LightGMB.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Kaiizx3014/Hackathon2_IOT/blob/main/LightGMB.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Import Lib"
      ],
      "metadata": {
        "id": "bXaFx2Y7cxRH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kmk3hh32c28c",
        "outputId": "cab0328b-11c3-4c5e-eafc-212864488156"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip /content/drive/MyDrive/IOT.zip"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7Stut866c_0B",
        "outputId": "48bf3e42-3cf1-4831-8a73-ba8386412f69"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  /content/drive/MyDrive/IOT.zip\n",
            "replace IOT/IOT_Submit.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: N\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install --pre pycaret"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9EmVNVoSd3DA",
        "outputId": "7f7b9ca3-03de-4742-d3e8-d20c26197d57"
      },
      "execution_count": 85,
      "outputs": [
        {
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          "name": "stdout",
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            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "import seaborn as sns # visualization library\n",
        "import matplotlib.pyplot as plt # visualization library\n",
        "import plotly.express as px\n",
        "# import the regression module**\n",
        "from pycaret.regression import *\n",
        "\n",
        "\n",
        "\n",
        "import os"
      ],
      "metadata": {
        "id": "CiQQiN8Ddkj8"
      },
      "execution_count": 86,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Cleansing Data"
      ],
      "metadata": {
        "id": "qdrg1OYAZGKD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cwd = os.getcwd()\n",
        "data = pd.read_csv(cwd+'/IOT/IOT_Train.csv')\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 748
        },
        "id": "Aqwhdrc1iflA",
        "outputId": "04815da4-f727-48e8-c6fa-377e3f4f7a47"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                mac                   station_name  tambon_code   tambon_namt  \\\n",
              "0      3C71BF18EA64                       บ้านนา_2       300903         กำปัง   \n",
              "1      3C71BF18EA64                       บ้านนา_2       300903         กำปัง   \n",
              "2      3C71BF18EA64                       บ้านนา_2       300903         กำปัง   \n",
              "3      3C71BF18EA64                       บ้านนา_2       300903         กำปัง   \n",
              "4      3C71BF18EA64                       บ้านนา_2       300903         กำปัง   \n",
              "...             ...                            ...          ...           ...   \n",
              "13630  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706  หนองสูงเหนือ   \n",
              "13631  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706  หนองสูงเหนือ   \n",
              "13632  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706  หนองสูงเหนือ   \n",
              "13633  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706  หนองสูงเหนือ   \n",
              "13634  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706  หนองสูงเหนือ   \n",
              "\n",
              "       amphur_code amphur_namt  province_code province_namt   latitude  \\\n",
              "0             3009      โนนไทย             30    นครราชสีมา  15.112831   \n",
              "1             3009      โนนไทย             30    นครราชสีมา  15.112831   \n",
              "2             3009      โนนไทย             30    นครราชสีมา  15.112831   \n",
              "3             3009      โนนไทย             30    นครราชสีมา  15.112831   \n",
              "4             3009      โนนไทย             30    นครราชสีมา  15.112831   \n",
              "...            ...         ...            ...           ...        ...   \n",
              "13630         4907     หนองสูง             49      มุกดาหาร  16.494229   \n",
              "13631         4907     หนองสูง             49      มุกดาหาร  16.494229   \n",
              "13632         4907     หนองสูง             49      มุกดาหาร  16.494229   \n",
              "13633         4907     หนองสูง             49      มุกดาหาร  16.494229   \n",
              "13634         4907     หนองสูง             49      มุกดาหาร  16.494229   \n",
              "\n",
              "        longitude                       time  humid  light  pm10  pm2.5  \\\n",
              "0      102.052114  2022-07-20 15:00:00+07:00   70.6   59.0   NaN    NaN   \n",
              "1      102.052114  2022-05-16 09:00:00+07:00   62.3   76.0   NaN    NaN   \n",
              "2      102.052114  2022-06-26 19:00:00+07:00   90.3    0.0   NaN    NaN   \n",
              "3      102.052114  2022-07-16 04:00:00+07:00   91.7    0.0   NaN    NaN   \n",
              "4      102.052114  2022-05-30 08:00:00+07:00   59.1   71.0   NaN    NaN   \n",
              "...           ...                        ...    ...    ...   ...    ...   \n",
              "13630  104.350891  2022-06-14 01:00:00+07:00   97.9    0.0   NaN    NaN   \n",
              "13631  104.350891  2022-05-03 02:00:00+07:00   80.6    0.0   NaN    NaN   \n",
              "13632  104.350891  2022-05-19 06:00:00+07:00   87.9   37.0   NaN    NaN   \n",
              "13633  104.350891  2022-06-15 02:00:00+07:00   89.9    0.0   NaN    NaN   \n",
              "13634  104.350891  2022-06-05 18:00:00+07:00   66.3   43.0   NaN    NaN   \n",
              "\n",
              "       rainfall  wind_direct  wind_speed  temp  \n",
              "0           0.0         45.0         4.3  32.6  \n",
              "1           0.0         45.0         1.9  37.9  \n",
              "2           0.0        135.0         3.2  26.4  \n",
              "3           0.0        157.5         0.0  25.6  \n",
              "4           0.0        180.0         2.3  36.2  \n",
              "...         ...          ...         ...   ...  \n",
              "13630       4.2          0.0         0.0  23.5  \n",
              "13631       0.0        135.0         2.9  19.3  \n",
              "13632       0.0         45.0         3.0  24.5  \n",
              "13633       0.0        315.0         0.0  27.3  \n",
              "13634       0.0         45.0         0.8  33.5  \n",
              "\n",
              "[13635 rows x 19 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-dffcd8e7-6789-493e-925e-573343c77cef\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\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>mac</th>\n",
              "      <th>station_name</th>\n",
              "      <th>tambon_code</th>\n",
              "      <th>tambon_namt</th>\n",
              "      <th>amphur_code</th>\n",
              "      <th>amphur_namt</th>\n",
              "      <th>province_code</th>\n",
              "      <th>province_namt</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>time</th>\n",
              "      <th>humid</th>\n",
              "      <th>light</th>\n",
              "      <th>pm10</th>\n",
              "      <th>pm2.5</th>\n",
              "      <th>rainfall</th>\n",
              "      <th>wind_direct</th>\n",
              "      <th>wind_speed</th>\n",
              "      <th>temp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3C71BF18EA64</td>\n",
              "      <td>บ้านนา_2</td>\n",
              "      <td>300903</td>\n",
              "      <td>กำปัง</td>\n",
              "      <td>3009</td>\n",
              "      <td>โนนไทย</td>\n",
              "      <td>30</td>\n",
              "      <td>นครราชสีมา</td>\n",
              "      <td>15.112831</td>\n",
              "      <td>102.052114</td>\n",
              "      <td>2022-07-20 15:00:00+07:00</td>\n",
              "      <td>70.6</td>\n",
              "      <td>59.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>4.3</td>\n",
              "      <td>32.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3C71BF18EA64</td>\n",
              "      <td>บ้านนา_2</td>\n",
              "      <td>300903</td>\n",
              "      <td>กำปัง</td>\n",
              "      <td>3009</td>\n",
              "      <td>โนนไทย</td>\n",
              "      <td>30</td>\n",
              "      <td>นครราชสีมา</td>\n",
              "      <td>15.112831</td>\n",
              "      <td>102.052114</td>\n",
              "      <td>2022-05-16 09:00:00+07:00</td>\n",
              "      <td>62.3</td>\n",
              "      <td>76.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>1.9</td>\n",
              "      <td>37.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3C71BF18EA64</td>\n",
              "      <td>บ้านนา_2</td>\n",
              "      <td>300903</td>\n",
              "      <td>กำปัง</td>\n",
              "      <td>3009</td>\n",
              "      <td>โนนไทย</td>\n",
              "      <td>30</td>\n",
              "      <td>นครราชสีมา</td>\n",
              "      <td>15.112831</td>\n",
              "      <td>102.052114</td>\n",
              "      <td>2022-06-26 19:00:00+07:00</td>\n",
              "      <td>90.3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>26.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3C71BF18EA64</td>\n",
              "      <td>บ้านนา_2</td>\n",
              "      <td>300903</td>\n",
              "      <td>กำปัง</td>\n",
              "      <td>3009</td>\n",
              "      <td>โนนไทย</td>\n",
              "      <td>30</td>\n",
              "      <td>นครราชสีมา</td>\n",
              "      <td>15.112831</td>\n",
              "      <td>102.052114</td>\n",
              "      <td>2022-07-16 04:00:00+07:00</td>\n",
              "      <td>91.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>157.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>25.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3C71BF18EA64</td>\n",
              "      <td>บ้านนา_2</td>\n",
              "      <td>300903</td>\n",
              "      <td>กำปัง</td>\n",
              "      <td>3009</td>\n",
              "      <td>โนนไทย</td>\n",
              "      <td>30</td>\n",
              "      <td>นครราชสีมา</td>\n",
              "      <td>15.112831</td>\n",
              "      <td>102.052114</td>\n",
              "      <td>2022-05-30 08:00:00+07:00</td>\n",
              "      <td>59.1</td>\n",
              "      <td>71.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>2.3</td>\n",
              "      <td>36.2</td>\n",
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              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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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",
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              "    <tr>\n",
              "      <th>13630</th>\n",
              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
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              "    <tr>\n",
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              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
              "      <td>หนองสูง</td>\n",
              "      <td>49</td>\n",
              "      <td>มุกดาหาร</td>\n",
              "      <td>16.494229</td>\n",
              "      <td>104.350891</td>\n",
              "      <td>2022-05-03 02:00:00+07:00</td>\n",
              "      <td>80.6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>2.9</td>\n",
              "      <td>19.3</td>\n",
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              "    <tr>\n",
              "      <th>13632</th>\n",
              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
              "      <td>หนองสูง</td>\n",
              "      <td>49</td>\n",
              "      <td>มุกดาหาร</td>\n",
              "      <td>16.494229</td>\n",
              "      <td>104.350891</td>\n",
              "      <td>2022-05-19 06:00:00+07:00</td>\n",
              "      <td>87.9</td>\n",
              "      <td>37.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>24.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13633</th>\n",
              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
              "      <td>หนองสูง</td>\n",
              "      <td>49</td>\n",
              "      <td>มุกดาหาร</td>\n",
              "      <td>16.494229</td>\n",
              "      <td>104.350891</td>\n",
              "      <td>2022-06-15 02:00:00+07:00</td>\n",
              "      <td>89.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>315.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13634</th>\n",
              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
              "      <td>หนองสูง</td>\n",
              "      <td>49</td>\n",
              "      <td>มุกดาหาร</td>\n",
              "      <td>16.494229</td>\n",
              "      <td>104.350891</td>\n",
              "      <td>2022-06-05 18:00:00+07:00</td>\n",
              "      <td>66.3</td>\n",
              "      <td>43.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>0.8</td>\n",
              "      <td>33.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>13635 rows × 19 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dffcd8e7-6789-493e-925e-573343c77cef')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-dffcd8e7-6789-493e-925e-573343c77cef button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-dffcd8e7-6789-493e-925e-573343c77cef');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drop_list = ['mac','station_name','tambon_code','tambon_namt','amphur_code','amphur_namt','province_code','province_namt','latitude','longitude']\n",
        "data.drop(drop_list, axis=1,inplace = True)\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "_Oz2qZJmix8c",
        "outputId": "ab7f4186-9d66-4dc3-9ffe-a37ea1aa4ff5"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            time  humid  light  pm10  pm2.5  rainfall  \\\n",
              "0      2022-07-20 15:00:00+07:00   70.6   59.0   NaN    NaN       0.0   \n",
              "1      2022-05-16 09:00:00+07:00   62.3   76.0   NaN    NaN       0.0   \n",
              "2      2022-06-26 19:00:00+07:00   90.3    0.0   NaN    NaN       0.0   \n",
              "3      2022-07-16 04:00:00+07:00   91.7    0.0   NaN    NaN       0.0   \n",
              "4      2022-05-30 08:00:00+07:00   59.1   71.0   NaN    NaN       0.0   \n",
              "...                          ...    ...    ...   ...    ...       ...   \n",
              "13630  2022-06-14 01:00:00+07:00   97.9    0.0   NaN    NaN       4.2   \n",
              "13631  2022-05-03 02:00:00+07:00   80.6    0.0   NaN    NaN       0.0   \n",
              "13632  2022-05-19 06:00:00+07:00   87.9   37.0   NaN    NaN       0.0   \n",
              "13633  2022-06-15 02:00:00+07:00   89.9    0.0   NaN    NaN       0.0   \n",
              "13634  2022-06-05 18:00:00+07:00   66.3   43.0   NaN    NaN       0.0   \n",
              "\n",
              "       wind_direct  wind_speed  temp  \n",
              "0             45.0         4.3  32.6  \n",
              "1             45.0         1.9  37.9  \n",
              "2            135.0         3.2  26.4  \n",
              "3            157.5         0.0  25.6  \n",
              "4            180.0         2.3  36.2  \n",
              "...            ...         ...   ...  \n",
              "13630          0.0         0.0  23.5  \n",
              "13631        135.0         2.9  19.3  \n",
              "13632         45.0         3.0  24.5  \n",
              "13633        315.0         0.0  27.3  \n",
              "13634         45.0         0.8  33.5  \n",
              "\n",
              "[13635 rows x 9 columns]"
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              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>humid</th>\n",
              "      <th>light</th>\n",
              "      <th>pm10</th>\n",
              "      <th>pm2.5</th>\n",
              "      <th>rainfall</th>\n",
              "      <th>wind_direct</th>\n",
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              "    <tr>\n",
              "      <th>13630</th>\n",
              "      <td>2022-06-14 01:00:00+07:00</td>\n",
              "      <td>97.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.2</td>\n",
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              "      <td>2022-05-03 02:00:00+07:00</td>\n",
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              "      <td>19.3</td>\n",
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              "    <tr>\n",
              "      <th>13632</th>\n",
              "      <td>2022-05-19 06:00:00+07:00</td>\n",
              "      <td>87.9</td>\n",
              "      <td>37.0</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>2022-06-15 02:00:00+07:00</td>\n",
              "      <td>89.9</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f3033a7c-d791-4b77-a3c2-9f4b2f8beafa')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "                           time  humid  light  pm10  pm2.5  rainfall  \\\n",
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        "data['time']=data['time'].dt.tz_localize(None)\n",
        "data['time']=pd.to_datetime(data['time'],format='%Y-%m-%D %H:%M:%S')\n",
        "data"
      ],
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      "execution_count": 90,
      "outputs": [
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              "                     time  humid  light  pm10  pm2.5  rainfall  wind_direct  \\\n",
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              "\n",
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              "      <td>76.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>1.9</td>\n",
              "      <td>37.9</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2022-06-26 19:00:00</td>\n",
              "      <td>90.3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>26.4</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2022-07-16 04:00:00</td>\n",
              "      <td>91.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>157.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>25.6</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2022-05-30 08:00:00</td>\n",
              "      <td>59.1</td>\n",
              "      <td>71.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>180.0</td>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>13630</th>\n",
              "      <td>2022-06-14 01:00:00</td>\n",
              "      <td>97.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.5</td>\n",
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              "    <tr>\n",
              "      <th>13631</th>\n",
              "      <td>2022-05-03 02:00:00</td>\n",
              "      <td>80.6</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>2.9</td>\n",
              "      <td>19.3</td>\n",
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              "    <tr>\n",
              "      <th>13632</th>\n",
              "      <td>2022-05-19 06:00:00</td>\n",
              "      <td>87.9</td>\n",
              "      <td>37.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>3.0</td>\n",
              "      <td>24.5</td>\n",
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              "    <tr>\n",
              "      <th>13633</th>\n",
              "      <td>2022-06-15 02:00:00</td>\n",
              "      <td>89.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>315.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>27.3</td>\n",
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              "    <tr>\n",
              "      <th>13634</th>\n",
              "      <td>2022-06-05 18:00:00</td>\n",
              "      <td>66.3</td>\n",
              "      <td>43.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>0.8</td>\n",
              "      <td>33.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>13635 rows × 9 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ca9966d2-47ea-414e-8ba1-010550d6dad3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ca9966d2-47ea-414e-8ba1-010550d6dad3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ca9966d2-47ea-414e-8ba1-010550d6dad3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Bf4uqCHbi6at",
        "outputId": "d69c2c7d-f900-4ef4-8b44-b97d2bd7735d"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 13635 entries, 0 to 13634\n",
            "Data columns (total 9 columns):\n",
            " #   Column       Non-Null Count  Dtype         \n",
            "---  ------       --------------  -----         \n",
            " 0   time         13635 non-null  datetime64[ns]\n",
            " 1   humid        13635 non-null  float64       \n",
            " 2   light        13635 non-null  float64       \n",
            " 3   pm10         6841 non-null   float64       \n",
            " 4   pm2.5        6841 non-null   float64       \n",
            " 5   rainfall     13635 non-null  float64       \n",
            " 6   wind_direct  13635 non-null  float64       \n",
            " 7   wind_speed   13635 non-null  float64       \n",
            " 8   temp         13634 non-null  float64       \n",
            "dtypes: datetime64[ns](1), float64(8)\n",
            "memory usage: 958.8 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y5arQZI3i-_k",
        "outputId": "fd87b5ff-89a0-417a-bd3e-cf1d40bdd132"
      },
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "time              0\n",
              "humid             0\n",
              "light             0\n",
              "pm10           6794\n",
              "pm2.5          6794\n",
              "rainfall          0\n",
              "wind_direct       0\n",
              "wind_speed        0\n",
              "temp              1\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = data[data['temp'].notna()]\n",
        "data.drop(['pm10','pm2.5'], axis=1,inplace = True)\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "RljxBUGxtvH_",
        "outputId": "09249db5-da4b-4484-bb71-bf047aaecf3f"
      },
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     time  humid  light  rainfall  wind_direct  wind_speed  \\\n",
              "0     2022-07-20 15:00:00   70.6   59.0       0.0         45.0         4.3   \n",
              "1     2022-05-16 09:00:00   62.3   76.0       0.0         45.0         1.9   \n",
              "2     2022-06-26 19:00:00   90.3    0.0       0.0        135.0         3.2   \n",
              "3     2022-07-16 04:00:00   91.7    0.0       0.0        157.5         0.0   \n",
              "4     2022-05-30 08:00:00   59.1   71.0       0.0        180.0         2.3   \n",
              "...                   ...    ...    ...       ...          ...         ...   \n",
              "13630 2022-06-14 01:00:00   97.9    0.0       4.2          0.0         0.0   \n",
              "13631 2022-05-03 02:00:00   80.6    0.0       0.0        135.0         2.9   \n",
              "13632 2022-05-19 06:00:00   87.9   37.0       0.0         45.0         3.0   \n",
              "13633 2022-06-15 02:00:00   89.9    0.0       0.0        315.0         0.0   \n",
              "13634 2022-06-05 18:00:00   66.3   43.0       0.0         45.0         0.8   \n",
              "\n",
              "       temp  \n",
              "0      32.6  \n",
              "1      37.9  \n",
              "2      26.4  \n",
              "3      25.6  \n",
              "4      36.2  \n",
              "...     ...  \n",
              "13630  23.5  \n",
              "13631  19.3  \n",
              "13632  24.5  \n",
              "13633  27.3  \n",
              "13634  33.5  \n",
              "\n",
              "[13634 rows x 7 columns]"
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              "\n",
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              "          const element = document.querySelector('#df-3c0fd836-1385-49e3-a0a5-1dfe467e7bca');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sort_data = data.sort_values(by='time',ascending=True)\n",
        "sort_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "gtpOGH2djI6U",
        "outputId": "e29a43cc-48e3-465f-b739-37f58da92d97"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     time  humid  light  rainfall  wind_direct  wind_speed  \\\n",
              "10145 2022-05-02 00:00:00   78.3    0.0       0.0        270.0         0.0   \n",
              "13614 2022-05-02 00:00:00   97.7    0.0       1.5         45.0         4.9   \n",
              "5098  2022-05-02 00:00:00   93.9    0.0       0.0        135.0         4.1   \n",
              "11871 2022-05-02 00:00:00   76.7    0.0       0.0        225.0         5.8   \n",
              "1678  2022-05-02 00:00:00   94.7    0.0       0.9         45.0         5.8   \n",
              "...                   ...    ...    ...       ...          ...         ...   \n",
              "55    2022-07-31 21:00:00   92.2    0.0      21.5          0.0         6.3   \n",
              "10275 2022-07-31 21:00:00   80.7    0.0       0.9         45.0         0.0   \n",
              "1806  2022-07-31 21:00:00   85.6    0.0       0.0          0.0         0.0   \n",
              "8545  2022-07-31 21:00:00   86.2    0.0       0.0        135.0         0.0   \n",
              "6830  2022-07-31 21:00:00   97.5    0.0       0.0          0.0         0.0   \n",
              "\n",
              "       temp  \n",
              "10145  27.0  \n",
              "13614  19.6  \n",
              "5098   23.6  \n",
              "11871  29.8  \n",
              "1678   22.5  \n",
              "...     ...  \n",
              "55     24.5  \n",
              "10275  29.0  \n",
              "1806   28.4  \n",
              "8545   25.6  \n",
              "6830   25.3  \n",
              "\n",
              "[13634 rows x 7 columns]"
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              "<p>13634 rows × 7 columns</p>\n",
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              "\n",
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              "          document.querySelector('#df-30d2b52d-74b3-4f19-9681-aa11a3eac617 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-30d2b52d-74b3-4f19-9681-aa11a3eac617');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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            ]
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_data=sort_data.copy()"
      ],
      "metadata": {
        "id": "VCFm1vhKCVJS"
      },
      "execution_count": 95,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_data['MA'] = data['temp'].rolling(36).mean()"
      ],
      "metadata": {
        "id": "uAlNebCM5a6q"
      },
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig = px.line(plot_data, x=\"time\", y=[\"temp\",\"MA\"], template = 'plotly_dark')\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "tvEQHd2rjLM7",
        "outputId": "2b436da9-00b0-43ad-fe6a-e61b1e5df53e"
      },
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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    {
      "cell_type": "code",
      "source": [
        "sort_data.drop(['time'],axis=1,inplace = True)\n",
        "sort_data"
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      "execution_count": 98,
      "outputs": [
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            "text/plain": [
              "       humid  light  rainfall  wind_direct  wind_speed  temp\n",
              "10145   78.3    0.0       0.0        270.0         0.0  27.0\n",
              "13614   97.7    0.0       1.5         45.0         4.9  19.6\n",
              "5098    93.9    0.0       0.0        135.0         4.1  23.6\n",
              "11871   76.7    0.0       0.0        225.0         5.8  29.8\n",
              "1678    94.7    0.0       0.9         45.0         5.8  22.5\n",
              "...      ...    ...       ...          ...         ...   ...\n",
              "55      92.2    0.0      21.5          0.0         6.3  24.5\n",
              "10275   80.7    0.0       0.9         45.0         0.0  29.0\n",
              "1806    85.6    0.0       0.0          0.0         0.0  28.4\n",
              "8545    86.2    0.0       0.0        135.0         0.0  25.6\n",
              "6830    97.5    0.0       0.0          0.0         0.0  25.3\n",
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              "[13634 rows x 6 columns]"
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              "      <th>humid</th>\n",
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              "      <th>55</th>\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a943ac79-b8a7-48a3-af8a-0213bd3a2733');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Model"
      ],
      "metadata": {
        "id": "GL_xHDioZa8M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "pc_train,pc_test = train_test_split(sort_data,test_size=0.2,shuffle=False)\n",
        "pc_train.shape , pc_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z7ulh4ncjM8E",
        "outputId": "f8e2b064-b2e2-40cf-ea63-9284fc38307c"
      },
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((10907, 6), (2727, 6))"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s = setup(data = pc_train, test_data = pc_test, target = 'temp', session_id = 123)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "yO4SDOUpjbjW",
        "outputId": "6fb384da-9637-4216-b98d-7058ee16a25c"
      },
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f5b1850e990>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_be752_row7_col1 {\n",
              "  background-color: lightgreen;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_be752_\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th class=\"col_heading level0 col0\" >Description</th>\n",
              "      <th class=\"col_heading level0 col1\" >Value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_be752_row0_col0\" class=\"data row0 col0\" >Session id</td>\n",
              "      <td id=\"T_be752_row0_col1\" class=\"data row0 col1\" >123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_be752_row1_col0\" class=\"data row1 col0\" >Target</td>\n",
              "      <td id=\"T_be752_row1_col1\" class=\"data row1 col1\" >temp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_be752_row2_col0\" class=\"data row2 col0\" >Target type</td>\n",
              "      <td id=\"T_be752_row2_col1\" class=\"data row2 col1\" >Regression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_be752_row3_col0\" class=\"data row3 col0\" >Data shape</td>\n",
              "      <td id=\"T_be752_row3_col1\" class=\"data row3 col1\" >(13634, 6)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_be752_row4_col0\" class=\"data row4 col0\" >Train data shape</td>\n",
              "      <td id=\"T_be752_row4_col1\" class=\"data row4 col1\" >(10907, 6)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_be752_row5_col0\" class=\"data row5 col0\" >Test data shape</td>\n",
              "      <td id=\"T_be752_row5_col1\" class=\"data row5 col1\" >(2727, 6)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_be752_row6_col0\" class=\"data row6 col0\" >Numeric features</td>\n",
              "      <td id=\"T_be752_row6_col1\" class=\"data row6 col1\" >5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_be752_row7_col0\" class=\"data row7 col0\" >Preprocess</td>\n",
              "      <td id=\"T_be752_row7_col1\" class=\"data row7 col1\" >True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_be752_row8_col0\" class=\"data row8 col0\" >Imputation type</td>\n",
              "      <td id=\"T_be752_row8_col1\" class=\"data row8 col1\" >simple</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_be752_row9_col0\" class=\"data row9 col0\" >Numeric imputation</td>\n",
              "      <td id=\"T_be752_row9_col1\" class=\"data row9 col1\" >mean</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_be752_row10_col0\" class=\"data row10 col0\" >Categorical imputation</td>\n",
              "      <td id=\"T_be752_row10_col1\" class=\"data row10 col1\" >constant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_be752_row11_col0\" class=\"data row11 col0\" >Low variance threshold</td>\n",
              "      <td id=\"T_be752_row11_col1\" class=\"data row11 col1\" >0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_be752_row12_col0\" class=\"data row12 col0\" >Fold Generator</td>\n",
              "      <td id=\"T_be752_row12_col1\" class=\"data row12 col1\" >KFold</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_be752_row13_col0\" class=\"data row13 col0\" >Fold Number</td>\n",
              "      <td id=\"T_be752_row13_col1\" class=\"data row13 col1\" >10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_be752_row14_col0\" class=\"data row14 col0\" >CPU Jobs</td>\n",
              "      <td id=\"T_be752_row14_col1\" class=\"data row14 col1\" >-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_be752_row15_col0\" class=\"data row15 col0\" >Use GPU</td>\n",
              "      <td id=\"T_be752_row15_col1\" class=\"data row15 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_be752_row16_col0\" class=\"data row16 col0\" >Log Experiment</td>\n",
              "      <td id=\"T_be752_row16_col1\" class=\"data row16 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_be752_row17_col0\" class=\"data row17 col0\" >Experiment Name</td>\n",
              "      <td id=\"T_be752_row17_col1\" class=\"data row17 col1\" >reg-default-name</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_be752_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_be752_row18_col0\" class=\"data row18 col0\" >USI</td>\n",
              "      <td id=\"T_be752_row18_col1\" class=\"data row18 col1\" >e80d</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "best = compare_models()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614,
          "referenced_widgets": [
            "41b1730ecbae4f138d64a5e91895cc11",
            "56445e6f879247c18ad82a57cfbc84c9",
            "04781cd3c54c47e98bb3e64a8550c71b",
            "88e003abad61474fbbc66f0fcc57d9e8",
            "079540361247425e9712de799bca4b5c",
            "4945495a7eeb4bd1874b0eda3b6285e4",
            "9e278751cc1f460aa84cd9efbe9820fa",
            "5adeb13b922044f7a18fa5ea38673b1e",
            "9472086a3ec441ad9e70559127628f6c",
            "bc28c56f130e4ce5a9d8183408d2012a",
            "632c69a765be482b9051dbc666f39aee"
          ]
        },
        "id": "oX2rvwWfvCBc",
        "outputId": "432470a9-8e93-4def-c0d3-5e825dfdfa1e"
      },
      "execution_count": 106,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": []
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f5b1abff150>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_36002_ th {\n",
              "  text-align: left;\n",
              "}\n",
              "#T_36002_row0_col0, #T_36002_row0_col3, #T_36002_row0_col5, #T_36002_row1_col0, #T_36002_row1_col1, #T_36002_row1_col2, #T_36002_row1_col4, #T_36002_row1_col6, #T_36002_row2_col0, #T_36002_row2_col1, #T_36002_row2_col2, #T_36002_row2_col3, #T_36002_row2_col4, #T_36002_row2_col5, #T_36002_row2_col6, #T_36002_row3_col0, #T_36002_row3_col1, #T_36002_row3_col2, #T_36002_row3_col3, #T_36002_row3_col4, #T_36002_row3_col5, #T_36002_row3_col6, #T_36002_row4_col0, #T_36002_row4_col1, #T_36002_row4_col2, #T_36002_row4_col3, #T_36002_row4_col4, #T_36002_row4_col5, #T_36002_row4_col6, #T_36002_row5_col0, #T_36002_row5_col1, #T_36002_row5_col2, #T_36002_row5_col3, #T_36002_row5_col4, #T_36002_row5_col5, #T_36002_row5_col6, #T_36002_row6_col0, #T_36002_row6_col1, #T_36002_row6_col2, #T_36002_row6_col3, #T_36002_row6_col4, #T_36002_row6_col5, #T_36002_row6_col6, #T_36002_row7_col0, #T_36002_row7_col1, #T_36002_row7_col2, #T_36002_row7_col3, #T_36002_row7_col4, #T_36002_row7_col5, #T_36002_row7_col6, #T_36002_row8_col0, #T_36002_row8_col1, #T_36002_row8_col2, #T_36002_row8_col3, #T_36002_row8_col4, #T_36002_row8_col5, #T_36002_row8_col6, #T_36002_row9_col0, #T_36002_row9_col1, #T_36002_row9_col2, #T_36002_row9_col3, #T_36002_row9_col4, #T_36002_row9_col5, #T_36002_row9_col6, #T_36002_row10_col0, #T_36002_row10_col1, #T_36002_row10_col2, #T_36002_row10_col3, #T_36002_row10_col4, #T_36002_row10_col5, #T_36002_row10_col6, #T_36002_row11_col0, #T_36002_row11_col1, #T_36002_row11_col2, #T_36002_row11_col3, #T_36002_row11_col4, #T_36002_row11_col5, #T_36002_row11_col6, #T_36002_row12_col0, #T_36002_row12_col1, #T_36002_row12_col2, #T_36002_row12_col3, #T_36002_row12_col4, #T_36002_row12_col5, #T_36002_row12_col6, #T_36002_row13_col0, #T_36002_row13_col1, #T_36002_row13_col2, #T_36002_row13_col3, #T_36002_row13_col4, #T_36002_row13_col5, #T_36002_row13_col6, #T_36002_row14_col0, #T_36002_row14_col1, #T_36002_row14_col2, #T_36002_row14_col3, #T_36002_row14_col4, #T_36002_row14_col5, #T_36002_row14_col6, #T_36002_row15_col0, #T_36002_row15_col1, #T_36002_row15_col2, #T_36002_row15_col3, #T_36002_row15_col4, #T_36002_row15_col5, #T_36002_row15_col6, #T_36002_row16_col0, #T_36002_row16_col1, #T_36002_row16_col2, #T_36002_row16_col3, #T_36002_row16_col4, #T_36002_row16_col5, #T_36002_row16_col6, #T_36002_row17_col0, #T_36002_row17_col1, #T_36002_row17_col2, #T_36002_row17_col3, #T_36002_row17_col4, #T_36002_row17_col5, #T_36002_row17_col6 {\n",
              "  text-align: left;\n",
              "}\n",
              "#T_36002_row0_col1, #T_36002_row0_col2, #T_36002_row0_col4, #T_36002_row0_col6, #T_36002_row1_col3, #T_36002_row1_col5 {\n",
              "  text-align: left;\n",
              "  background-color: yellow;\n",
              "}\n",
              "#T_36002_row0_col7, #T_36002_row1_col7, #T_36002_row2_col7, #T_36002_row3_col7, #T_36002_row4_col7, #T_36002_row5_col7, #T_36002_row6_col7, #T_36002_row7_col7, #T_36002_row8_col7, #T_36002_row9_col7, #T_36002_row10_col7, #T_36002_row11_col7, #T_36002_row12_col7, #T_36002_row13_col7, #T_36002_row14_col7, #T_36002_row16_col7, #T_36002_row17_col7 {\n",
              "  text-align: left;\n",
              "  background-color: lightgrey;\n",
              "}\n",
              "#T_36002_row15_col7 {\n",
              "  text-align: left;\n",
              "  background-color: yellow;\n",
              "  background-color: lightgrey;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_36002_\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th class=\"col_heading level0 col0\" >Model</th>\n",
              "      <th class=\"col_heading level0 col1\" >MAE</th>\n",
              "      <th class=\"col_heading level0 col2\" >MSE</th>\n",
              "      <th class=\"col_heading level0 col3\" >RMSE</th>\n",
              "      <th class=\"col_heading level0 col4\" >R2</th>\n",
              "      <th class=\"col_heading level0 col5\" >RMSLE</th>\n",
              "      <th class=\"col_heading level0 col6\" >MAPE</th>\n",
              "      <th class=\"col_heading level0 col7\" >TT (Sec)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row0\" class=\"row_heading level0 row0\" >lightgbm</th>\n",
              "      <td id=\"T_36002_row0_col0\" class=\"data row0 col0\" >Light Gradient Boosting Machine</td>\n",
              "      <td id=\"T_36002_row0_col1\" class=\"data row0 col1\" >1.1375</td>\n",
              "      <td id=\"T_36002_row0_col2\" class=\"data row0 col2\" >3.0189</td>\n",
              "      <td id=\"T_36002_row0_col3\" class=\"data row0 col3\" >1.5039</td>\n",
              "      <td id=\"T_36002_row0_col4\" class=\"data row0 col4\" >0.8381</td>\n",
              "      <td id=\"T_36002_row0_col5\" class=\"data row0 col5\" >0.0497</td>\n",
              "      <td id=\"T_36002_row0_col6\" class=\"data row0 col6\" >0.0404</td>\n",
              "      <td id=\"T_36002_row0_col7\" class=\"data row0 col7\" >0.1280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row1\" class=\"row_heading level0 row1\" >gbr</th>\n",
              "      <td id=\"T_36002_row1_col0\" class=\"data row1 col0\" >Gradient Boosting Regressor</td>\n",
              "      <td id=\"T_36002_row1_col1\" class=\"data row1 col1\" >1.1472</td>\n",
              "      <td id=\"T_36002_row1_col2\" class=\"data row1 col2\" >3.0659</td>\n",
              "      <td id=\"T_36002_row1_col3\" class=\"data row1 col3\" >1.5017</td>\n",
              "      <td id=\"T_36002_row1_col4\" class=\"data row1 col4\" >0.8360</td>\n",
              "      <td id=\"T_36002_row1_col5\" class=\"data row1 col5\" >0.0495</td>\n",
              "      <td id=\"T_36002_row1_col6\" class=\"data row1 col6\" >0.0407</td>\n",
              "      <td id=\"T_36002_row1_col7\" class=\"data row1 col7\" >0.5090</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row2\" class=\"row_heading level0 row2\" >rf</th>\n",
              "      <td id=\"T_36002_row2_col0\" class=\"data row2 col0\" >Random Forest Regressor</td>\n",
              "      <td id=\"T_36002_row2_col1\" class=\"data row2 col1\" >1.2138</td>\n",
              "      <td id=\"T_36002_row2_col2\" class=\"data row2 col2\" >3.3444</td>\n",
              "      <td id=\"T_36002_row2_col3\" class=\"data row2 col3\" >1.6100</td>\n",
              "      <td id=\"T_36002_row2_col4\" class=\"data row2 col4\" >0.8196</td>\n",
              "      <td id=\"T_36002_row2_col5\" class=\"data row2 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row2_col6\" class=\"data row2 col6\" >0.0431</td>\n",
              "      <td id=\"T_36002_row2_col7\" class=\"data row2 col7\" >1.8250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row3\" class=\"row_heading level0 row3\" >knn</th>\n",
              "      <td id=\"T_36002_row3_col0\" class=\"data row3 col0\" >K Neighbors Regressor</td>\n",
              "      <td id=\"T_36002_row3_col1\" class=\"data row3 col1\" >1.2421</td>\n",
              "      <td id=\"T_36002_row3_col2\" class=\"data row3 col2\" >3.3288</td>\n",
              "      <td id=\"T_36002_row3_col3\" class=\"data row3 col3\" >1.6499</td>\n",
              "      <td id=\"T_36002_row3_col4\" class=\"data row3 col4\" >0.8188</td>\n",
              "      <td id=\"T_36002_row3_col5\" class=\"data row3 col5\" >0.0548</td>\n",
              "      <td id=\"T_36002_row3_col6\" class=\"data row3 col6\" >0.0440</td>\n",
              "      <td id=\"T_36002_row3_col7\" class=\"data row3 col7\" >0.0850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row4\" class=\"row_heading level0 row4\" >en</th>\n",
              "      <td id=\"T_36002_row4_col0\" class=\"data row4 col0\" >Elastic Net</td>\n",
              "      <td id=\"T_36002_row4_col1\" class=\"data row4 col1\" >1.2455</td>\n",
              "      <td id=\"T_36002_row4_col2\" class=\"data row4 col2\" >3.3518</td>\n",
              "      <td id=\"T_36002_row4_col3\" class=\"data row4 col3\" >1.6519</td>\n",
              "      <td id=\"T_36002_row4_col4\" class=\"data row4 col4\" >0.8185</td>\n",
              "      <td id=\"T_36002_row4_col5\" class=\"data row4 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row4_col6\" class=\"data row4 col6\" >0.0438</td>\n",
              "      <td id=\"T_36002_row4_col7\" class=\"data row4 col7\" >0.0370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row5\" class=\"row_heading level0 row5\" >ridge</th>\n",
              "      <td id=\"T_36002_row5_col0\" class=\"data row5 col0\" >Ridge Regression</td>\n",
              "      <td id=\"T_36002_row5_col1\" class=\"data row5 col1\" >1.2462</td>\n",
              "      <td id=\"T_36002_row5_col2\" class=\"data row5 col2\" >3.3560</td>\n",
              "      <td id=\"T_36002_row5_col3\" class=\"data row5 col3\" >1.6476</td>\n",
              "      <td id=\"T_36002_row5_col4\" class=\"data row5 col4\" >0.8184</td>\n",
              "      <td id=\"T_36002_row5_col5\" class=\"data row5 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row5_col6\" class=\"data row5 col6\" >0.0438</td>\n",
              "      <td id=\"T_36002_row5_col7\" class=\"data row5 col7\" >0.0350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row6\" class=\"row_heading level0 row6\" >lar</th>\n",
              "      <td id=\"T_36002_row6_col0\" class=\"data row6 col0\" >Least Angle Regression</td>\n",
              "      <td id=\"T_36002_row6_col1\" class=\"data row6 col1\" >1.2462</td>\n",
              "      <td id=\"T_36002_row6_col2\" class=\"data row6 col2\" >3.3560</td>\n",
              "      <td id=\"T_36002_row6_col3\" class=\"data row6 col3\" >1.6476</td>\n",
              "      <td id=\"T_36002_row6_col4\" class=\"data row6 col4\" >0.8184</td>\n",
              "      <td id=\"T_36002_row6_col5\" class=\"data row6 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row6_col6\" class=\"data row6 col6\" >0.0438</td>\n",
              "      <td id=\"T_36002_row6_col7\" class=\"data row6 col7\" >0.0380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row7\" class=\"row_heading level0 row7\" >br</th>\n",
              "      <td id=\"T_36002_row7_col0\" class=\"data row7 col0\" >Bayesian Ridge</td>\n",
              "      <td id=\"T_36002_row7_col1\" class=\"data row7 col1\" >1.2462</td>\n",
              "      <td id=\"T_36002_row7_col2\" class=\"data row7 col2\" >3.3560</td>\n",
              "      <td id=\"T_36002_row7_col3\" class=\"data row7 col3\" >1.6477</td>\n",
              "      <td id=\"T_36002_row7_col4\" class=\"data row7 col4\" >0.8184</td>\n",
              "      <td id=\"T_36002_row7_col5\" class=\"data row7 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row7_col6\" class=\"data row7 col6\" >0.0438</td>\n",
              "      <td id=\"T_36002_row7_col7\" class=\"data row7 col7\" >0.0420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row8\" class=\"row_heading level0 row8\" >lasso</th>\n",
              "      <td id=\"T_36002_row8_col0\" class=\"data row8 col0\" >Lasso Regression</td>\n",
              "      <td id=\"T_36002_row8_col1\" class=\"data row8 col1\" >1.2459</td>\n",
              "      <td id=\"T_36002_row8_col2\" class=\"data row8 col2\" >3.3542</td>\n",
              "      <td id=\"T_36002_row8_col3\" class=\"data row8 col3\" >1.6553</td>\n",
              "      <td id=\"T_36002_row8_col4\" class=\"data row8 col4\" >0.8184</td>\n",
              "      <td id=\"T_36002_row8_col5\" class=\"data row8 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row8_col6\" class=\"data row8 col6\" >0.0437</td>\n",
              "      <td id=\"T_36002_row8_col7\" class=\"data row8 col7\" >0.0380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row9\" class=\"row_heading level0 row9\" >lr</th>\n",
              "      <td id=\"T_36002_row9_col0\" class=\"data row9 col0\" >Linear Regression</td>\n",
              "      <td id=\"T_36002_row9_col1\" class=\"data row9 col1\" >1.2462</td>\n",
              "      <td id=\"T_36002_row9_col2\" class=\"data row9 col2\" >3.3560</td>\n",
              "      <td id=\"T_36002_row9_col3\" class=\"data row9 col3\" >1.6476</td>\n",
              "      <td id=\"T_36002_row9_col4\" class=\"data row9 col4\" >0.8184</td>\n",
              "      <td id=\"T_36002_row9_col5\" class=\"data row9 col5\" >0.0536</td>\n",
              "      <td id=\"T_36002_row9_col6\" class=\"data row9 col6\" >0.0438</td>\n",
              "      <td id=\"T_36002_row9_col7\" class=\"data row9 col7\" >0.1340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row10\" class=\"row_heading level0 row10\" >et</th>\n",
              "      <td id=\"T_36002_row10_col0\" class=\"data row10 col0\" >Extra Trees Regressor</td>\n",
              "      <td id=\"T_36002_row10_col1\" class=\"data row10 col1\" >1.2393</td>\n",
              "      <td id=\"T_36002_row10_col2\" class=\"data row10 col2\" >3.4549</td>\n",
              "      <td id=\"T_36002_row10_col3\" class=\"data row10 col3\" >1.6514</td>\n",
              "      <td id=\"T_36002_row10_col4\" class=\"data row10 col4\" >0.8133</td>\n",
              "      <td id=\"T_36002_row10_col5\" class=\"data row10 col5\" >0.0554</td>\n",
              "      <td id=\"T_36002_row10_col6\" class=\"data row10 col6\" >0.0440</td>\n",
              "      <td id=\"T_36002_row10_col7\" class=\"data row10 col7\" >1.2740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row11\" class=\"row_heading level0 row11\" >omp</th>\n",
              "      <td id=\"T_36002_row11_col0\" class=\"data row11 col0\" >Orthogonal Matching Pursuit</td>\n",
              "      <td id=\"T_36002_row11_col1\" class=\"data row11 col1\" >1.3322</td>\n",
              "      <td id=\"T_36002_row11_col2\" class=\"data row11 col2\" >3.7892</td>\n",
              "      <td id=\"T_36002_row11_col3\" class=\"data row11 col3\" >1.7579</td>\n",
              "      <td id=\"T_36002_row11_col4\" class=\"data row11 col4\" >0.7936</td>\n",
              "      <td id=\"T_36002_row11_col5\" class=\"data row11 col5\" >0.0571</td>\n",
              "      <td id=\"T_36002_row11_col6\" class=\"data row11 col6\" >0.0467</td>\n",
              "      <td id=\"T_36002_row11_col7\" class=\"data row11 col7\" >0.0360</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row12\" class=\"row_heading level0 row12\" >dt</th>\n",
              "      <td id=\"T_36002_row12_col0\" class=\"data row12 col0\" >Decision Tree Regressor</td>\n",
              "      <td id=\"T_36002_row12_col1\" class=\"data row12 col1\" >1.5954</td>\n",
              "      <td id=\"T_36002_row12_col2\" class=\"data row12 col2\" >5.5906</td>\n",
              "      <td id=\"T_36002_row12_col3\" class=\"data row12 col3\" >2.2563</td>\n",
              "      <td id=\"T_36002_row12_col4\" class=\"data row12 col4\" >0.6899</td>\n",
              "      <td id=\"T_36002_row12_col5\" class=\"data row12 col5\" >0.0774</td>\n",
              "      <td id=\"T_36002_row12_col6\" class=\"data row12 col6\" >0.0562</td>\n",
              "      <td id=\"T_36002_row12_col7\" class=\"data row12 col7\" >0.0580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row13\" class=\"row_heading level0 row13\" >ada</th>\n",
              "      <td id=\"T_36002_row13_col0\" class=\"data row13 col0\" >AdaBoost Regressor</td>\n",
              "      <td id=\"T_36002_row13_col1\" class=\"data row13 col1\" >2.0586</td>\n",
              "      <td id=\"T_36002_row13_col2\" class=\"data row13 col2\" >6.6702</td>\n",
              "      <td id=\"T_36002_row13_col3\" class=\"data row13 col3\" >2.5329</td>\n",
              "      <td id=\"T_36002_row13_col4\" class=\"data row13 col4\" >0.6257</td>\n",
              "      <td id=\"T_36002_row13_col5\" class=\"data row13 col5\" >0.0860</td>\n",
              "      <td id=\"T_36002_row13_col6\" class=\"data row13 col6\" >0.0708</td>\n",
              "      <td id=\"T_36002_row13_col7\" class=\"data row13 col7\" >0.3230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row14\" class=\"row_heading level0 row14\" >llar</th>\n",
              "      <td id=\"T_36002_row14_col0\" class=\"data row14 col0\" >Lasso Least Angle Regression</td>\n",
              "      <td id=\"T_36002_row14_col1\" class=\"data row14 col1\" >3.4556</td>\n",
              "      <td id=\"T_36002_row14_col2\" class=\"data row14 col2\" >18.6021</td>\n",
              "      <td id=\"T_36002_row14_col3\" class=\"data row14 col3\" >4.2987</td>\n",
              "      <td id=\"T_36002_row14_col4\" class=\"data row14 col4\" >-0.0581</td>\n",
              "      <td id=\"T_36002_row14_col5\" class=\"data row14 col5\" >0.1386</td>\n",
              "      <td id=\"T_36002_row14_col6\" class=\"data row14 col6\" >0.1186</td>\n",
              "      <td id=\"T_36002_row14_col7\" class=\"data row14 col7\" >0.0370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row15\" class=\"row_heading level0 row15\" >dummy</th>\n",
              "      <td id=\"T_36002_row15_col0\" class=\"data row15 col0\" >Dummy Regressor</td>\n",
              "      <td id=\"T_36002_row15_col1\" class=\"data row15 col1\" >3.4556</td>\n",
              "      <td id=\"T_36002_row15_col2\" class=\"data row15 col2\" >18.6021</td>\n",
              "      <td id=\"T_36002_row15_col3\" class=\"data row15 col3\" >4.2987</td>\n",
              "      <td id=\"T_36002_row15_col4\" class=\"data row15 col4\" >-0.0581</td>\n",
              "      <td id=\"T_36002_row15_col5\" class=\"data row15 col5\" >0.1386</td>\n",
              "      <td id=\"T_36002_row15_col6\" class=\"data row15 col6\" >0.1186</td>\n",
              "      <td id=\"T_36002_row15_col7\" class=\"data row15 col7\" >0.0330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row16\" class=\"row_heading level0 row16\" >huber</th>\n",
              "      <td id=\"T_36002_row16_col0\" class=\"data row16 col0\" >Huber Regressor</td>\n",
              "      <td id=\"T_36002_row16_col1\" class=\"data row16 col1\" >1.2987</td>\n",
              "      <td id=\"T_36002_row16_col2\" class=\"data row16 col2\" >79.9523</td>\n",
              "      <td id=\"T_36002_row16_col3\" class=\"data row16 col3\" >4.0165</td>\n",
              "      <td id=\"T_36002_row16_col4\" class=\"data row16 col4\" >-2.9539</td>\n",
              "      <td id=\"T_36002_row16_col5\" class=\"data row16 col5\" >0.0557</td>\n",
              "      <td id=\"T_36002_row16_col6\" class=\"data row16 col6\" >0.0455</td>\n",
              "      <td id=\"T_36002_row16_col7\" class=\"data row16 col7\" >0.1880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_36002_level0_row17\" class=\"row_heading level0 row17\" >par</th>\n",
              "      <td id=\"T_36002_row17_col0\" class=\"data row17 col0\" >Passive Aggressive Regressor</td>\n",
              "      <td id=\"T_36002_row17_col1\" class=\"data row17 col1\" >5.7436</td>\n",
              "      <td id=\"T_36002_row17_col2\" class=\"data row17 col2\" >1308.3964</td>\n",
              "      <td id=\"T_36002_row17_col3\" class=\"data row17 col3\" >20.7572</td>\n",
              "      <td id=\"T_36002_row17_col4\" class=\"data row17 col4\" >-70.3690</td>\n",
              "      <td id=\"T_36002_row17_col5\" class=\"data row17 col5\" >0.2346</td>\n",
              "      <td id=\"T_36002_row17_col6\" class=\"data row17 col6\" >0.1949</td>\n",
              "      <td id=\"T_36002_row17_col7\" class=\"data row17 col7\" >0.0440</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Processing:   0%|          | 0/77 [00:00<?, ?it/s]"
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              "colab": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "##Prepare Test Data"
      ],
      "metadata": {
        "id": "Cd1m6JnwQia8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "test = pd.read_csv(cwd+'/IOT/IOT_Test.csv')\n",
        "test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 748
        },
        "id": "VoG-gXhMQ34d",
        "outputId": "1670f9ac-7584-4db0-e73f-9c6c5006b357"
      },
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id           mac                   station_name  tambon_code  \\\n",
              "0        1  3C71BF18EA64                       บ้านนา_2       300903   \n",
              "1        2  3C71BF18EA64                       บ้านนา_2       300903   \n",
              "2        3  3C71BF18EA64                       บ้านนา_2       300903   \n",
              "3        4  3C71BF18EA64                       บ้านนา_2       300903   \n",
              "4        5  3C71BF18EA64                       บ้านนา_2       300903   \n",
              "...    ...           ...                            ...          ...   \n",
              "3408  3409  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706   \n",
              "3409  3410  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706   \n",
              "3410  3411  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706   \n",
              "3411  3412  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706   \n",
              "3412  3413  3C71BF18CEA4  โรงเรียนหนองสูงสามัคคีวิทยา_2       490706   \n",
              "\n",
              "       tambon_namt  amphur_code amphur_namt  province_code province_namt  \\\n",
              "0            กำปัง         3009      โนนไทย             30    นครราชสีมา   \n",
              "1            กำปัง         3009      โนนไทย             30    นครราชสีมา   \n",
              "2            กำปัง         3009      โนนไทย             30    นครราชสีมา   \n",
              "3            กำปัง         3009      โนนไทย             30    นครราชสีมา   \n",
              "4            กำปัง         3009      โนนไทย             30    นครราชสีมา   \n",
              "...            ...          ...         ...            ...           ...   \n",
              "3408  หนองสูงเหนือ         4907     หนองสูง             49      มุกดาหาร   \n",
              "3409  หนองสูงเหนือ         4907     หนองสูง             49      มุกดาหาร   \n",
              "3410  หนองสูงเหนือ         4907     หนองสูง             49      มุกดาหาร   \n",
              "3411  หนองสูงเหนือ         4907     หนองสูง             49      มุกดาหาร   \n",
              "3412  หนองสูงเหนือ         4907     หนองสูง             49      มุกดาหาร   \n",
              "\n",
              "       latitude   longitude                       time  humid  light  pm10  \\\n",
              "0     15.112831  102.052114  2022-05-23 04:00:00+07:00   88.9    1.0   NaN   \n",
              "1     15.112831  102.052114  2022-05-12 16:00:00+07:00   85.0   40.0   NaN   \n",
              "2     15.112831  102.052114  2022-06-20 03:00:00+07:00   88.9    7.0   NaN   \n",
              "3     15.112831  102.052114  2022-07-13 13:00:00+07:00   81.9   66.0   NaN   \n",
              "4     15.112831  102.052114  2022-07-05 09:00:00+07:00   64.9   71.0   NaN   \n",
              "...         ...         ...                        ...    ...    ...   ...   \n",
              "3408  16.494229  104.350891  2022-06-05 03:00:00+07:00   87.0    0.0   NaN   \n",
              "3409  16.494229  104.350891  2022-05-26 09:00:00+07:00   71.7   81.0   NaN   \n",
              "3410  16.494229  104.350891  2022-05-21 22:00:00+07:00   86.5    2.0   NaN   \n",
              "3411  16.494229  104.350891  2022-07-21 01:00:00+07:00   96.5    0.0   NaN   \n",
              "3412  16.494229  104.350891  2022-06-20 11:00:00+07:00   63.8   87.0   1.0   \n",
              "\n",
              "      pm2.5  rainfall  wind_direct  wind_speed  \n",
              "0       NaN       0.0        180.0         2.3  \n",
              "1       NaN       0.3        135.0         1.5  \n",
              "2       NaN       0.0        157.5         0.0  \n",
              "3       NaN       0.0        135.0         0.2  \n",
              "4       NaN       0.0        225.0         2.4  \n",
              "...     ...       ...          ...         ...  \n",
              "3408    NaN       0.0        315.0         0.0  \n",
              "3409    NaN       0.0        180.0         3.1  \n",
              "3410    NaN       0.0          0.0         0.6  \n",
              "3411    NaN       0.0          0.0         0.0  \n",
              "3412    0.0       0.0          0.0         0.4  \n",
              "\n",
              "[3413 rows x 19 columns]"
            ],
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              "\n",
              "  <div id=\"df-9d44f2ab-f62f-4861-9124-bed6d6aedb82\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>mac</th>\n",
              "      <th>station_name</th>\n",
              "      <th>tambon_code</th>\n",
              "      <th>tambon_namt</th>\n",
              "      <th>amphur_code</th>\n",
              "      <th>amphur_namt</th>\n",
              "      <th>province_code</th>\n",
              "      <th>province_namt</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>time</th>\n",
              "      <th>humid</th>\n",
              "      <th>light</th>\n",
              "      <th>pm10</th>\n",
              "      <th>pm2.5</th>\n",
              "      <th>rainfall</th>\n",
              "      <th>wind_direct</th>\n",
              "      <th>wind_speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>3C71BF18EA64</td>\n",
              "      <td>บ้านนา_2</td>\n",
              "      <td>300903</td>\n",
              "      <td>กำปัง</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>0.2</td>\n",
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              "    <tr>\n",
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              "      <td>5</td>\n",
              "      <td>3C71BF18EA64</td>\n",
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              "      <td>16.494229</td>\n",
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              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
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              "      <td>16.494229</td>\n",
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              "      <td>2022-05-21 22:00:00+07:00</td>\n",
              "      <td>86.5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3411</th>\n",
              "      <td>3412</td>\n",
              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
              "      <td>หนองสูง</td>\n",
              "      <td>49</td>\n",
              "      <td>มุกดาหาร</td>\n",
              "      <td>16.494229</td>\n",
              "      <td>104.350891</td>\n",
              "      <td>2022-07-21 01:00:00+07:00</td>\n",
              "      <td>96.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3412</th>\n",
              "      <td>3413</td>\n",
              "      <td>3C71BF18CEA4</td>\n",
              "      <td>โรงเรียนหนองสูงสามัคคีวิทยา_2</td>\n",
              "      <td>490706</td>\n",
              "      <td>หนองสูงเหนือ</td>\n",
              "      <td>4907</td>\n",
              "      <td>หนองสูง</td>\n",
              "      <td>49</td>\n",
              "      <td>มุกดาหาร</td>\n",
              "      <td>16.494229</td>\n",
              "      <td>104.350891</td>\n",
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              "      <td>63.8</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>3413 rows × 19 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9d44f2ab-f62f-4861-9124-bed6d6aedb82')\"\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
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              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-9d44f2ab-f62f-4861-9124-bed6d6aedb82');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test.drop(drop_list, axis=1,inplace = True)\n",
        "test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "bRWkx6SwQ3wl",
        "outputId": "096013b1-ac14-4673-dcb4-6cd3e30be4f0"
      },
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id                       time  humid  light  pm10  pm2.5  rainfall  \\\n",
              "0        1  2022-05-23 04:00:00+07:00   88.9    1.0   NaN    NaN       0.0   \n",
              "1        2  2022-05-12 16:00:00+07:00   85.0   40.0   NaN    NaN       0.3   \n",
              "2        3  2022-06-20 03:00:00+07:00   88.9    7.0   NaN    NaN       0.0   \n",
              "3        4  2022-07-13 13:00:00+07:00   81.9   66.0   NaN    NaN       0.0   \n",
              "4        5  2022-07-05 09:00:00+07:00   64.9   71.0   NaN    NaN       0.0   \n",
              "...    ...                        ...    ...    ...   ...    ...       ...   \n",
              "3408  3409  2022-06-05 03:00:00+07:00   87.0    0.0   NaN    NaN       0.0   \n",
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              "3412  3413  2022-06-20 11:00:00+07:00   63.8   87.0   1.0    0.0       0.0   \n",
              "\n",
              "      wind_direct  wind_speed  \n",
              "0           180.0         2.3  \n",
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              "...           ...         ...  \n",
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              "      <td>87.0</td>\n",
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              "    <tr>\n",
              "      <th>3409</th>\n",
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              "      <td>71.7</td>\n",
              "      <td>81.0</td>\n",
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              "    <tr>\n",
              "      <th>3410</th>\n",
              "      <td>3411</td>\n",
              "      <td>2022-05-21 22:00:00+07:00</td>\n",
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              "    <tr>\n",
              "      <th>3411</th>\n",
              "      <td>3412</td>\n",
              "      <td>2022-07-21 01:00:00+07:00</td>\n",
              "      <td>96.5</td>\n",
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              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>3412</th>\n",
              "      <td>3413</td>\n",
              "      <td>2022-06-20 11:00:00+07:00</td>\n",
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              "<p>3413 rows × 9 columns</p>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
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              "  "
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_id = test['id']\n",
        "test.drop(['id','time','pm10','pm2.5'], axis=1,inplace = True)\n",
        "test"
      ],
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        "colab": {
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          "height": 424
        },
        "id": "jsFemcA2Sbre",
        "outputId": "30c2585d-62b3-429b-96b4-d9413a9238fa"
      },
      "execution_count": 121,
      "outputs": [
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              "      humid  light  rainfall  wind_direct  wind_speed\n",
              "0      88.9    1.0       0.0        180.0         2.3\n",
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              "...     ...    ...       ...          ...         ...\n",
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              "3409   71.7   81.0       0.0        180.0         3.1\n",
              "3410   86.5    2.0       0.0          0.0         0.6\n",
              "3411   96.5    0.0       0.0          0.0         0.0\n",
              "3412   63.8   87.0       0.0          0.0         0.4\n",
              "\n",
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              "\n",
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              "  "
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          "metadata": {},
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    },
    {
      "cell_type": "markdown",
      "source": [
        "##Prediction\n"
      ],
      "metadata": {
        "id": "TlspLFMlTuC_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "predictions = predict_model(best, data=test)\n",
        "predictions['prediction_label']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "eUvlv1-B0AtJ",
        "outputId": "463317e9-2edf-476b-ccf4-b6a2d10e7504"
      },
      "execution_count": 118,
      "outputs": [
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              "          humid  light  rainfall  wind_direct  wind_speed  prediction_label\n",
              "0     88.900002    1.0       0.0        180.0         2.3         25.955642\n",
              "1     85.000000   40.0       0.3        135.0         1.5         26.988606\n",
              "2     88.900002    7.0       0.0        157.5         0.0         25.977603\n",
              "3     81.900002   66.0       0.0        135.0         0.2         28.693623\n",
              "4     64.900002   71.0       0.0        225.0         2.4         34.309345\n",
              "...         ...    ...       ...          ...         ...               ...\n",
              "3408  87.000000    0.0       0.0        315.0         0.0         26.788002\n",
              "3409  71.699997   81.0       0.0        180.0         3.1         32.216571\n",
              "3410  86.500000    2.0       0.0          0.0         0.6         26.478558\n",
              "3411  96.500000    0.0       0.0          0.0         0.0         24.338865\n",
              "3412  63.799999   87.0       0.0          0.0         0.4         35.327460\n",
              "\n",
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              "      <td>64.900002</td>\n",
              "      <td>71.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>2.4</td>\n",
              "      <td>34.309345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3408</th>\n",
              "      <td>87.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>315.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>26.788002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3409</th>\n",
              "      <td>71.699997</td>\n",
              "      <td>81.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>3.1</td>\n",
              "      <td>32.216571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3410</th>\n",
              "      <td>86.500000</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.6</td>\n",
              "      <td>26.478558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3411</th>\n",
              "      <td>96.500000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>24.338865</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3412</th>\n",
              "      <td>63.799999</td>\n",
              "      <td>87.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.4</td>\n",
              "      <td>35.327460</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3413 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bb3b7322-c7b2-484a-aa62-c58de84be6f5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bb3b7322-c7b2-484a-aa62-c58de84be6f5 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-bb3b7322-c7b2-484a-aa62-c58de84be6f5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "predictions['prediction_label']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kpm38n5ET1Uw",
        "outputId": "3bbf7125-d5c8-4c93-d74f-42e04db1c77e"
      },
      "execution_count": 126,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       25.955642\n",
              "1       26.988606\n",
              "2       25.977603\n",
              "3       28.693623\n",
              "4       34.309345\n",
              "          ...    \n",
              "3408    26.788002\n",
              "3409    32.216571\n",
              "3410    26.478558\n",
              "3411    24.338865\n",
              "3412    35.327460\n",
              "Name: prediction_label, Length: 3413, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 126
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_raw = pd.read_csv(cwd+'/IOT/IOT_Test2.csv')\n",
        "test_raw['id']=test_id\n",
        "test_raw['temp']=predictions['prediction_label']\n",
        "test_raw\n",
        "test_raw.to_csv(cwd+'/IOT/IOT_Test2.csv',index=False)"
      ],
      "metadata": {
        "id": "DEP-x-4-ULMh"
      },
      "execution_count": 129,
      "outputs": []
    }
  ]
}