</td>\n",
              "      <td>87.191860</td>\n",
              "      <td>1.266859</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 prec       tair         tw  ...      evap         ur        ws\n",
              "date  id                                     ...                               \n",
              "08-01 82024  6.219512  27.235246  24.882883  ...  2.597143  84.051471  1.025690\n",
              "      82042  4.133333  26.858163  24.436145  ...  2.345455  83.840000  0.467799\n",
              "      82098  3.716327  28.204027  25.416779  ...  2.765306  81.761364  1.290667\n",
              "      82106  4.888889  25.806329  24.044521  ...  1.298000  88.738372  1.182592\n",
              "      82113  6.386538  26.638000  24.857746  ...  1.847368  87.191860  1.266859\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aW5OvSRbkz9v",
        "colab_type": "text"
      },
      "source": [
        "Head do Dataset de 2019:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yo9EQcoaFGrS",
        "colab_type": "code",
        "outputId": "fb594d63-583f-40a1-d544-5f6641c9e90a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "df_2019.head()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>6.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>47.8</td>\n",
              "      <td>24.100000</td>\n",
              "      <td>34.4</td>\n",
              "      <td>22.0</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>81.0</td>\n",
              "      <td>91.500000</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>3.7</td>\n",
              "      <td>8.9</td>\n",
              "      <td>1009.466667</td>\n",
              "      <td>1011.166667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.066667</td>\n",
              "      <td>33.2</td>\n",
              "      <td>26.6</td>\n",
              "      <td>26.400000</td>\n",
              "      <td>74.5</td>\n",
              "      <td>72.666667</td>\n",
              "      <td>7.666667</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>9.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.1</td>\n",
              "      <td>25.550000</td>\n",
              "      <td>30.9</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>93.0</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>4.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.5</td>\n",
              "      <td>1010.533333</td>\n",
              "      <td>1011.833333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.766667</td>\n",
              "      <td>32.0</td>\n",
              "      <td>27.4</td>\n",
              "      <td>26.300000</td>\n",
              "      <td>77.0</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>14.333333</td>\n",
              "      <td>2.733333</td>\n",
              "      <td>2.733333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>4.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.8</td>\n",
              "      <td>1007.500000</td>\n",
              "      <td>1011.766667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.133333</td>\n",
              "      <td>32.6</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.666667</td>\n",
              "      <td>84.0</td>\n",
              "      <td>82.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>0.533333</td>\n",
              "      <td>0.533333</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   cc  evap     n  ...         wd        ws     wsmax\n",
              "date  id                           ...                               \n",
              "08-01 82024  6.250000   NaN   9.6  ...  11.500000  0.514440  0.514440\n",
              "      82098  6.333333   3.7   8.9  ...   7.666667  1.666667  2.000000\n",
              "      82106  9.000000   NaN   NaN  ...   4.500000  0.514440  0.514440\n",
              "      82141  5.000000   0.3  10.5  ...  14.333333  2.733333  2.733333\n",
              "      82145  4.333333   1.0   9.8  ...  15.000000  0.533333  0.533333\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MSMfUu1VlItZ",
        "colab_type": "text"
      },
      "source": [
        "Para calcular a diferença entre os Dados de 2019 e o Baseline, vamos realizar um Merge Horizontal entre os dois Datasets e subtrair as colunas equivalentes uma da outra:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zEXDcknSHG01",
        "colab_type": "code",
        "outputId": "75cf286b-25d4-47b8-81d4-54308602b199",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "df_merged = pd.merge(df_2019,df,on=['date','id'])\n",
        "df_merged.head()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th></th>\n",
              "      <th>cc_x</th>\n",
              "      <th>evap_x</th>\n",
              "      <th>n_x</th>\n",
              "      <th>patm_x</th>\n",
              "      <th>pnmm_x</th>\n",
              "      <th>prec_x</th>\n",
              "      <th>tair_x</th>\n",
              "      <th>tmax_x</th>\n",
              "      <th>tmin_x</th>\n",
              "      <th>tw_x</th>\n",
              "      <th>ur_x</th>\n",
              "      <th>urmax_x</th>\n",
              "      <th>wd_x</th>\n",
              "      <th>ws_x</th>\n",
              "      <th>wsmax_x</th>\n",
              "      <th>prec_y</th>\n",
              "      <th>tair_y</th>\n",
              "      <th>tw_y</th>\n",
              "      <th>tmax_y</th>\n",
              "      <th>tmin_y</th>\n",
              "      <th>urmax_y</th>\n",
              "      <th>patm_y</th>\n",
              "      <th>pnmm_y</th>\n",
              "      <th>wd_y</th>\n",
              "      <th>wsmax_y</th>\n",
              "      <th>n_y</th>\n",
              "      <th>cc_y</th>\n",
              "      <th>evap_y</th>\n",
              "      <th>ur_y</th>\n",
              "      <th>ws_y</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>6.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>47.8</td>\n",
              "      <td>24.100000</td>\n",
              "      <td>34.4</td>\n",
              "      <td>22.0</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>81.0</td>\n",
              "      <td>91.500000</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>6.219512</td>\n",
              "      <td>27.235246</td>\n",
              "      <td>24.882883</td>\n",
              "      <td>32.069231</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>82.653465</td>\n",
              "      <td>1001.716216</td>\n",
              "      <td>1012.100000</td>\n",
              "      <td>10.176471</td>\n",
              "      <td>1.075546</td>\n",
              "      <td>5.175000</td>\n",
              "      <td>5.283333</td>\n",
              "      <td>2.597143</td>\n",
              "      <td>84.051471</td>\n",
              "      <td>1.025690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>3.7</td>\n",
              "      <td>8.9</td>\n",
              "      <td>1009.466667</td>\n",
              "      <td>1011.166667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.066667</td>\n",
              "      <td>33.2</td>\n",
              "      <td>26.6</td>\n",
              "      <td>26.400000</td>\n",
              "      <td>74.5</td>\n",
              "      <td>72.666667</td>\n",
              "      <td>7.666667</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.716327</td>\n",
              "      <td>28.204027</td>\n",
              "      <td>25.416779</td>\n",
              "      <td>31.976000</td>\n",
              "      <td>23.632000</td>\n",
              "      <td>79.320611</td>\n",
              "      <td>1010.518571</td>\n",
              "      <td>1012.216667</td>\n",
              "      <td>5.694656</td>\n",
              "      <td>1.385906</td>\n",
              "      <td>8.237500</td>\n",
              "      <td>4.687162</td>\n",
              "      <td>2.765306</td>\n",
              "      <td>81.761364</td>\n",
              "      <td>1.290667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>9.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.1</td>\n",
              "      <td>25.550000</td>\n",
              "      <td>30.9</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>93.0</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>4.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>4.888889</td>\n",
              "      <td>25.806329</td>\n",
              "      <td>24.044521</td>\n",
              "      <td>30.796296</td>\n",
              "      <td>21.407547</td>\n",
              "      <td>87.307087</td>\n",
              "      <td>1003.087736</td>\n",
              "      <td>1007.000000</td>\n",
              "      <td>9.503937</td>\n",
              "      <td>1.180905</td>\n",
              "      <td>4.656250</td>\n",
              "      <td>5.431250</td>\n",
              "      <td>1.298000</td>\n",
              "      <td>88.738372</td>\n",
              "      <td>1.182592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.5</td>\n",
              "      <td>1010.533333</td>\n",
              "      <td>1011.833333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.766667</td>\n",
              "      <td>32.0</td>\n",
              "      <td>27.4</td>\n",
              "      <td>26.300000</td>\n",
              "      <td>77.0</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>14.333333</td>\n",
              "      <td>2.733333</td>\n",
              "      <td>2.733333</td>\n",
              "      <td>4.429091</td>\n",
              "      <td>28.562048</td>\n",
              "      <td>25.538922</td>\n",
              "      <td>31.333962</td>\n",
              "      <td>24.365385</td>\n",
              "      <td>77.657718</td>\n",
              "      <td>1011.978523</td>\n",
              "      <td>1012.652083</td>\n",
              "      <td>7.856164</td>\n",
              "      <td>2.243902</td>\n",
              "      <td>9.070909</td>\n",
              "      <td>2.986228</td>\n",
              "      <td>2.694444</td>\n",
              "      <td>79.305000</td>\n",
              "      <td>2.241212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>4.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.8</td>\n",
              "      <td>1007.500000</td>\n",
              "      <td>1011.766667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.133333</td>\n",
              "      <td>32.6</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.666667</td>\n",
              "      <td>84.0</td>\n",
              "      <td>82.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>0.533333</td>\n",
              "      <td>0.533333</td>\n",
              "      <td>3.228889</td>\n",
              "      <td>27.343966</td>\n",
              "      <td>25.033621</td>\n",
              "      <td>31.532500</td>\n",
              "      <td>20.511628</td>\n",
              "      <td>83.172414</td>\n",
              "      <td>1008.446078</td>\n",
              "      <td>1012.684091</td>\n",
              "      <td>7.422680</td>\n",
              "      <td>1.191753</td>\n",
              "      <td>8.190909</td>\n",
              "      <td>4.073770</td>\n",
              "      <td>2.139535</td>\n",
              "      <td>85.653846</td>\n",
              "      <td>1.192929</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 cc_x  evap_x   n_x  ...    evap_y       ur_y      ws_y\n",
              "date  id                             ...                               \n",
              "08-01 82024  6.250000     NaN   9.6  ...  2.597143  84.051471  1.025690\n",
              "      82098  6.333333     3.7   8.9  ...  2.765306  81.761364  1.290667\n",
              "      82106  9.000000     NaN   NaN  ...  1.298000  88.738372  1.182592\n",
              "      82141  5.000000     0.3  10.5  ...  2.694444  79.305000  2.241212\n",
              "      82145  4.333333     1.0   9.8  ...  2.139535  85.653846  1.192929\n",
              "\n",
              "[5 rows x 30 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HyWO1zjn9AaF",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "diff = pd.DataFrame()\n",
        "measures = ['tair','tmax','tmin','tw']\n",
        "for column in measures:\n",
        "  diff[column] =  abs(df_merged[column+'_x'] - df_merged[column+'_y'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wtiMoaLklvOA",
        "colab_type": "text"
      },
      "source": [
        "Head do Resultado (diff):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3HZ4ViZ_PbaX",
        "colab_type": "code",
        "outputId": "756f492a-1679-45dc-9d7d-134e3f30dba1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        }
      },
      "source": [
        "diff.head(1000)"
      ],
      "execution_count": 24,
      "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></th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>3.135246</td>\n",
              "      <td>2.330769</td>\n",
              "      <td>1.400000</td>\n",
              "      <td>1.482883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>1.862640</td>\n",
              "      <td>1.224000</td>\n",
              "      <td>2.968000</td>\n",
              "      <td>0.983221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>0.256329</td>\n",
              "      <td>0.103704</td>\n",
              "      <td>0.892453</td>\n",
              "      <td>1.455479</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>1.204618</td>\n",
              "      <td>0.666038</td>\n",
              "      <td>3.034615</td>\n",
              "      <td>0.761078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>0.789368</td>\n",
              "      <td>1.067500</td>\n",
              "      <td>1.788372</td>\n",
              "      <td>0.633046</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-06</th>\n",
              "      <th>83565</th>\n",
              "      <td>4.729023</td>\n",
              "      <td>7.289189</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.195942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83579</th>\n",
              "      <td>3.758156</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.853191</td>\n",
              "      <td>1.361594</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83587</th>\n",
              "      <td>2.410766</td>\n",
              "      <td>4.507407</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>0.806329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83589</th>\n",
              "      <td>0.210173</td>\n",
              "      <td>3.923077</td>\n",
              "      <td>4.930769</td>\n",
              "      <td>1.080313</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83592</th>\n",
              "      <td>0.192402</td>\n",
              "      <td>2.373913</td>\n",
              "      <td>2.275556</td>\n",
              "      <td>0.013784</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1000 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 tair      tmax      tmin        tw\n",
              "date  id                                           \n",
              "08-01 82024  3.135246  2.330769  1.400000  1.482883\n",
              "      82098  1.862640  1.224000  2.968000  0.983221\n",
              "      82106  0.256329  0.103704  0.892453  1.455479\n",
              "      82141  1.204618  0.666038  3.034615  0.761078\n",
              "      82145  0.789368  1.067500  1.788372  0.633046\n",
              "...               ...       ...       ...       ...\n",
              "08-06 83565  4.729023  7.289189       NaN  0.195942\n",
              "      83579  3.758156       NaN  0.853191  1.361594\n",
              "      83587  2.410766  4.507407  0.800000  0.806329\n",
              "      83589  0.210173  3.923077  4.930769  1.080313\n",
              "      83592  0.192402  2.373913  2.275556  0.013784\n",
              "\n",
              "[1000 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GesGLW2umJVf",
        "colab_type": "text"
      },
      "source": [
        "Algoritmos para Download do Resultado em formato.csv:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yzZBwYiT_GUX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#diff.to_csv('./diff_temp.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dit0WWJXCYdO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from google.colab import files\n",
        "#files.download('diff_temp.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QTgTf12I1fYb",
        "colab_type": "text"
      },
      "source": [
        "## Cálculo de PCA"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wt-h3DKrmzEh",
        "colab_type": "text"
      },
      "source": [
        "Dataset do Baseline pré-processado, sem Group By:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-vvyTdm42PcV",
        "colab_type": "code",
        "outputId": "48ee2297-07d3-44e9-c35d-d2d4ea85efca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df_pre_gp.head()"
      ],
      "execution_count": 27,
      "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>date</th>\n",
              "      <th>id</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tw</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>urmax</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>wd</th>\n",
              "      <th>wsmax</th>\n",
              "      <th>n</th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>ur</th>\n",
              "      <th>ws</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>53402</th>\n",
              "      <td>08-01</td>\n",
              "      <td>82915</td>\n",
              "      <td>NaN</td>\n",
              "      <td>25.0</td>\n",
              "      <td>22.8</td>\n",
              "      <td>35.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>84.0</td>\n",
              "      <td>1010.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.6</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>74.75</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53403</th>\n",
              "      <td>08-01</td>\n",
              "      <td>82915</td>\n",
              "      <td>0.0</td>\n",
              "      <td>22.2</td>\n",
              "      <td>21.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19.7</td>\n",
              "      <td>94.0</td>\n",
              "      <td>1000.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53404</th>\n",
              "      <td>08-01</td>\n",
              "      <td>82915</td>\n",
              "      <td>NaN</td>\n",
              "      <td>33.8</td>\n",
              "      <td>27.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>999.2</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>53405</th>\n",
              "      <td>08-02</td>\n",
              "      <td>82915</td>\n",
              "      <td>NaN</td>\n",
              "      <td>26.8</td>\n",
              "      <td>24.8</td>\n",
              "      <td>33.8</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>996.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.5</td>\n",
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              "      <td>2.1</td>\n",
              "      <td>83.50</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53406</th>\n",
              "      <td>08-02</td>\n",
              "      <td>82915</td>\n",
              "      <td>21.9</td>\n",
              "      <td>11.8</td>\n",
              "      <td>11.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.2</td>\n",
              "      <td>90.0</td>\n",
              "      <td>1009.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        date     id  prec  tair    tw  tmax  ...  wsmax    n   cc  evap     ur   ws\n",
              "53402  08-01  82915   NaN  25.0  22.8  35.0  ...    NaN  5.6  4.0   3.2  74.75  0.0\n",
              "53403  08-01  82915   0.0  22.2  21.6   NaN  ...    0.0  NaN  7.0   NaN    NaN  NaN\n",
              "53404  08-01  82915   NaN  33.8  27.0   NaN  ...    0.0  NaN  7.0   NaN    NaN  NaN\n",
              "53405  08-02  82915   NaN  26.8  24.8  33.8  ...    NaN  3.5  6.0   2.1  83.50  NaN\n",
              "53406  08-02  82915  21.9  11.8  11.0   NaN  ...    NaN  NaN  8.0   NaN    NaN  NaN\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lYjUvmwEm84W",
        "colab_type": "text"
      },
      "source": [
        "Dataset de 2019 pré-processado, sem Group By:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FR96Jc-kBCKT",
        "colab_type": "code",
        "outputId": "addb71b9-f9d4-4b6f-e3f3-d09a3c0c968b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df_2019_pre_gp.head()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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            "text/plain": [
              "        cc   date  evap     id    n  ...     ur  urmax   wd       ws    wsmax\n",
              "573   6.25  08-01   NaN  82487  6.4  ...  87.50   95.0  9.0  3.25812  3.08664\n",
              "574  10.00  08-01   NaN  82487  NaN  ...    NaN   92.0  9.0      NaN  3.60108\n",
              "575   5.00  08-01   NaN  82487  NaN  ...    NaN   68.0  5.0      NaN  3.08664\n",
              "576  10.00  08-02   NaN  82487  6.3  ...  87.75   95.0  5.0  3.08664  3.08664\n",
              "577  10.00  08-02   NaN  82487  NaN  ...    NaN   93.0  9.0      NaN  3.08664\n",
              "\n",
              "[5 rows x 17 columns]"
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          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jwcZLTroBU4n",
        "colab_type": "text"
      },
      "source": [
        "Cocatenando os dois Dataframes Verticalmente:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Tx6Ad2DR9R9z",
        "colab_type": "code",
        "outputId": "9efd3aae-70c1-4124-c5aa-861a2f2b9014",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 555
        }
      },
      "source": [
        "X = pd.concat([df_pre_gp,df_2019_pre_gp])\n",
        "X"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
            "of pandas will change to not sort by default.\n",
            "\n",
            "To accept the future behavior, pass 'sort=False'.\n",
            "\n",
            "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
            "\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20.0</td>\n",
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              "      <td>NaN</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>808829 rows × 17 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         cc   date  evap     id     n  ...     ur  urmax    wd       ws    wsmax\n",
              "53402  4.00  08-01   3.2  82915   5.6  ...  74.75   84.0   NaN  0.00000      NaN\n",
              "53403  7.00  08-01   NaN  82915   NaN  ...    NaN   94.0   0.0      NaN  0.00000\n",
              "53404  7.00  08-01   NaN  82915   NaN  ...    NaN   57.0   0.0      NaN  0.00000\n",
              "53405  6.00  08-02   2.1  82915   3.5  ...  83.50   74.0   NaN      NaN      NaN\n",
              "53406  8.00  08-02   NaN  82915   NaN  ...    NaN   90.0   NaN      NaN      NaN\n",
              "...     ...    ...   ...    ...   ...  ...    ...    ...   ...      ...      ...\n",
              "724    0.00  08-30   NaN  83228   NaN  ...    NaN   37.0   9.0      NaN  2.57220\n",
              "725    1.25  08-30   NaN  83228   NaN  ...    NaN   21.0   5.0      NaN  2.05776\n",
              "726    0.00  08-31   NaN  83228  10.4  ...  37.25   52.0   0.0  1.88628  0.00000\n",
              "727    2.50  08-31   NaN  83228   NaN  ...    NaN   35.0   9.0      NaN  3.60108\n",
              "728    3.75  08-31   NaN  83228   NaN  ...    NaN   20.0  14.0      NaN  2.05776\n",
              "\n",
              "[808829 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zRyjIJ3inSdD",
        "colab_type": "text"
      },
      "source": [
        "Realizando um Group By por Date e Id:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3WeLo7QcBZdo",
        "colab_type": "code",
        "outputId": "4f3587f8-08a6-4c28-e363-09505e0ca6d2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        }
      },
      "source": [
        "X = X.groupby(by=['date','id']).mean()\n",
        "X"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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            "text/plain": [
              "                   cc      evap         n  ...         wd        ws     wsmax\n",
              "date  id                                   ...                               \n",
              "08-01 82024  5.298800  2.597143  5.309091  ...  10.201923  1.013518  1.066496\n",
              "      82042  5.754639  2.345455  5.860000  ...   3.578947  0.467799  0.445155\n",
              "      82098  4.719868  2.784000  8.251020  ...   5.738806  1.298039  1.398026\n",
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              "      82113  3.563333  1.847368  6.700000  ...  13.333333  1.266859  1.276955\n",
              "...               ...       ...       ...  ...        ...       ...       ...\n",
              "08-31 83967  5.215839  2.359615  4.674074  ...  15.403727  2.106845  2.140708\n",
              "      83980  4.631579  3.256000  4.938000  ...  15.546667  3.246771  3.115013\n",
              "      83985  6.345455  2.354054  5.303571  ...  13.719626  3.071296  2.985981\n",
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              "\n",
              "[6045 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ue-QqafsI42W",
        "colab_type": "text"
      },
      "source": [
        "Filtrando para dia 19:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YUqMPdmCI7TT",
        "colab_type": "code",
        "outputId": "c64609ad-358e-4ebb-8fa0-c0f74c7990f4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        }
      },
      "source": [
        "X = X.loc['08-19']\n",
        "X"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>83967</th>\n",
              "      <td>4.875000</td>\n",
              "      <td>1.915094</td>\n",
              "      <td>5.087273</td>\n",
              "      <td>1014.116463</td>\n",
              "      <td>1018.227778</td>\n",
              "      <td>2.505455</td>\n",
              "      <td>17.079878</td>\n",
              "      <td>21.738182</td>\n",
              "      <td>11.756364</td>\n",
              "      <td>14.266456</td>\n",
              "      <td>77.036364</td>\n",
              "      <td>75.018293</td>\n",
              "      <td>13.682927</td>\n",
              "      <td>1.788841</td>\n",
              "      <td>1.815779</td>\n",
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              "    <tr>\n",
              "      <th>83980</th>\n",
              "      <td>4.466667</td>\n",
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              "      <td>1017.598148</td>\n",
              "      <td>3.691837</td>\n",
              "      <td>14.524324</td>\n",
              "      <td>19.293750</td>\n",
              "      <td>9.333333</td>\n",
              "      <td>11.719595</td>\n",
              "      <td>72.898936</td>\n",
              "      <td>71.959459</td>\n",
              "      <td>14.864865</td>\n",
              "      <td>3.103401</td>\n",
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              "    <tr>\n",
              "      <th>83985</th>\n",
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              "      <td>1017.783929</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.880556</td>\n",
              "      <td>14.941964</td>\n",
              "      <td>19.111429</td>\n",
              "      <td>9.568571</td>\n",
              "      <td>13.271429</td>\n",
              "      <td>85.317568</td>\n",
              "      <td>82.598214</td>\n",
              "      <td>13.747748</td>\n",
              "      <td>3.032432</td>\n",
              "      <td>2.900000</td>\n",
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              "      <th>83995</th>\n",
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              "      <td>1018.284173</td>\n",
              "      <td>1018.325641</td>\n",
              "      <td>2.400000</td>\n",
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              "      <td>17.834783</td>\n",
              "      <td>11.371111</td>\n",
              "      <td>13.166906</td>\n",
              "      <td>83.880435</td>\n",
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              "      <td>14.733813</td>\n",
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              "      <th>83997</th>\n",
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              "      <td>1020.448148</td>\n",
              "      <td>4.555102</td>\n",
              "      <td>13.461268</td>\n",
              "      <td>17.583673</td>\n",
              "      <td>9.159184</td>\n",
              "      <td>11.773239</td>\n",
              "      <td>83.213542</td>\n",
              "      <td>81.492958</td>\n",
              "      <td>15.169014</td>\n",
              "      <td>3.642857</td>\n",
              "      <td>3.496063</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>195 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             cc      evap         n  ...         wd        ws     wsmax\n",
              "id                                   ...                               \n",
              "82024  5.462602  3.236364  5.743333  ...   9.639175  1.158565  1.211875\n",
              "82042  5.805392  2.450000  6.435000  ...   3.291139  0.670222  0.677841\n",
              "82098  4.677419  3.148077  8.900000  ...   8.355072  1.967949  2.023718\n",
              "82106  4.884431  1.460784  4.891837  ...  11.613636  1.193914  1.194979\n",
              "82113  3.887908  1.776316  5.665909  ...  15.712000  1.223741  1.279382\n",
              "...         ...       ...       ...  ...        ...       ...       ...\n",
              "83967  4.875000  1.915094  5.087273  ...  13.682927  1.788841  1.815779\n",
              "83980  4.466667  3.479592  4.420408  ...  14.864865  3.103401  2.926351\n",
              "83985  6.428571  2.543243  4.425000  ...  13.747748  3.032432  2.900000\n",
              "83995  5.848921  2.447826  4.512195  ...  14.733813  2.583333  2.670504\n",
              "83997  5.288732  1.979592  5.129787  ...  15.169014  3.642857  3.496063\n",
              "\n",
              "[195 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oiZKq9qn9euq",
        "colab_type": "text"
      },
      "source": [
        "Decompondo Wd em Coordenadas Retangulares:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ba9MZ3gU9g6m",
        "colab_type": "code",
        "outputId": "2f24a4b8-1170-43a6-a6cb-a11df375c72a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        }
      },
      "source": [
        "X['wd'] = X['wd'].multiply(np.pi/180)\n",
        "X['wd_cos'] = X['wd'].apply(np.cos)\n",
        "X['wd_sin'] = X['wd'].apply(np.sin)\n",
        "X = X.drop('wd',axis=1)\n",
        "X"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>82106</th>\n",
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              "      <td>11.719595</td>\n",
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              "      <td>71.959459</td>\n",
              "      <td>3.103401</td>\n",
              "      <td>2.926351</td>\n",
              "      <td>0.966534</td>\n",
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              "      <th>83985</th>\n",
              "      <td>6.428571</td>\n",
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              "      <td>4.425000</td>\n",
              "      <td>1017.783929</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.880556</td>\n",
              "      <td>14.941964</td>\n",
              "      <td>19.111429</td>\n",
              "      <td>9.568571</td>\n",
              "      <td>13.271429</td>\n",
              "      <td>85.317568</td>\n",
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              "      <td>1.979592</td>\n",
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              "      <td>13.461268</td>\n",
              "      <td>17.583673</td>\n",
              "      <td>9.159184</td>\n",
              "      <td>11.773239</td>\n",
              "      <td>83.213542</td>\n",
              "      <td>81.492958</td>\n",
              "      <td>3.642857</td>\n",
              "      <td>3.496063</td>\n",
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              "      <td>0.261667</td>\n",
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              "<p>195 rows × 16 columns</p>\n",
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            "text/plain": [
              "             cc      evap         n  ...     wsmax    wd_cos    wd_sin\n",
              "id                                   ...                              \n",
              "82024  5.462602  3.236364  5.743333  ...  1.211875  0.985882  0.167443\n",
              "82042  5.805392  2.450000  6.435000  ...  0.677841  0.998351  0.057410\n",
              "82098  4.677419  3.148077  8.900000  ...  2.023718  0.989387  0.145307\n",
              "82106  4.884431  1.460784  4.891837  ...  1.194979  0.979527  0.201311\n",
              "82113  3.887908  1.776316  5.665909  ...  1.279382  0.962635  0.270802\n",
              "...         ...       ...       ...  ...       ...       ...       ...\n",
              "83967  4.875000  1.915094  5.087273  ...  1.815779  0.971620  0.236549\n",
              "83980  4.466667  3.479592  4.420408  ...  2.926351  0.966534  0.256540\n",
              "83985  6.428571  2.543243  4.425000  ...  2.900000  0.971351  0.237648\n",
              "83995  5.848921  2.447826  4.512195  ...  2.670504  0.967118  0.254329\n",
              "83997  5.288732  1.979592  5.129787  ...  3.496063  0.965158  0.261667\n",
              "\n",
              "[195 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kRBRkI9yJ4kN",
        "colab_type": "text"
      },
      "source": [
        "Dropando NaN's:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XNLn22enJ72o",
        "colab_type": "code",
        "outputId": "5112ef60-29c5-4f42-e9c4-180daaadf73d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        }
      },
      "source": [
        "X = X.dropna()\n",
        "X"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>wd_cos</th>\n",
              "      <th>wd_sin</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>82024</th>\n",
              "      <td>5.462602</td>\n",
              "      <td>3.236364</td>\n",
              "      <td>5.743333</td>\n",
              "      <td>1001.922857</td>\n",
              "      <td>1011.650000</td>\n",
              "      <td>7.351282</td>\n",
              "      <td>27.880992</td>\n",
              "      <td>32.912821</td>\n",
              "      <td>23.513514</td>\n",
              "      <td>25.115741</td>\n",
              "      <td>81.712121</td>\n",
              "      <td>80.226804</td>\n",
              "      <td>1.158565</td>\n",
              "      <td>1.211875</td>\n",
              "      <td>0.985882</td>\n",
              "      <td>0.167443</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>4.677419</td>\n",
              "      <td>3.148077</td>\n",
              "      <td>8.900000</td>\n",
              "      <td>1010.198639</td>\n",
              "      <td>1011.883333</td>\n",
              "      <td>2.232692</td>\n",
              "      <td>28.639103</td>\n",
              "      <td>32.275000</td>\n",
              "      <td>23.905882</td>\n",
              "      <td>25.633974</td>\n",
              "      <td>79.266304</td>\n",
              "      <td>78.536232</td>\n",
              "      <td>1.967949</td>\n",
              "      <td>2.023718</td>\n",
              "      <td>0.989387</td>\n",
              "      <td>0.145307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>4.884431</td>\n",
              "      <td>1.460784</td>\n",
              "      <td>4.891837</td>\n",
              "      <td>993.564545</td>\n",
              "      <td>1009.966667</td>\n",
              "      <td>8.489474</td>\n",
              "      <td>26.081212</td>\n",
              "      <td>31.462500</td>\n",
              "      <td>21.389091</td>\n",
              "      <td>24.205405</td>\n",
              "      <td>87.139535</td>\n",
              "      <td>86.522727</td>\n",
              "      <td>1.193914</td>\n",
              "      <td>1.194979</td>\n",
              "      <td>0.979527</td>\n",
              "      <td>0.201311</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>3.233333</td>\n",
              "      <td>2.994444</td>\n",
              "      <td>8.546296</td>\n",
              "      <td>1011.428000</td>\n",
              "      <td>1011.285417</td>\n",
              "      <td>2.443103</td>\n",
              "      <td>28.552976</td>\n",
              "      <td>31.315385</td>\n",
              "      <td>24.628302</td>\n",
              "      <td>25.534524</td>\n",
              "      <td>79.020000</td>\n",
              "      <td>77.751678</td>\n",
              "      <td>2.504242</td>\n",
              "      <td>2.607273</td>\n",
              "      <td>0.988185</td>\n",
              "      <td>0.153267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>4.627119</td>\n",
              "      <td>2.321951</td>\n",
              "      <td>8.109524</td>\n",
              "      <td>1008.248980</td>\n",
              "      <td>1012.557407</td>\n",
              "      <td>2.313953</td>\n",
              "      <td>27.269565</td>\n",
              "      <td>31.854054</td>\n",
              "      <td>20.870000</td>\n",
              "      <td>25.053913</td>\n",
              "      <td>85.901316</td>\n",
              "      <td>83.686957</td>\n",
              "      <td>1.151111</td>\n",
              "      <td>1.117582</td>\n",
              "      <td>0.994602</td>\n",
              "      <td>0.103765</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83964</th>\n",
              "      <td>4.283688</td>\n",
              "      <td>2.297872</td>\n",
              "      <td>5.029787</td>\n",
              "      <td>968.835461</td>\n",
              "      <td>1018.205556</td>\n",
              "      <td>1.708511</td>\n",
              "      <td>14.759859</td>\n",
              "      <td>19.414894</td>\n",
              "      <td>9.957447</td>\n",
              "      <td>11.925352</td>\n",
              "      <td>74.367021</td>\n",
              "      <td>71.816901</td>\n",
              "      <td>1.748672</td>\n",
              "      <td>1.886883</td>\n",
              "      <td>0.958697</td>\n",
              "      <td>0.284431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83967</th>\n",
              "      <td>4.875000</td>\n",
              "      <td>1.915094</td>\n",
              "      <td>5.087273</td>\n",
              "      <td>1014.116463</td>\n",
              "      <td>1018.227778</td>\n",
              "      <td>2.505455</td>\n",
              "      <td>17.079878</td>\n",
              "      <td>21.738182</td>\n",
              "      <td>11.756364</td>\n",
              "      <td>14.266456</td>\n",
              "      <td>77.036364</td>\n",
              "      <td>75.018293</td>\n",
              "      <td>1.788841</td>\n",
              "      <td>1.815779</td>\n",
              "      <td>0.971620</td>\n",
              "      <td>0.236549</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83980</th>\n",
              "      <td>4.466667</td>\n",
              "      <td>3.479592</td>\n",
              "      <td>4.420408</td>\n",
              "      <td>991.535811</td>\n",
              "      <td>1017.598148</td>\n",
              "      <td>3.691837</td>\n",
              "      <td>14.524324</td>\n",
              "      <td>19.293750</td>\n",
              "      <td>9.333333</td>\n",
              "      <td>11.719595</td>\n",
              "      <td>72.898936</td>\n",
              "      <td>71.959459</td>\n",
              "      <td>3.103401</td>\n",
              "      <td>2.926351</td>\n",
              "      <td>0.966534</td>\n",
              "      <td>0.256540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83995</th>\n",
              "      <td>5.848921</td>\n",
              "      <td>2.447826</td>\n",
              "      <td>4.512195</td>\n",
              "      <td>1018.284173</td>\n",
              "      <td>1018.325641</td>\n",
              "      <td>2.400000</td>\n",
              "      <td>14.813669</td>\n",
              "      <td>17.834783</td>\n",
              "      <td>11.371111</td>\n",
              "      <td>13.166906</td>\n",
              "      <td>83.880435</td>\n",
              "      <td>82.201439</td>\n",
              "      <td>2.583333</td>\n",
              "      <td>2.670504</td>\n",
              "      <td>0.967118</td>\n",
              "      <td>0.254329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83997</th>\n",
              "      <td>5.288732</td>\n",
              "      <td>1.979592</td>\n",
              "      <td>5.129787</td>\n",
              "      <td>1015.400704</td>\n",
              "      <td>1020.448148</td>\n",
              "      <td>4.555102</td>\n",
              "      <td>13.461268</td>\n",
              "      <td>17.583673</td>\n",
              "      <td>9.159184</td>\n",
              "      <td>11.773239</td>\n",
              "      <td>83.213542</td>\n",
              "      <td>81.492958</td>\n",
              "      <td>3.642857</td>\n",
              "      <td>3.496063</td>\n",
              "      <td>0.965158</td>\n",
              "      <td>0.261667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>168 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             cc      evap         n  ...     wsmax    wd_cos    wd_sin\n",
              "id                                   ...                              \n",
              "82024  5.462602  3.236364  5.743333  ...  1.211875  0.985882  0.167443\n",
              "82098  4.677419  3.148077  8.900000  ...  2.023718  0.989387  0.145307\n",
              "82106  4.884431  1.460784  4.891837  ...  1.194979  0.979527  0.201311\n",
              "82141  3.233333  2.994444  8.546296  ...  2.607273  0.988185  0.153267\n",
              "82145  4.627119  2.321951  8.109524  ...  1.117582  0.994602  0.103765\n",
              "...         ...       ...       ...  ...       ...       ...       ...\n",
              "83964  4.283688  2.297872  5.029787  ...  1.886883  0.958697  0.284431\n",
              "83967  4.875000  1.915094  5.087273  ...  1.815779  0.971620  0.236549\n",
              "83980  4.466667  3.479592  4.420408  ...  2.926351  0.966534  0.256540\n",
              "83995  5.848921  2.447826  4.512195  ...  2.670504  0.967118  0.254329\n",
              "83997  5.288732  1.979592  5.129787  ...  3.496063  0.965158  0.261667\n",
              "\n",
              "[168 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XJ_BcwbInh9U",
        "colab_type": "text"
      },
      "source": [
        "Configurando Algoritmo de Normalização e PCA:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zsNINpRNDtv9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.pipeline import Pipeline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l6JrTva33UHs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sc = StandardScaler()\n",
        "pca = PCA(n_components=3)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QqE57NooLXjj",
        "colab_type": "text"
      },
      "source": [
        "Guardando index de X:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jit9F_99LZnA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "index = X.index"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sGt4jug4LeKK",
        "colab_type": "text"
      },
      "source": [
        "Calculando PCA:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9cofTkSVKqZl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = sc.fit_transform(X.values)\n",
        "pca_values = pca.fit_transform(X)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qEirvHiq3QJi",
        "colab_type": "code",
        "outputId": "687e0711-43c3-4cfa-c1c1-1f413bae597d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "pca_values = pd.DataFrame(pca_values)\n",
        "pca_values"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.041286</td>\n",
              "      <td>4.500024</td>\n",
              "      <td>-0.797471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-1.555133</td>\n",
              "      <td>3.488031</td>\n",
              "      <td>0.065955</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.169083</td>\n",
              "      <td>4.503105</td>\n",
              "      <td>-0.881481</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-1.684043</td>\n",
              "      <td>3.227437</td>\n",
              "      <td>0.683155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.972034</td>\n",
              "      <td>3.923929</td>\n",
              "      <td>-1.535067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>163</th>\n",
              "      <td>4.363965</td>\n",
              "      <td>-1.790542</td>\n",
              "      <td>-1.158680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>164</th>\n",
              "      <td>3.640791</td>\n",
              "      <td>0.002124</td>\n",
              "      <td>-1.084213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>165</th>\n",
              "      <td>4.465704</td>\n",
              "      <td>-1.457392</td>\n",
              "      <td>0.109036</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>166</th>\n",
              "      <td>4.963034</td>\n",
              "      <td>-0.145945</td>\n",
              "      <td>0.033667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>167</th>\n",
              "      <td>5.724098</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>1.000193</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>168 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            0         1         2\n",
              "0    0.041286  4.500024 -0.797471\n",
              "1   -1.555133  3.488031  0.065955\n",
              "2    1.169083  4.503105 -0.881481\n",
              "3   -1.684043  3.227437  0.683155\n",
              "4   -0.972034  3.923929 -1.535067\n",
              "..        ...       ...       ...\n",
              "163  4.363965 -1.790542 -1.158680\n",
              "164  3.640791  0.002124 -1.084213\n",
              "165  4.465704 -1.457392  0.109036\n",
              "166  4.963034 -0.145945  0.033667\n",
              "167  5.724098 -0.763114  1.000193\n",
              "\n",
              "[168 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AKFj_HObB22R",
        "colab_type": "text"
      },
      "source": [
        "Concatenando Latitude e Longitude:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uUyIdiegBqco",
        "colab_type": "code",
        "outputId": "931e5f95-97e3-421c-b450-345d54b7a542",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        }
      },
      "source": [
        "pca_values.index = index\n",
        "pca_values"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>82024</th>\n",
              "      <td>0.041286</td>\n",
              "      <td>4.500024</td>\n",
              "      <td>-0.797471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>-1.555133</td>\n",
              "      <td>3.488031</td>\n",
              "      <td>0.065955</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>1.169083</td>\n",
              "      <td>4.503105</td>\n",
              "      <td>-0.881481</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>-1.684043</td>\n",
              "      <td>3.227437</td>\n",
              "      <td>0.683155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>-0.972034</td>\n",
              "      <td>3.923929</td>\n",
              "      <td>-1.535067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83964</th>\n",
              "      <td>4.363965</td>\n",
              "      <td>-1.790542</td>\n",
              "      <td>-1.158680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83967</th>\n",
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              "    <tr>\n",
              "      <th>83980</th>\n",
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              "      <td>-1.457392</td>\n",
              "      <td>0.109036</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83995</th>\n",
              "      <td>4.963034</td>\n",
              "      <td>-0.145945</td>\n",
              "      <td>0.033667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83997</th>\n",
              "      <td>5.724098</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>1.000193</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>168 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              0         1         2\n",
              "id                                 \n",
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              "82141 -1.684043  3.227437  0.683155\n",
              "82145 -0.972034  3.923929 -1.535067\n",
              "...         ...       ...       ...\n",
              "83964  4.363965 -1.790542 -1.158680\n",
              "83967  3.640791  0.002124 -1.084213\n",
              "83980  4.465704 -1.457392  0.109036\n",
              "83995  4.963034 -0.145945  0.033667\n",
              "83997  5.724098 -0.763114  1.000193\n",
              "\n",
              "[168 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-iwdEETg84XK",
        "colab_type": "code",
        "outputId": "14cedd91-ffeb-4af5-96a2-a316ea88980f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "pca_values = pca_values.merge(df_m,on='id')\n",
        "pca_values = pca_values.drop(['alt','name','state','uf','time_zone','offset_utc','time_zone.1','offset_utc.1'],axis=1)\n",
        "pca_values"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>-31.333333</td>\n",
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            "text/plain": [
              "        id         0         1         2        lon        lat\n",
              "0    82024  0.041286  4.500024 -0.797471 -60.650000   2.816667\n",
              "1    82098 -1.555133  3.488031  0.065955 -51.116667  -0.050000\n",
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              "4    82145 -0.972034  3.923929 -1.535067 -46.900000  -1.066667\n",
              "..     ...       ...       ...       ...        ...        ...\n",
              "163  83964  4.363965 -1.790542 -1.158680 -52.516667 -30.533333\n",
              "164  83967  3.640791  0.002124 -1.084213 -51.166667 -30.050000\n",
              "165  83980  4.465704 -1.457392  0.109036 -54.100000 -31.333333\n",
              "166  83995  4.963034 -0.145945  0.033667 -52.100000 -32.033333\n",
              "167  83997  5.724098 -0.763114  1.000193 -53.350000 -33.516667\n",
              "\n",
              "[168 rows x 6 columns]"
            ]
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          "metadata": {
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          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X04c4TKQnrZQ",
        "colab_type": "text"
      },
      "source": [
        "Obtendo as Composição das Componentes Principais:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u4O1pHcrDbL8",
        "colab_type": "code",
        "outputId": "6d173825-55d2-4312-aad3-2471ca962c51",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        }
      },
      "source": [
        "pca_components = pd.DataFrame(pca.components_)\n",
        "pca_components"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th>3</th>\n",
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              "      <th>5</th>\n",
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              "      <th>15</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>0.296371</td>\n",
              "      <td>-0.289575</td>\n",
              "      <td>-0.326861</td>\n",
              "      <td>-0.063397</td>\n",
              "      <td>0.285436</td>\n",
              "      <td>0.228554</td>\n",
              "      <td>-0.342711</td>\n",
              "      <td>-0.359671</td>\n",
              "      <td>-0.245568</td>\n",
              "      <td>-0.216456</td>\n",
              "      <td>0.266651</td>\n",
              "      <td>0.272378</td>\n",
              "      <td>0.049454</td>\n",
              "      <td>0.045730</td>\n",
              "      <td>-0.204857</td>\n",
              "      <td>0.194874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.192971</td>\n",
              "      <td>-0.271494</td>\n",
              "      <td>-0.137052</td>\n",
              "      <td>0.374536</td>\n",
              "      <td>-0.137315</td>\n",
              "      <td>0.247936</td>\n",
              "      <td>0.192682</td>\n",
              "      <td>0.125177</td>\n",
              "      <td>0.325274</td>\n",
              "      <td>0.397580</td>\n",
              "      <td>0.349000</td>\n",
              "      <td>0.343735</td>\n",
              "      <td>-0.112808</td>\n",
              "      <td>-0.115173</td>\n",
              "      <td>0.182234</td>\n",
              "      <td>-0.183964</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.108187</td>\n",
              "      <td>0.134378</td>\n",
              "      <td>0.105924</td>\n",
              "      <td>0.183764</td>\n",
              "      <td>0.002245</td>\n",
              "      <td>0.047521</td>\n",
              "      <td>0.107012</td>\n",
              "      <td>0.012431</td>\n",
              "      <td>0.235960</td>\n",
              "      <td>0.127799</td>\n",
              "      <td>0.035213</td>\n",
              "      <td>0.031312</td>\n",
              "      <td>0.602798</td>\n",
              "      <td>0.603286</td>\n",
              "      <td>-0.211662</td>\n",
              "      <td>0.255009</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         0         1         2   ...        13        14        15\n",
              "0  0.296371 -0.289575 -0.326861  ...  0.045730 -0.204857  0.194874\n",
              "1  0.192971 -0.271494 -0.137052  ... -0.115173  0.182234 -0.183964\n",
              "2  0.108187  0.134378  0.105924  ...  0.603286 -0.211662  0.255009\n",
              "\n",
              "[3 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xLEetILeJS-y",
        "colab_type": "text"
      },
      "source": [
        "Analisando o Percentual de Variabilidade Explicada:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3sSETE1IJYpM",
        "colab_type": "code",
        "outputId": "35dda756-6183-48a8-9cd6-da35d09ee484",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "var_ratio = pca.explained_variance_ratio_\n",
        "var_ratio"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.42072303, 0.23674437, 0.14330238])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "af2e_MPGLp4j",
        "colab_type": "code",
        "outputId": "b16a7fed-e21b-491a-ed86-f2ed6260bcc2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 623
        }
      },
      "source": [
        "sns.set_style('darkgrid')\n",
        "plt.figure(figsize=(10,10))\n",
        "plt.bar(['PC1','PC2','PC3'],var_ratio)\n",
        "plt.xlabel('Componente Principal')\n",
        "plt.ylabel('Percentual de Variância Explicada')"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Percentual de Variância Explicada')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UqFFoOyYmRhMmTLBqJgAAgIgWVqAFg0HZbLb/OygqSocOHbJsKAAAgEgWVqAlJCRo7ty5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\nYQg0AAAAw/wvaLj/pUUYaU8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7jh7rN0kn1Ju",
        "colab_type": "text"
      },
      "source": [
        "Código para Download dos Resultados:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ms2odFXr__MC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pca_values.to_csv('./pca_values_08-19.csv')\n",
        "pca_components.to_csv('./pca_components_08-19.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BSZnpmOrBVxG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from google.colab import files\n",
        "#files.download('pca_values_08-19.csv')\n",
        "#files.download('pca_components_08-19.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tZq7FKiLXp76",
        "colab_type": "text"
      },
      "source": [
        "## Aplicação do PCA Calculado ao dia 19-08-2019"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fo4cnHELvGmu",
        "colab_type": "text"
      },
      "source": [
        "Dataset de 2019, pré-processado e com Group By por Id e Date, com operação de Média:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YIwxAN2smsqx",
        "colab_type": "code",
        "outputId": "88f9413e-b8e2-49f9-9959-449475aec71c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "X = df_2019_pre_gp.groupby(['id','date']).mean()\n",
        "X"
      ],
      "execution_count": 46,
      "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></th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>id</th>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">82024</th>\n",
              "      <th>08-01</th>\n",
              "      <td>6.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>47.8</td>\n",
              "      <td>24.100000</td>\n",
              "      <td>34.4</td>\n",
              "      <td>22.0</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>81.00</td>\n",
              "      <td>91.500000</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>0.51444</td>\n",
              "      <td>0.51444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-02</th>\n",
              "      <td>6.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.550000</td>\n",
              "      <td>33.6</td>\n",
              "      <td>23.7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>86.00</td>\n",
              "      <td>82.000000</td>\n",
              "      <td>2.500000</td>\n",
              "      <td>2.05776</td>\n",
              "      <td>1.02888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-03</th>\n",
              "      <td>9.375000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.2</td>\n",
              "      <td>26.700000</td>\n",
              "      <td>33.6</td>\n",
              "      <td>24.1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>95.00</td>\n",
              "      <td>89.500000</td>\n",
              "      <td>2.500000</td>\n",
              "      <td>0.51444</td>\n",
              "      <td>1.02888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-04</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>30.0</td>\n",
              "      <td>24.600000</td>\n",
              "      <td>33.5</td>\n",
              "      <td>22.7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>86.00</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>1.02888</td>\n",
              "      <td>1.02888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-05</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>23.6</td>\n",
              "      <td>25.733333</td>\n",
              "      <td>29.3</td>\n",
              "      <td>23.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>90.50</td>\n",
              "      <td>89.666667</td>\n",
              "      <td>13.666667</td>\n",
              "      <td>1.37184</td>\n",
              "      <td>0.68592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">83997</th>\n",
              "      <th>08-27</th>\n",
              "      <td>7.666667</td>\n",
              "      <td>0.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1020.966667</td>\n",
              "      <td>1025.466667</td>\n",
              "      <td>1.5</td>\n",
              "      <td>15.166667</td>\n",
              "      <td>19.8</td>\n",
              "      <td>9.9</td>\n",
              "      <td>14.466667</td>\n",
              "      <td>93.75</td>\n",
              "      <td>93.333333</td>\n",
              "      <td>10.666667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-28</th>\n",
              "      <td>8.000000</td>\n",
              "      <td>0.7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1017.666667</td>\n",
              "      <td>1022.133333</td>\n",
              "      <td>0.2</td>\n",
              "      <td>15.333333</td>\n",
              "      <td>21.9</td>\n",
              "      <td>10.6</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>89.25</td>\n",
              "      <td>89.333333</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-29</th>\n",
              "      <td>3.333333</td>\n",
              "      <td>1.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1008.200000</td>\n",
              "      <td>1012.566667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.633333</td>\n",
              "      <td>27.2</td>\n",
              "      <td>14.2</td>\n",
              "      <td>17.900000</td>\n",
              "      <td>81.75</td>\n",
              "      <td>77.333333</td>\n",
              "      <td>22.666667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-30</th>\n",
              "      <td>9.666667</td>\n",
              "      <td>2.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1011.200000</td>\n",
              "      <td>1015.666667</td>\n",
              "      <td>38.7</td>\n",
              "      <td>13.500000</td>\n",
              "      <td>16.5</td>\n",
              "      <td>11.5</td>\n",
              "      <td>12.933333</td>\n",
              "      <td>90.25</td>\n",
              "      <td>93.666667</td>\n",
              "      <td>10.666667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>08-31</th>\n",
              "      <td>6.666667</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1013.266667</td>\n",
              "      <td>1017.733333</td>\n",
              "      <td>24.0</td>\n",
              "      <td>14.066667</td>\n",
              "      <td>17.9</td>\n",
              "      <td>10.6</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>75.00</td>\n",
              "      <td>74.333333</td>\n",
              "      <td>15.333333</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5409 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                    cc  evap    n  ...         wd       ws    wsmax\n",
              "id    date                         ...                             \n",
              "82024 08-01   6.250000   NaN  9.6  ...  11.500000  0.51444  0.51444\n",
              "      08-02   6.250000   NaN  5.1  ...   2.500000  2.05776  1.02888\n",
              "      08-03   9.375000   NaN  NaN  ...   2.500000  0.51444  1.02888\n",
              "      08-04  10.000000   NaN  5.5  ...  18.000000  1.02888  1.02888\n",
              "      08-05  10.000000   NaN  0.0  ...  13.666667  1.37184  0.68592\n",
              "...                ...   ...  ...  ...        ...      ...      ...\n",
              "83997 08-27   7.666667   0.3  NaN  ...  10.666667      NaN      NaN\n",
              "      08-28   8.000000   0.7  NaN  ...  11.000000      NaN      NaN\n",
              "      08-29   3.333333   1.2  NaN  ...  22.666667      NaN      NaN\n",
              "      08-30   9.666667   2.8  NaN  ...  10.666667      NaN      NaN\n",
              "      08-31   6.666667   1.0  NaN  ...  15.333333      NaN      NaN\n",
              "\n",
              "[5409 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KQRhyr8cvsv1",
        "colab_type": "text"
      },
      "source": [
        "Preenchendo Na's com Fills de Dados de uma Mesma Estação, porém com valores de outros dias:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UdlWfsSvy6Va",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "lst_08 = [v for k, v in X.groupby('id')]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p54CI6fc80Zi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = pd.DataFrame()\n",
        "for i, df_i_ in enumerate(lst_08):\n",
        "  df_aux = df_i_.fillna(method='ffill')\n",
        "  df_aux = df_aux.fillna(method='bfill')\n",
        "  df_aux = df_aux.fillna(method='ffill')\n",
        "  X = pd.concat([df_aux,X])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ji_NClT-7HaH",
        "colab_type": "code",
        "outputId": "62927833-5f64-4c96-8141-710e8ea938db",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "print(\"List of\", type(lst_08[0]), \"with length =\", len(lst_08))"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "List of <class 'pandas.core.frame.DataFrame'> with length = 182\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "41zBVq-bNV0y",
        "colab_type": "code",
        "outputId": "1c600e50-9f03-4d0a-dba4-3c3dd1bb2e91",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "X = X.reorder_levels(['date','id']).sort_index()\n",
        "X"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
              "      <th>tmax</th>\n",
              "      <th>tmin</th>\n",
              "      <th>tw</th>\n",
              "      <th>ur</th>\n",
              "      <th>urmax</th>\n",
              "      <th>wd</th>\n",
              "      <th>ws</th>\n",
              "      <th>wsmax</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-01</th>\n",
              "      <th>82024</th>\n",
              "      <td>6.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>47.8</td>\n",
              "      <td>24.100000</td>\n",
              "      <td>34.4</td>\n",
              "      <td>22.0</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>81.00</td>\n",
              "      <td>91.500000</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>3.7</td>\n",
              "      <td>8.9</td>\n",
              "      <td>1009.466667</td>\n",
              "      <td>1011.166667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.066667</td>\n",
              "      <td>33.2</td>\n",
              "      <td>26.6</td>\n",
              "      <td>26.400000</td>\n",
              "      <td>74.50</td>\n",
              "      <td>72.666667</td>\n",
              "      <td>7.666667</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82106</th>\n",
              "      <td>9.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.1</td>\n",
              "      <td>25.550000</td>\n",
              "      <td>30.9</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>93.00</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>4.500000</td>\n",
              "      <td>0.514440</td>\n",
              "      <td>0.514440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.5</td>\n",
              "      <td>1010.533333</td>\n",
              "      <td>1011.833333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.766667</td>\n",
              "      <td>32.0</td>\n",
              "      <td>27.4</td>\n",
              "      <td>26.300000</td>\n",
              "      <td>77.00</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>14.333333</td>\n",
              "      <td>2.733333</td>\n",
              "      <td>2.733333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>4.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.8</td>\n",
              "      <td>1007.500000</td>\n",
              "      <td>1011.766667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.133333</td>\n",
              "      <td>32.6</td>\n",
              "      <td>22.3</td>\n",
              "      <td>25.666667</td>\n",
              "      <td>84.00</td>\n",
              "      <td>82.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>0.533333</td>\n",
              "      <td>0.533333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\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",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">08-31</th>\n",
              "      <th>83964</th>\n",
              "      <td>9.333333</td>\n",
              "      <td>1.6</td>\n",
              "      <td>0.9</td>\n",
              "      <td>965.100000</td>\n",
              "      <td>1014.633333</td>\n",
              "      <td>32.2</td>\n",
              "      <td>13.766667</td>\n",
              "      <td>18.6</td>\n",
              "      <td>10.1</td>\n",
              "      <td>12.966667</td>\n",
              "      <td>88.50</td>\n",
              "      <td>91.333333</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83967</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1008.566667</td>\n",
              "      <td>1014.233333</td>\n",
              "      <td>28.6</td>\n",
              "      <td>16.800000</td>\n",
              "      <td>18.7</td>\n",
              "      <td>14.6</td>\n",
              "      <td>15.700000</td>\n",
              "      <td>89.25</td>\n",
              "      <td>88.666667</td>\n",
              "      <td>22.666667</td>\n",
              "      <td>1.266667</td>\n",
              "      <td>2.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83980</th>\n",
              "      <td>7.000000</td>\n",
              "      <td>0.1</td>\n",
              "      <td>6.9</td>\n",
              "      <td>986.433333</td>\n",
              "      <td>1015.000000</td>\n",
              "      <td>37.3</td>\n",
              "      <td>13.600000</td>\n",
              "      <td>16.8</td>\n",
              "      <td>10.0</td>\n",
              "      <td>12.166667</td>\n",
              "      <td>80.50</td>\n",
              "      <td>84.333333</td>\n",
              "      <td>12.333333</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>4.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83985</th>\n",
              "      <td>9.333333</td>\n",
              "      <td>0.5</td>\n",
              "      <td>4.3</td>\n",
              "      <td>1012.600000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>31.7</td>\n",
              "      <td>15.733333</td>\n",
              "      <td>18.4</td>\n",
              "      <td>12.0</td>\n",
              "      <td>14.400000</td>\n",
              "      <td>89.25</td>\n",
              "      <td>87.000000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>2.266667</td>\n",
              "      <td>3.433333</td>\n",
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              "    <tr>\n",
              "      <th>83997</th>\n",
              "      <td>6.666667</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1013.266667</td>\n",
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              "      <td>24.0</td>\n",
              "      <td>14.066667</td>\n",
              "      <td>17.9</td>\n",
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              "date  id                            ...                               \n",
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              "...                ...   ...   ...  ...        ...       ...       ...\n",
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              "\n",
              "[5409 rows x 15 columns]"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u9b6iv3ZX22K",
        "colab_type": "text"
      },
      "source": [
        "Filtrando para o dia 19:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6pbzWjaVX4t4",
        "colab_type": "code",
        "outputId": "9f22503e-3a64-4803-f25e-470a5be4ee86",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "X = X.loc['08-19']\n",
        "X"
      ],
      "execution_count": 51,
      "outputs": [
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              "             cc  evap     n  ...         wd        ws     wsmax\n",
              "id                           ...                               \n",
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      "source": [
        "Decompondo Wd em coordenadas cartesianas:"
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        "colab": {
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        "X['wd'] = X['wd'].multiply(np.pi/180)\n",
        "X['wd_cos'] = X['wd'].apply(np.cos)\n",
        "X['wd_sin'] = X['wd'].apply(np.sin)\n",
        "X = X.drop('wd',axis=1)\n",
        "X"
      ],
      "execution_count": 52,
      "outputs": [
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              "      <td>0.0</td>\n",
              "      <td>8.466667</td>\n",
              "      <td>16.2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.766667</td>\n",
              "      <td>73.75</td>\n",
              "      <td>66.666667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.970296</td>\n",
              "      <td>0.241922</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83967</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>1.8</td>\n",
              "      <td>5.2</td>\n",
              "      <td>1019.500000</td>\n",
              "      <td>1025.366667</td>\n",
              "      <td>0.1</td>\n",
              "      <td>11.866667</td>\n",
              "      <td>14.4</td>\n",
              "      <td>6.7</td>\n",
              "      <td>9.466667</td>\n",
              "      <td>75.75</td>\n",
              "      <td>71.666667</td>\n",
              "      <td>2.133333</td>\n",
              "      <td>2.033333</td>\n",
              "      <td>0.949243</td>\n",
              "      <td>0.314545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83980</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.9</td>\n",
              "      <td>9.5</td>\n",
              "      <td>996.233333</td>\n",
              "      <td>1025.933333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.666667</td>\n",
              "      <td>10.2</td>\n",
              "      <td>-0.3</td>\n",
              "      <td>4.733333</td>\n",
              "      <td>68.75</td>\n",
              "      <td>73.000000</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>0.970296</td>\n",
              "      <td>0.241922</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83985</th>\n",
              "      <td>5.666667</td>\n",
              "      <td>2.3</td>\n",
              "      <td>7.2</td>\n",
              "      <td>1023.766667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.466667</td>\n",
              "      <td>12.8</td>\n",
              "      <td>4.4</td>\n",
              "      <td>7.766667</td>\n",
              "      <td>81.50</td>\n",
              "      <td>78.000000</td>\n",
              "      <td>3.333333</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>0.920505</td>\n",
              "      <td>0.390731</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83997</th>\n",
              "      <td>3.333333</td>\n",
              "      <td>2.4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1023.733333</td>\n",
              "      <td>1028.133333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.933333</td>\n",
              "      <td>11.7</td>\n",
              "      <td>1.4</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>78.00</td>\n",
              "      <td>72.666667</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.931480</td>\n",
              "      <td>0.363793</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>174 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             cc  evap     n  ...     wsmax    wd_cos    wd_sin\n",
              "id                           ...                              \n",
              "82024  7.083333   NaN   9.4  ...  1.028880  0.986762  0.162178\n",
              "82042  7.333333   NaN   NaN  ...  0.666667  0.999577  0.029085\n",
              "82098  5.333333   2.5   9.9  ...  0.466667  0.951057  0.309017\n",
              "82106  7.500000   NaN   9.0  ...  1.543320  0.992546  0.121869\n",
              "82113  3.750000   NaN  10.1  ...  0.000000  1.000000  0.000000\n",
              "...         ...   ...   ...  ...       ...       ...       ...\n",
              "83964  1.333333   2.3   9.1  ...       NaN  0.970296  0.241922\n",
              "83967  6.333333   1.8   5.2  ...  2.033333  0.949243  0.314545\n",
              "83980  3.000000   2.9   9.5  ...  1.666667  0.970296  0.241922\n",
              "83985  5.666667   2.3   7.2  ...  3.666667  0.920505  0.390731\n",
              "83997  3.333333   2.4   NaN  ...       NaN  0.931480  0.363793\n",
              "\n",
              "[174 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hMAsV5y0YmT-",
        "colab_type": "text"
      },
      "source": [
        "Preenchendo NaN's da coluna Evap com 0's, e em seguida removendo linhas com NaN's ainda remanescentes:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "93O2lxQtYoD-",
        "colab_type": "code",
        "outputId": "094bdd8b-3b2d-40f0-c857-8f80c0ebc0b7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "X['evap'] = X['evap'].fillna(0)\n",
        "X = X.dropna()\n",
        "X"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cc</th>\n",
              "      <th>evap</th>\n",
              "      <th>n</th>\n",
              "      <th>patm</th>\n",
              "      <th>pnmm</th>\n",
              "      <th>prec</th>\n",
              "      <th>tair</th>\n",
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              "      <th>tw</th>\n",
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              "      <th>wsmax</th>\n",
              "      <th>wd_cos</th>\n",
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              "    <tr>\n",
              "      <th>id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>82098</th>\n",
              "      <td>5.333333</td>\n",
              "      <td>2.5</td>\n",
              "      <td>9.9</td>\n",
              "      <td>1010.900000</td>\n",
              "      <td>1012.666667</td>\n",
              "      <td>9.2</td>\n",
              "      <td>29.066667</td>\n",
              "      <td>34.0</td>\n",
              "      <td>23.3</td>\n",
              "      <td>26.233333</td>\n",
              "      <td>78.25</td>\n",
              "      <td>79.666667</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.466667</td>\n",
              "      <td>0.951057</td>\n",
              "      <td>0.309017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82141</th>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.4</td>\n",
              "      <td>9.4</td>\n",
              "      <td>1011.850000</td>\n",
              "      <td>1013.200000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.300000</td>\n",
              "      <td>32.0</td>\n",
              "      <td>23.5</td>\n",
              "      <td>26.700000</td>\n",
              "      <td>87.50</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>1.633333</td>\n",
              "      <td>2.450000</td>\n",
              "      <td>0.945519</td>\n",
              "      <td>0.325568</td>\n",
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              "    <tr>\n",
              "      <th>82145</th>\n",
              "      <td>3.666667</td>\n",
              "      <td>0.7</td>\n",
              "      <td>8.3</td>\n",
              "      <td>1009.000000</td>\n",
              "      <td>1013.233333</td>\n",
              "      <td>2.0</td>\n",
              "      <td>27.866667</td>\n",
              "      <td>32.4</td>\n",
              "      <td>21.3</td>\n",
              "      <td>25.833333</td>\n",
              "      <td>88.25</td>\n",
              "      <td>86.000000</td>\n",
              "      <td>0.733333</td>\n",
              "      <td>0.733333</td>\n",
              "      <td>0.971687</td>\n",
              "      <td>0.236273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82181</th>\n",
              "      <td>3.500000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.5</td>\n",
              "      <td>1001.650000</td>\n",
              "      <td>1014.500000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.350000</td>\n",
              "      <td>33.4</td>\n",
              "      <td>22.2</td>\n",
              "      <td>25.200000</td>\n",
              "      <td>66.50</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>1.700000</td>\n",
              "      <td>1.400000</td>\n",
              "      <td>0.999391</td>\n",
              "      <td>0.034899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82184</th>\n",
              "      <td>4.666667</td>\n",
              "      <td>3.4</td>\n",
              "      <td>10.2</td>\n",
              "      <td>1012.100000</td>\n",
              "      <td>1013.866667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.333333</td>\n",
              "      <td>34.4</td>\n",
              "      <td>25.3</td>\n",
              "      <td>26.233333</td>\n",
              "      <td>71.25</td>\n",
              "      <td>71.333333</td>\n",
              "      <td>0.766667</td>\n",
              "      <td>0.733333</td>\n",
              "      <td>0.976921</td>\n",
              "      <td>0.213599</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82188</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.3</td>\n",
              "      <td>1012.366667</td>\n",
              "      <td>1015.500000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>29.600000</td>\n",
              "      <td>34.4</td>\n",
              "      <td>23.3</td>\n",
              "      <td>25.900000</td>\n",
              "      <td>79.75</td>\n",
              "      <td>79.666667</td>\n",
              "      <td>0.342960</td>\n",
              "      <td>0.342960</td>\n",
              "      <td>0.999577</td>\n",
              "      <td>0.029085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82198</th>\n",
              "      <td>5.666667</td>\n",
              "      <td>4.3</td>\n",
              "      <td>7.3</td>\n",
              "      <td>1009.200000</td>\n",
              "      <td>1014.366667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.933333</td>\n",
              "      <td>33.5</td>\n",
              "      <td>23.9</td>\n",
              "      <td>25.600000</td>\n",
              "      <td>78.75</td>\n",
              "      <td>75.666667</td>\n",
              "      <td>2.633333</td>\n",
              "      <td>2.100000</td>\n",
              "      <td>0.987688</td>\n",
              "      <td>0.156434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82212</th>\n",
              "      <td>2.916667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.5</td>\n",
              "      <td>1004.333333</td>\n",
              "      <td>1012.466667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.600000</td>\n",
              "      <td>34.7</td>\n",
              "      <td>23.0</td>\n",
              "      <td>25.300000</td>\n",
              "      <td>90.75</td>\n",
              "      <td>93.333333</td>\n",
              "      <td>0.685920</td>\n",
              "      <td>0.685920</td>\n",
              "      <td>0.999577</td>\n",
              "      <td>0.029085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82246</th>\n",
              "      <td>7.333333</td>\n",
              "      <td>2.8</td>\n",
              "      <td>8.2</td>\n",
              "      <td>994.100000</td>\n",
              "      <td>1013.966667</td>\n",
              "      <td>10.2</td>\n",
              "      <td>27.833333</td>\n",
              "      <td>33.4</td>\n",
              "      <td>22.0</td>\n",
              "      <td>26.166667</td>\n",
              "      <td>89.75</td>\n",
              "      <td>87.333333</td>\n",
              "      <td>1.100000</td>\n",
              "      <td>0.766667</td>\n",
              "      <td>0.989442</td>\n",
              "      <td>0.144932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82263</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>3.3</td>\n",
              "      <td>9.7</td>\n",
              "      <td>1012.000000</td>\n",
              "      <td>1014.800000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.566667</td>\n",
              "      <td>34.9</td>\n",
              "      <td>24.0</td>\n",
              "      <td>27.566667</td>\n",
              "      <td>81.25</td>\n",
              "      <td>78.666667</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>0.999729</td>\n",
              "      <td>0.023269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82353</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.9</td>\n",
              "      <td>10.4</td>\n",
              "      <td>1001.250000</td>\n",
              "      <td>1009.600000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.850000</td>\n",
              "      <td>35.6</td>\n",
              "      <td>21.3</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>63.25</td>\n",
              "      <td>58.500000</td>\n",
              "      <td>1.766667</td>\n",
              "      <td>2.150000</td>\n",
              "      <td>0.906308</td>\n",
              "      <td>0.422618</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82376</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>4.0</td>\n",
              "      <td>9.3</td>\n",
              "      <td>1007.166667</td>\n",
              "      <td>1012.433333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.133333</td>\n",
              "      <td>34.8</td>\n",
              "      <td>22.0</td>\n",
              "      <td>25.066667</td>\n",
              "      <td>63.75</td>\n",
              "      <td>66.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.987688</td>\n",
              "      <td>0.156434</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82445</th>\n",
              "      <td>3.666667</td>\n",
              "      <td>3.9</td>\n",
              "      <td>9.6</td>\n",
              "      <td>1009.533333</td>\n",
              "      <td>1014.766667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.066667</td>\n",
              "      <td>35.8</td>\n",
              "      <td>23.9</td>\n",
              "      <td>26.366667</td>\n",
              "      <td>77.75</td>\n",
              "      <td>74.666667</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.996685</td>\n",
              "      <td>0.081359</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82768</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>5.2</td>\n",
              "      <td>9.5</td>\n",
              "      <td>983.100000</td>\n",
              "      <td>1012.200000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>30.133333</td>\n",
              "      <td>37.8</td>\n",
              "      <td>16.7</td>\n",
              "      <td>24.766667</td>\n",
              "      <td>66.25</td>\n",
              "      <td>64.333333</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.993897</td>\n",
              "      <td>0.110313</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82861</th>\n",
              "      <td>2.000000</td>\n",
              "      <td>6.4</td>\n",
              "      <td>10.5</td>\n",
              "      <td>993.050000</td>\n",
              "      <td>1011.100000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.600000</td>\n",
              "      <td>39.7</td>\n",
              "      <td>22.1</td>\n",
              "      <td>23.800000</td>\n",
              "      <td>53.50</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.965926</td>\n",
              "      <td>0.258819</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82915</th>\n",
              "      <td>5.416667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>995.766667</td>\n",
              "      <td>1013.900000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>28.400000</td>\n",
              "      <td>34.9</td>\n",
              "      <td>21.6</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>74.00</td>\n",
              "      <td>72.666667</td>\n",
              "      <td>2.057760</td>\n",
              "      <td>1.714800</td>\n",
              "      <td>0.991061</td>\n",
              "      <td>0.133410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83386</th>\n",
              "      <td>3.333333</td>\n",
              "      <td>6.9</td>\n",
              "      <td>10.7</td>\n",
              "      <td>961.233333</td>\n",
              "      <td>1013.366667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27.800000</td>\n",
              "      <td>34.6</td>\n",
              "      <td>13.9</td>\n",
              "      <td>18.333333</td>\n",
              "      <td>40.75</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>2.133333</td>\n",
              "      <td>2.100000</td>\n",
              "      <td>0.965926</td>\n",
              "      <td>0.258819</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83437</th>\n",
              "      <td>2.666667</td>\n",
              "      <td>6.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>943.600000</td>\n",
              "      <td>1014.500000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>25.600000</td>\n",
              "      <td>32.3</td>\n",
              "      <td>14.8</td>\n",
              "      <td>17.666667</td>\n",
              "      <td>44.50</td>\n",
              "      <td>45.333333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.949243</td>\n",
              "      <td>0.314545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83441</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>5.2</td>\n",
              "      <td>9.9</td>\n",
              "      <td>962.700000</td>\n",
              "      <td>1015.500000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>26.900000</td>\n",
              "      <td>33.3</td>\n",
              "      <td>15.4</td>\n",
              "      <td>21.566667</td>\n",
              "      <td>65.50</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>1.833333</td>\n",
              "      <td>1.833333</td>\n",
              "      <td>0.951057</td>\n",
              "      <td>0.309017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83587</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>5.9</td>\n",
              "      <td>7.8</td>\n",
              "      <td>914.166667</td>\n",
              "      <td>1014.266667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.866667</td>\n",
              "      <td>30.7</td>\n",
              "      <td>16.4</td>\n",
              "      <td>16.066667</td>\n",
              "      <td>40.50</td>\n",
              "      <td>44.333333</td>\n",
              "      <td>1.300000</td>\n",
              "      <td>0.866667</td>\n",
              "      <td>0.971687</td>\n",
              "      <td>0.236273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83592</th>\n",
              "      <td>6.666667</td>\n",
              "      <td>4.2</td>\n",
              "      <td>8.5</td>\n",
              "      <td>947.466667</td>\n",
              "      <td>1016.100000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.200000</td>\n",
              "      <td>31.8</td>\n",
              "      <td>11.4</td>\n",
              "      <td>18.066667</td>\n",
              "      <td>66.00</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.951057</td>\n",
              "      <td>0.309017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83648</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.6</td>\n",
              "      <td>8.2</td>\n",
              "      <td>1012.800000</td>\n",
              "      <td>1017.100000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>24.266667</td>\n",
              "      <td>30.7</td>\n",
              "      <td>20.2</td>\n",
              "      <td>20.600000</td>\n",
              "      <td>75.75</td>\n",
              "      <td>69.666667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.866025</td>\n",
              "      <td>0.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83669</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>6.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>945.166667</td>\n",
              "      <td>1014.266667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.900000</td>\n",
              "      <td>31.1</td>\n",
              "      <td>12.9</td>\n",
              "      <td>17.500000</td>\n",
              "      <td>58.25</td>\n",
              "      <td>52.666667</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83683</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>3.8</td>\n",
              "      <td>4.4</td>\n",
              "      <td>918.500000</td>\n",
              "      <td>1015.500000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.633333</td>\n",
              "      <td>27.7</td>\n",
              "      <td>11.3</td>\n",
              "      <td>16.533333</td>\n",
              "      <td>66.00</td>\n",
              "      <td>66.333333</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.981627</td>\n",
              "      <td>0.190809</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83687</th>\n",
              "      <td>7.666667</td>\n",
              "      <td>4.8</td>\n",
              "      <td>6.7</td>\n",
              "      <td>913.600000</td>\n",
              "      <td>1013.466667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>22.600000</td>\n",
              "      <td>29.9</td>\n",
              "      <td>12.6</td>\n",
              "      <td>15.800000</td>\n",
              "      <td>56.75</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>0.982721</td>\n",
              "      <td>0.185095</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83692</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.9</td>\n",
              "      <td>912.033333</td>\n",
              "      <td>1015.300000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>20.933333</td>\n",
              "      <td>25.6</td>\n",
              "      <td>15.2</td>\n",
              "      <td>16.700000</td>\n",
              "      <td>78.75</td>\n",
              "      <td>64.666667</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>0.913545</td>\n",
              "      <td>0.406737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83736</th>\n",
              "      <td>5.666667</td>\n",
              "      <td>3.9</td>\n",
              "      <td>6.4</td>\n",
              "      <td>912.466667</td>\n",
              "      <td>1019.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19.200000</td>\n",
              "      <td>27.6</td>\n",
              "      <td>10.2</td>\n",
              "      <td>15.333333</td>\n",
              "      <td>72.50</td>\n",
              "      <td>68.333333</td>\n",
              "      <td>1.200000</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>0.999577</td>\n",
              "      <td>0.029085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83766</th>\n",
              "      <td>6.666667</td>\n",
              "      <td>5.3</td>\n",
              "      <td>4.8</td>\n",
              "      <td>949.933333</td>\n",
              "      <td>1014.433333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.800000</td>\n",
              "      <td>25.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>17.466667</td>\n",
              "      <td>73.25</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.994522</td>\n",
              "      <td>0.104528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83767</th>\n",
              "      <td>7.666667</td>\n",
              "      <td>5.1</td>\n",
              "      <td>5.5</td>\n",
              "      <td>951.633333</td>\n",
              "      <td>1013.133333</td>\n",
              "      <td>0.1</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>27.7</td>\n",
              "      <td>18.8</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>68.50</td>\n",
              "      <td>62.333333</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.971687</td>\n",
              "      <td>0.236273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83781</th>\n",
              "      <td>9.000000</td>\n",
              "      <td>5.6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>928.500000</td>\n",
              "      <td>1017.400000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>21.0</td>\n",
              "      <td>14.9</td>\n",
              "      <td>15.666667</td>\n",
              "      <td>87.75</td>\n",
              "      <td>77.666667</td>\n",
              "      <td>3.866667</td>\n",
              "      <td>3.866667</td>\n",
              "      <td>0.951057</td>\n",
              "      <td>0.309017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83836</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>917.866667</td>\n",
              "      <td>1015.166667</td>\n",
              "      <td>27.8</td>\n",
              "      <td>14.533333</td>\n",
              "      <td>19.0</td>\n",
              "      <td>8.8</td>\n",
              "      <td>13.266667</td>\n",
              "      <td>96.25</td>\n",
              "      <td>88.000000</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>1.300000</td>\n",
              "      <td>0.986762</td>\n",
              "      <td>0.162178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83842</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>915.000000</td>\n",
              "      <td>1018.566667</td>\n",
              "      <td>14.5</td>\n",
              "      <td>11.800000</td>\n",
              "      <td>17.6</td>\n",
              "      <td>8.6</td>\n",
              "      <td>11.233333</td>\n",
              "      <td>96.25</td>\n",
              "      <td>93.666667</td>\n",
              "      <td>1.733333</td>\n",
              "      <td>2.200000</td>\n",
              "      <td>0.990268</td>\n",
              "      <td>0.139173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83907</th>\n",
              "      <td>0.666667</td>\n",
              "      <td>2.4</td>\n",
              "      <td>9.6</td>\n",
              "      <td>993.633333</td>\n",
              "      <td>1023.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.100000</td>\n",
              "      <td>17.2</td>\n",
              "      <td>5.7</td>\n",
              "      <td>9.700000</td>\n",
              "      <td>67.75</td>\n",
              "      <td>64.000000</td>\n",
              "      <td>4.133333</td>\n",
              "      <td>4.133333</td>\n",
              "      <td>0.976921</td>\n",
              "      <td>0.213599</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83914</th>\n",
              "      <td>4.666667</td>\n",
              "      <td>2.5</td>\n",
              "      <td>9.2</td>\n",
              "      <td>942.533333</td>\n",
              "      <td>1022.633333</td>\n",
              "      <td>0.2</td>\n",
              "      <td>10.700000</td>\n",
              "      <td>16.3</td>\n",
              "      <td>4.6</td>\n",
              "      <td>7.466667</td>\n",
              "      <td>65.25</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>4.866667</td>\n",
              "      <td>4.033333</td>\n",
              "      <td>0.976921</td>\n",
              "      <td>0.213599</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83919</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>8.2</td>\n",
              "      <td>901.966667</td>\n",
              "      <td>1022.433333</td>\n",
              "      <td>0.2</td>\n",
              "      <td>7.933333</td>\n",
              "      <td>14.8</td>\n",
              "      <td>1.6</td>\n",
              "      <td>5.400000</td>\n",
              "      <td>77.25</td>\n",
              "      <td>74.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.851117</td>\n",
              "      <td>0.524977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83936</th>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.7</td>\n",
              "      <td>9.4</td>\n",
              "      <td>1012.933333</td>\n",
              "      <td>1025.700000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.866667</td>\n",
              "      <td>13.6</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.400000</td>\n",
              "      <td>81.00</td>\n",
              "      <td>70.666667</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>2.666667</td>\n",
              "      <td>0.957990</td>\n",
              "      <td>0.286803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83942</th>\n",
              "      <td>7.333333</td>\n",
              "      <td>0.6</td>\n",
              "      <td>8.2</td>\n",
              "      <td>931.366667</td>\n",
              "      <td>1020.000000</td>\n",
              "      <td>0.4</td>\n",
              "      <td>7.733333</td>\n",
              "      <td>11.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>5.933333</td>\n",
              "      <td>79.00</td>\n",
              "      <td>77.333333</td>\n",
              "      <td>4.333333</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>0.951057</td>\n",
              "      <td>0.309017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83948</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>2.6</td>\n",
              "      <td>9.3</td>\n",
              "      <td>1023.333333</td>\n",
              "      <td>1024.033333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.566667</td>\n",
              "      <td>17.1</td>\n",
              "      <td>8.1</td>\n",
              "      <td>10.633333</td>\n",
              "      <td>72.25</td>\n",
              "      <td>67.666667</td>\n",
              "      <td>3.333333</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>0.933580</td>\n",
              "      <td>0.358368</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83967</th>\n",
              "      <td>6.333333</td>\n",
              "      <td>1.8</td>\n",
              "      <td>5.2</td>\n",
              "      <td>1019.500000</td>\n",
              "      <td>1025.366667</td>\n",
              "      <td>0.1</td>\n",
              "      <td>11.866667</td>\n",
              "      <td>14.4</td>\n",
              "      <td>6.7</td>\n",
              "      <td>9.466667</td>\n",
              "      <td>75.75</td>\n",
              "      <td>71.666667</td>\n",
              "      <td>2.133333</td>\n",
              "      <td>2.033333</td>\n",
              "      <td>0.949243</td>\n",
              "      <td>0.314545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83980</th>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.9</td>\n",
              "      <td>9.5</td>\n",
              "      <td>996.233333</td>\n",
              "      <td>1025.933333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6.666667</td>\n",
              "      <td>10.2</td>\n",
              "      <td>-0.3</td>\n",
              "      <td>4.733333</td>\n",
              "      <td>68.75</td>\n",
              "      <td>73.000000</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>1.666667</td>\n",
              "      <td>0.970296</td>\n",
              "      <td>0.241922</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              cc  evap     n  ...     wsmax    wd_cos    wd_sin\n",
              "id                            ...                              \n",
              "82098   5.333333   2.5   9.9  ...  0.466667  0.951057  0.309017\n",
              "82141   6.000000   0.4   9.4  ...  2.450000  0.945519  0.325568\n",
              "82145   3.666667   0.7   8.3  ...  0.733333  0.971687  0.236273\n",
              "82181   3.500000  10.0  10.5  ...  1.400000  0.999391  0.034899\n",
              "82184   4.666667   3.4  10.2  ...  0.733333  0.976921  0.213599\n",
              "82188   5.000000   0.0  10.3  ...  0.342960  0.999577  0.029085\n",
              "82198   5.666667   4.3   7.3  ...  2.100000  0.987688  0.156434\n",
              "82212   2.916667   0.0   9.5  ...  0.685920  0.999577  0.029085\n",
              "82246   7.333333   2.8   8.2  ...  0.766667  0.989442  0.144932\n",
              "82263   4.000000   3.3   9.7  ...  1.666667  0.999729  0.023269\n",
              "82353   3.000000   2.9  10.4  ...  2.150000  0.906308  0.422618\n",
              "82376   3.000000   4.0   9.3  ...  0.000000  0.987688  0.156434\n",
              "82445   3.666667   3.9   9.6  ...  0.666667  0.996685  0.081359\n",
              "82768   3.000000   5.2   9.5  ...  0.666667  0.993897  0.110313\n",
              "82861   2.000000   6.4  10.5  ...  3.000000  0.965926  0.258819\n",
              "82915   5.416667   0.0   4.0  ...  1.714800  0.991061  0.133410\n",
              "83386   3.333333   6.9  10.7  ...  2.100000  0.965926  0.258819\n",
              "83437   2.666667   6.0  10.0  ...  0.000000  0.949243  0.314545\n",
              "83441   4.000000   5.2   9.9  ...  1.833333  0.951057  0.309017\n",
              "83587   3.000000   5.9   7.8  ...  0.866667  0.971687  0.236273\n",
              "83592   6.666667   4.2   8.5  ...  0.666667  0.951057  0.309017\n",
              "83648   1.000000   3.6   8.2  ...  0.000000  0.866025  0.500000\n",
              "83669   6.333333   6.8   0.0  ...  0.000000  1.000000  0.000000\n",
              "83683   5.000000   3.8   4.4  ...  1.000000  0.981627  0.190809\n",
              "83687   7.666667   4.8   6.7  ...  1.666667  0.982721  0.185095\n",
              "83692   1.000000   7.0   6.9  ...  3.666667  0.913545  0.406737\n",
              "83736   5.666667   3.9   6.4  ...  0.166667  0.999577  0.029085\n",
              "83766   6.666667   5.3   4.8  ...  0.666667  0.994522  0.104528\n",
              "83767   7.666667   5.1   5.5  ...  1.000000  0.971687  0.236273\n",
              "83781   9.000000   5.6   0.0  ...  3.866667  0.951057  0.309017\n",
              "83836  10.000000   3.5   0.0  ...  1.300000  0.986762  0.162178\n",
              "83842  10.000000   4.0   0.0  ...  2.200000  0.990268  0.139173\n",
              "83907   0.666667   2.4   9.6  ...  4.133333  0.976921  0.213599\n",
              "83914   4.666667   2.5   9.2  ...  4.033333  0.976921  0.213599\n",
              "83919   4.000000   1.0   8.2  ...  0.933333  0.851117  0.524977\n",
              "83936   2.000000   3.7   9.4  ...  2.666667  0.957990  0.286803\n",
              "83942   7.333333   0.6   8.2  ...  3.666667  0.951057  0.309017\n",
              "83948   4.000000   2.6   9.3  ...  3.666667  0.933580  0.358368\n",
              "83967   6.333333   1.8   5.2  ...  2.033333  0.949243  0.314545\n",
              "83980   3.000000   2.9   9.5  ...  1.666667  0.970296  0.241922\n",
              "\n",
              "[40 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "siMHRaMdM3rD",
        "colab_type": "text"
      },
      "source": [
        "Aplicando o Dataset resultante ao PCA calculado anteriormente:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2c67GEZpUAlt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pc1_2019 = sc.fit_transform(X.values)\n",
        "pc1_2019 = pca.transform(pc1_2019)\n",
        "pc1_2019 = pd.DataFrame(pc1_2019,index=X.index)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q_tdSiT_M60d",
        "colab_type": "text"
      },
      "source": [
        "Adicionando Latitudes e Longitudes:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qimKRRYiUTYF",
        "colab_type": "code",
        "outputId": "48522c17-e3a7-44ce-c6f0-64e26f23f636",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        }
      },
      "source": [
        "pc1_2019 = pc1_2019.merge(df_m,on='id')\n",
        "pc1_2019 = pc1_2019.drop(['alt','name','state','uf','time_zone','offset_utc','time_zone.1','offset_utc.1'],axis=1)\n",
        "pc1_2019"
      ],
      "execution_count": 55,
      "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",
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              "    }\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>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>lon</th>\n",
              "      <th>lat</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>82098</td>\n",
              "      <td>-0.519376</td>\n",
              "      <td>2.422612</td>\n",
              "      <td>0.173939</td>\n",
              "      <td>-51.116667</td>\n",
              "      <td>-0.050000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>82141</td>\n",
              "      <td>-0.218598</td>\n",
              "      <td>2.164525</td>\n",
              "      <td>1.385208</td>\n",
              "      <td>-48.516667</td>\n",
              "      <td>-0.733333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>82145</td>\n",
              "      <td>-0.295781</td>\n",
              "      <td>2.678700</td>\n",
              "      <td>-0.466718</td>\n",
              "      <td>-46.900000</td>\n",
              "      <td>-1.066667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>82181</td>\n",
              "      <td>-3.238190</td>\n",
              "      <td>0.427667</td>\n",
              "      <td>0.293742</td>\n",
              "      <td>-54.083333</td>\n",
              "      <td>-2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>82184</td>\n",
              "      <td>-1.847400</td>\n",
              "      <td>1.761225</td>\n",
              "      <td>-0.159280</td>\n",
              "      <td>-52.233333</td>\n",
              "      <td>-1.733333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>82188</td>\n",
              "      <td>-1.240919</td>\n",
              "      <td>2.941913</td>\n",
              "      <td>-1.296755</td>\n",
              "      <td>-50.483333</td>\n",
              "      <td>-1.683333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>82198</td>\n",
              "      <td>-1.102110</td>\n",
              "      <td>1.825536</td>\n",
              "      <td>1.196013</td>\n",
              "      <td>-45.366667</td>\n",
              "      <td>-1.566667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>82212</td>\n",
              "      <td>-1.014055</td>\n",
              "      <td>3.357782</td>\n",
              "      <td>-1.093666</td>\n",
              "      <td>-66.166667</td>\n",
              "      <td>-2.533333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>82246</td>\n",
              "      <td>0.098334</td>\n",
              "      <td>3.290029</td>\n",
              "      <td>-0.221170</td>\n",
              "      <td>-54.950000</td>\n",
              "      <td>-2.633333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>82263</td>\n",
              "      <td>-1.828581</td>\n",
              "      <td>2.429153</td>\n",
              "      <td>0.199840</td>\n",
              "      <td>-49.500000</td>\n",
              "      <td>-2.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>82353</td>\n",
              "      <td>-1.852284</td>\n",
              "      <td>0.075396</td>\n",
              "      <td>1.561296</td>\n",
              "      <td>-52.216667</td>\n",
              "      <td>-3.216667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>82376</td>\n",
              "      <td>-2.472564</td>\n",
              "      <td>1.307345</td>\n",
              "      <td>-1.343165</td>\n",
              "      <td>-45.650000</td>\n",
              "      <td>-3.266667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>82445</td>\n",
              "      <td>-2.043091</td>\n",
              "      <td>2.121556</td>\n",
              "      <td>-0.696801</td>\n",
              "      <td>-56.000000</td>\n",
              "      <td>-4.283333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>82768</td>\n",
              "      <td>-2.611392</td>\n",
              "      <td>0.712613</td>\n",
              "      <td>-1.020595</td>\n",
              "      <td>-46.033333</td>\n",
              "      <td>-7.533333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>82861</td>\n",
              "      <td>-3.483108</td>\n",
              "      <td>-0.647824</td>\n",
              "      <td>1.658587</td>\n",
              "      <td>-49.266667</td>\n",
              "      <td>-8.266667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>82915</td>\n",
              "      <td>-0.326946</td>\n",
              "      <td>2.001387</td>\n",
              "      <td>0.035976</td>\n",
              "      <td>-67.800000</td>\n",
              "      <td>-9.966667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>83386</td>\n",
              "      <td>-2.819222</td>\n",
              "      <td>-2.373905</td>\n",
              "      <td>0.562433</td>\n",
              "      <td>-44.366667</td>\n",
              "      <td>-15.450000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>83437</td>\n",
              "      <td>-2.184526</td>\n",
              "      <td>-2.081404</td>\n",
              "      <td>-1.495089</td>\n",
              "      <td>-43.833333</td>\n",
              "      <td>-16.683333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>83441</td>\n",
              "      <td>-1.194511</td>\n",
              "      <td>-0.732739</td>\n",
              "      <td>0.601373</td>\n",
              "      <td>-42.300000</td>\n",
              "      <td>-16.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>83587</td>\n",
              "      <td>-1.993900</td>\n",
              "      <td>-2.402735</td>\n",
              "      <td>-0.942000</td>\n",
              "      <td>-43.933333</td>\n",
              "      <td>-19.933333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>83592</td>\n",
              "      <td>-0.095353</td>\n",
              "      <td>-0.784767</td>\n",
              "      <td>-0.690168</td>\n",
              "      <td>-42.150000</td>\n",
              "      <td>-19.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>83648</td>\n",
              "      <td>-0.030669</td>\n",
              "      <td>-0.140089</td>\n",
              "      <td>-0.215278</td>\n",
              "      <td>-40.316667</td>\n",
              "      <td>-20.316667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>83669</td>\n",
              "      <td>-0.913872</td>\n",
              "      <td>-0.304125</td>\n",
              "      <td>-2.426518</td>\n",
              "      <td>-47.550000</td>\n",
              "      <td>-21.483333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>83683</td>\n",
              "      <td>0.269285</td>\n",
              "      <td>-0.745846</td>\n",
              "      <td>-1.392475</td>\n",
              "      <td>-45.900000</td>\n",
              "      <td>-21.650000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>83687</td>\n",
              "      <td>-0.549237</td>\n",
              "      <td>-1.551880</td>\n",
              "      <td>0.138588</td>\n",
              "      <td>-45.000000</td>\n",
              "      <td>-21.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>83692</td>\n",
              "      <td>0.184212</td>\n",
              "      <td>-2.395146</td>\n",
              "      <td>2.485633</td>\n",
              "      <td>-43.350000</td>\n",
              "      <td>-21.766667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>83736</td>\n",
              "      <td>0.318225</td>\n",
              "      <td>-0.503424</td>\n",
              "      <td>-2.118992</td>\n",
              "      <td>-45.016667</td>\n",
              "      <td>-22.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>83766</td>\n",
              "      <td>-0.073753</td>\n",
              "      <td>0.113201</td>\n",
              "      <td>-1.313508</td>\n",
              "      <td>-51.133333</td>\n",
              "      <td>-23.316667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>83767</td>\n",
              "      <td>-0.249546</td>\n",
              "      <td>0.008116</td>\n",
              "      <td>-0.179470</td>\n",
              "      <td>-51.916667</td>\n",
              "      <td>-23.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>83781</td>\n",
              "      <td>2.709437</td>\n",
              "      <td>-0.441691</td>\n",
              "      <td>2.203457</td>\n",
              "      <td>-46.616667</td>\n",
              "      <td>-23.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>83836</td>\n",
              "      <td>4.534872</td>\n",
              "      <td>1.969249</td>\n",
              "      <td>-0.482396</td>\n",
              "      <td>-50.633333</td>\n",
              "      <td>-25.466667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>83842</td>\n",
              "      <td>4.449002</td>\n",
              "      <td>1.089476</td>\n",
              "      <td>-0.554393</td>\n",
              "      <td>-49.266667</td>\n",
              "      <td>-25.433333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>83907</td>\n",
              "      <td>1.228609</td>\n",
              "      <td>-2.358303</td>\n",
              "      <td>1.585883</td>\n",
              "      <td>-55.016667</td>\n",
              "      <td>-28.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>83914</td>\n",
              "      <td>2.090039</td>\n",
              "      <td>-2.828059</td>\n",
              "      <td>1.724681</td>\n",
              "      <td>-52.400000</td>\n",
              "      <td>-28.216667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>83919</td>\n",
              "      <td>4.114083</td>\n",
              "      <td>-3.290030</td>\n",
              "      <td>-0.776965</td>\n",
              "      <td>-50.433333</td>\n",
              "      <td>-28.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>83936</td>\n",
              "      <td>2.167099</td>\n",
              "      <td>-1.769951</td>\n",
              "      <td>0.057276</td>\n",
              "      <td>-53.700000</td>\n",
              "      <td>-29.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>83942</td>\n",
              "      <td>3.848169</td>\n",
              "      <td>-2.078153</td>\n",
              "      <td>1.533351</td>\n",
              "      <td>-51.200000</td>\n",
              "      <td>-29.166667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>83948</td>\n",
              "      <td>2.161612</td>\n",
              "      <td>-1.773566</td>\n",
              "      <td>1.941937</td>\n",
              "      <td>-49.716667</td>\n",
              "      <td>-29.350000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>83967</td>\n",
              "      <td>3.268926</td>\n",
              "      <td>-0.972015</td>\n",
              "      <td>0.184506</td>\n",
              "      <td>-51.166667</td>\n",
              "      <td>-30.050000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>83980</td>\n",
              "      <td>2.757075</td>\n",
              "      <td>-2.521830</td>\n",
              "      <td>-0.638316</td>\n",
              "      <td>-54.100000</td>\n",
              "      <td>-31.333333</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       id         0         1         2        lon        lat\n",
              "0   82098 -0.519376  2.422612  0.173939 -51.116667  -0.050000\n",
              "1   82141 -0.218598  2.164525  1.385208 -48.516667  -0.733333\n",
              "2   82145 -0.295781  2.678700 -0.466718 -46.900000  -1.066667\n",
              "3   82181 -3.238190  0.427667  0.293742 -54.083333  -2.000000\n",
              "4   82184 -1.847400  1.761225 -0.159280 -52.233333  -1.733333\n",
              "5   82188 -1.240919  2.941913 -1.296755 -50.483333  -1.683333\n",
              "6   82198 -1.102110  1.825536  1.196013 -45.366667  -1.566667\n",
              "7   82212 -1.014055  3.357782 -1.093666 -66.166667  -2.533333\n",
              "8   82246  0.098334  3.290029 -0.221170 -54.950000  -2.633333\n",
              "9   82263 -1.828581  2.429153  0.199840 -49.500000  -2.250000\n",
              "10  82353 -1.852284  0.075396  1.561296 -52.216667  -3.216667\n",
              "11  82376 -2.472564  1.307345 -1.343165 -45.650000  -3.266667\n",
              "12  82445 -2.043091  2.121556 -0.696801 -56.000000  -4.283333\n",
              "13  82768 -2.611392  0.712613 -1.020595 -46.033333  -7.533333\n",
              "14  82861 -3.483108 -0.647824  1.658587 -49.266667  -8.266667\n",
              "15  82915 -0.326946  2.001387  0.035976 -67.800000  -9.966667\n",
              "16  83386 -2.819222 -2.373905  0.562433 -44.366667 -15.450000\n",
              "17  83437 -2.184526 -2.081404 -1.495089 -43.833333 -16.683333\n",
              "18  83441 -1.194511 -0.732739  0.601373 -42.300000 -16.166667\n",
              "19  83587 -1.993900 -2.402735 -0.942000 -43.933333 -19.933333\n",
              "20  83592 -0.095353 -0.784767 -0.690168 -42.150000 -19.800000\n",
              "21  83648 -0.030669 -0.140089 -0.215278 -40.316667 -20.316667\n",
              "22  83669 -0.913872 -0.304125 -2.426518 -47.550000 -21.483333\n",
              "23  83683  0.269285 -0.745846 -1.392475 -45.900000 -21.650000\n",
              "24  83687 -0.549237 -1.551880  0.138588 -45.000000 -21.750000\n",
              "25  83692  0.184212 -2.395146  2.485633 -43.350000 -21.766667\n",
              "26  83736  0.318225 -0.503424 -2.118992 -45.016667 -22.100000\n",
              "27  83766 -0.073753  0.113201 -1.313508 -51.133333 -23.316667\n",
              "28  83767 -0.249546  0.008116 -0.179470 -51.916667 -23.400000\n",
              "29  83781  2.709437 -0.441691  2.203457 -46.616667 -23.500000\n",
              "30  83836  4.534872  1.969249 -0.482396 -50.633333 -25.466667\n",
              "31  83842  4.449002  1.089476 -0.554393 -49.266667 -25.433333\n",
              "32  83907  1.228609 -2.358303  1.585883 -55.016667 -28.400000\n",
              "33  83914  2.090039 -2.828059  1.724681 -52.400000 -28.216667\n",
              "34  83919  4.114083 -3.290030 -0.776965 -50.433333 -28.666667\n",
              "35  83936  2.167099 -1.769951  0.057276 -53.700000 -29.700000\n",
              "36  83942  3.848169 -2.078153  1.533351 -51.200000 -29.166667\n",
              "37  83948  2.161612 -1.773566  1.941937 -49.716667 -29.350000\n",
              "38  83967  3.268926 -0.972015  0.184506 -51.166667 -30.050000\n",
              "39  83980  2.757075 -2.521830 -0.638316 -54.100000 -31.333333"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9DEC2Ob0wSZf",
        "colab_type": "text"
      },
      "source": [
        "Código para Download dos Resultados:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bTMKg0mpG5WX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pc1_2019.to_csv('./pc1_2019.csv')\n",
        "from google.colab import files\n",
        "#files.download('pc1_2019.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bBg4WPT5ZGwr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}