Hackthon_ML.ipynb

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    "colab": {
      "name": "Hackthon-ML.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPz0/ZBZQRYMUlmSZZIS4pW",
      "include_colab_link": true
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      "name": "python3",
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    "language_info": {
      "name": "python"
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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/sofittech/hackathon-ml/blob/main/Hackthon_ML.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gs_IIF_NmGOJ"
      },
      "source": [
        "#Import necessary libraries\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split\n",
        "import warnings\n",
        "warnings.filterwarnings(action='ignore')"
      ],
      "execution_count": 289,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ax6_SZQemgZW"
      },
      "source": [
        "# Import training and test data\n",
        "train = pd.read_csv('training-data.csv')\n",
        "test = pd.read_csv('test-data.csv')\n",
        "\n",
        "# DATES FEATURES\n",
        "def date_features(df):\n",
        "    # Date Features\n",
        "    df['date'] = pd.to_datetime(df['date'])\n",
        "    df['year'] = df.date.dt.year\n",
        "    df['month'] = df.date.dt.month\n",
        "    df['day'] = df.date.dt.day\n",
        "    df['dayofyear'] = df.date.dt.dayofyear\n",
        "    df['dayofweek'] = df.date.dt.dayofweek\n",
        "    df['weekofyear'] = df.date.dt.weekofyear\n",
        "    \n",
        "    # Additionnal Data Features\n",
        "    df['day^year'] = np.log((np.log(df['dayofyear'] + 1)) ** (df['year'] - 2000))\n",
        "    \n",
        "    # Drop date\n",
        "    df.drop('date', axis=1, inplace=True)\n",
        "    \n",
        "    return df\n",
        "\n",
        "# Dates Features for Train, Test\n",
        "train, test = date_features(train), date_features(test)"
      ],
      "execution_count": 253,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
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        "id": "uANompf00qHJ",
        "outputId": "0c08534d-1d9a-4372-dc76-2ce9bb210e12"
      },
      "source": [
        "train.head()"
      ],
      "execution_count": 254,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>store</th>\n",
              "      <th>item code</th>\n",
              "      <th>sales</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>day^year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>-5.864207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>20.028234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>14</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>22.681333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>24.180730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>25.138418</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   store  item code  sales    year  ...  dayofyear  dayofweek  weekofyear   day^year\n",
              "0      1          1     13  2016.0  ...        1.0        4.0        53.0  -5.864207\n",
              "1      1          1     11  2016.0  ...       32.0        0.0         5.0  20.028234\n",
              "2      1          1     14  2016.0  ...       61.0        1.0         9.0  22.681333\n",
              "3      1          1     13  2016.0  ...       92.0        4.0        13.0  24.180730\n",
              "4      1          1     10  2016.0  ...      122.0        6.0        17.0  25.138418\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 254
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mzuf03QgmgcP"
      },
      "source": [
        "daily_avg = train['daily_avg']  = train.groupby(['item code','store','dayofweek'])['sales'].transform('mean')\n",
        "train['monthly_avg'] = train.groupby(['item code','store','month'])['sales'].transform('mean')\n",
        "train = train.dropna()\n",
        "\n",
        "# Average sales for Day_of_week = d per Item,Store\n",
        "daymonth_avg = train.groupby(['item code','store','dayofweek'])['sales'].mean().reset_index()\n",
        "# Average sales for Month = m per Item,Store\n",
        "monthly_avg = train.groupby(['item code','store','month'])['sales'].mean().reset_index()"
      ],
      "execution_count": 255,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "xhie7SL90w0Y",
        "outputId": "1dd3e8bc-f4e3-4d97-edca-8c996121152a"
      },
      "source": [
        "\n",
        "train.head()\n"
      ],
      "execution_count": 256,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>store</th>\n",
              "      <th>item code</th>\n",
              "      <th>sales</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>day^year</th>\n",
              "      <th>daily_avg</th>\n",
              "      <th>monthly_avg</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>-5.864207</td>\n",
              "      <td>17.509579</td>\n",
              "      <td>16.025806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>20.028234</td>\n",
              "      <td>19.761538</td>\n",
              "      <td>16.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>14</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>22.681333</td>\n",
              "      <td>20.846743</td>\n",
              "      <td>19.212903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>24.180730</td>\n",
              "      <td>17.509579</td>\n",
              "      <td>20.286667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>25.138418</td>\n",
              "      <td>19.114943</td>\n",
              "      <td>21.838710</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   store  item code  sales  ...   day^year  daily_avg  monthly_avg\n",
              "0      1          1     13  ...  -5.864207  17.509579    16.025806\n",
              "1      1          1     11  ...  20.028234  19.761538    16.333333\n",
              "2      1          1     14  ...  22.681333  20.846743    19.212903\n",
              "3      1          1     13  ...  24.180730  17.509579    20.286667\n",
              "4      1          1     10  ...  25.138418  19.114943    21.838710\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 256
        }
      ]
    },
    {
      "cell_type": "code",
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        },
        "id": "iBGTYa50081K",
        "outputId": "c05dd83e-f4e1-4be7-c7d6-751ff9407285"
      },
      "source": [
        "test.head()"
      ],
      "execution_count": 257,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>store</th>\n",
              "      <th>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>day^year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>-7.330258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>32</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>25.035293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>61</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>28.351666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>92</td>\n",
              "      <td>2</td>\n",
              "      <td>14</td>\n",
              "      <td>30.225912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>122</td>\n",
              "      <td>4</td>\n",
              "      <td>18</td>\n",
              "      <td>31.423022</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   store  item code  year  month  ...  dayofyear  dayofweek  weekofyear   day^year\n",
              "0      1          1  2020      1  ...          1          2           1  -7.330258\n",
              "1      1          1  2020      2  ...         32          5           5  25.035293\n",
              "2      1          1  2020      3  ...         61          6           9  28.351666\n",
              "3      1          1  2020      4  ...         92          2          14  30.225912\n",
              "4      1          1  2020      5  ...        122          4          18  31.423022\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 257
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "3vqFv7BHmge1",
        "outputId": "f2c5eea1-1436-4667-cae4-f96aea1dc1e6"
      },
      "source": [
        "# def merge(df1, df2, col,col_name):\n",
        "#   df1 =pd.merge(df1, df2, how='left', on=None, left_on=col, right_on=col,left_index=False, right_index=False, sort=True,copy=True, indicator=False)\n",
        "#   df1 = df1.rename(columns={'sales':col_name})\n",
        "#   return df1\n",
        "\n",
        "# # Add Daily_avg and Monthly_avg features to test \n",
        "# # test = merge(test, daily_avg,['item','store','dayofweek'],['daily_avg'])\n",
        "# # test = merge(test, monthly_avg,['item','store','month'],['monthly_avg'])\n",
        "\n",
        "# # Sales Rolling mean sequence per item \n",
        "# rolling_10 = train.groupby(['item'])['sales'].rolling(10).mean().reset_index().drop('level_1', axis=1)\n",
        "# train['rolling_mean'] = rolling_10['sales'] \n",
        "\n",
        "# # 90 last days of training rolling mean sequence added to test data\n",
        "# rolling_last90 = train.groupby(['item','store'])['rolling_mean'].tail(90).copy()\n",
        "# test['rolling_mean'] = rolling_last90.reset_index().drop('index', axis=1)\n",
        "\n",
        "# # Shifting rolling mean 3 months\n",
        "# train['rolling_mean'] = train.groupby(['item'])['rolling_mean'].shift(90) # Create a feature with rolling mean of day - 90\n",
        "# train.head()"
      ],
      "execution_count": 127,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>store</th>\n",
              "      <th>item</th>\n",
              "      <th>sales</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>day^year</th>\n",
              "      <th>daily_avg</th>\n",
              "      <th>monthly_avg</th>\n",
              "      <th>rolling_mean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2013</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-4.764668</td>\n",
              "      <td>18.168582</td>\n",
              "      <td>13.709677</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>2013</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1.222622</td>\n",
              "      <td>18.793103</td>\n",
              "      <td>13.709677</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>14</td>\n",
              "      <td>2013</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4.246245</td>\n",
              "      <td>19.452107</td>\n",
              "      <td>13.709677</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2013</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>6.186505</td>\n",
              "      <td>21.015326</td>\n",
              "      <td>13.709677</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2013</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>7.581575</td>\n",
              "      <td>22.973180</td>\n",
              "      <td>13.709677</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   store  item  sales  year  ...  day^year  daily_avg  monthly_avg  rolling_mean\n",
              "0      1     1     13  2013  ... -4.764668  18.168582    13.709677           NaN\n",
              "1      1     1     11  2013  ...  1.222622  18.793103    13.709677           NaN\n",
              "2      1     1     14  2013  ...  4.246245  19.452107    13.709677           NaN\n",
              "3      1     1     13  2013  ...  6.186505  21.015326    13.709677           NaN\n",
              "4      1     1     10  2013  ...  7.581575  22.973180    13.709677           NaN\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "Yddw2y8fmghJ",
        "outputId": "16348c43-b38e-4618-b83c-3ff4920d87cc"
      },
      "source": [
        "test.head(20000)"
      ],
      "execution_count": 258,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>store</th>\n",
              "      <th>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>day</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>day^year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>-7.330258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>32</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>25.035293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>61</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>28.351666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>92</td>\n",
              "      <td>2</td>\n",
              "      <td>14</td>\n",
              "      <td>30.225912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>122</td>\n",
              "      <td>4</td>\n",
              "      <td>18</td>\n",
              "      <td>31.423022</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19995</th>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>16</td>\n",
              "      <td>16</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>20.828230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19996</th>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>17</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>21.227703</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19997</th>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>21.598366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19998</th>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>19</td>\n",
              "      <td>19</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>21.943774</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19999</th>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>22.266881</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20000 rows × 9 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       store  item code  year  ...  dayofweek  weekofyear   day^year\n",
              "0          1          1  2020  ...          2           1  -7.330258\n",
              "1          1          1  2020  ...          5           5  25.035293\n",
              "2          1          1  2020  ...          6           9  28.351666\n",
              "3          1          1  2020  ...          2          14  30.225912\n",
              "4          1          1  2020  ...          4          18  31.423022\n",
              "...      ...        ...   ...  ...        ...         ...        ...\n",
              "19995      3         23  2020  ...          3           3  20.828230\n",
              "19996      3         23  2020  ...          4           3  21.227703\n",
              "19997      3         23  2020  ...          5           3  21.598366\n",
              "19998      3         23  2020  ...          6           3  21.943774\n",
              "19999      3         23  2020  ...          0           4  22.266881\n",
              "\n",
              "[20000 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 258
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3KEMvTUfmgjM"
      },
      "source": [
        "# Clean features highly correlated to each others\n",
        "# for df in [train, test]:\n",
        "train.drop(['day^year', \n",
        "              'weekofyear',\n",
        "              'daily_avg',\n",
        "              'day',\n",
        "              'store',],\n",
        "              axis=1, \n",
        "              inplace=True)\n",
        "    \n"
      ],
      "execution_count": 259,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "3_JhAQy99UXx",
        "outputId": "0f0e6100-4ad1-4fa6-8358-bcda1aa39f61"
      },
      "source": [
        "train.head()"
      ],
      "execution_count": 260,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item code</th>\n",
              "      <th>sales</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>monthly_avg</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>16.025806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>16.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>14</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.212903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>20.286667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>21.838710</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   item code  sales    year  month  dayofyear  dayofweek  monthly_avg\n",
              "0          1     13  2016.0    1.0        1.0        4.0    16.025806\n",
              "1          1     11  2016.0    2.0       32.0        0.0    16.333333\n",
              "2          1     14  2016.0    3.0       61.0        1.0    19.212903\n",
              "3          1     13  2016.0    4.0       92.0        4.0    20.286667\n",
              "4          1     10  2016.0    5.0      122.0        6.0    21.838710"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 260
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IOKfchl_9X-E"
      },
      "source": [
        "test.drop(['day^year', \n",
        "              'weekofyear',\n",
        "              'day',\n",
        "              'store',],\n",
        "              axis=1, \n",
        "              inplace=True)"
      ],
      "execution_count": 261,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "NO8687ZE9YAx",
        "outputId": "5c5b222b-157b-4861-97c6-3f1077162502"
      },
      "source": [
        "test.head()"
      ],
      "execution_count": 262,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>32</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>3</td>\n",
              "      <td>61</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>4</td>\n",
              "      <td>92</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>5</td>\n",
              "      <td>122</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   item code  year  month  dayofyear  dayofweek\n",
              "0          1  2020      1          1          2\n",
              "1          1  2020      2         32          5\n",
              "2          1  2020      3         61          6\n",
              "3          1  2020      4         92          2\n",
              "4          1  2020      5        122          4"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 262
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ymsErLC9YDF"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j5b_zCPd9YFp"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o689xN76mglM"
      },
      "source": [
        "# Features Scaling (except sales)\n",
        "# sales_series, id_series = train['sales'], test['id']\n",
        "# # Features Scaling\n",
        "# train = (train - train.mean()) / train.std()\n",
        "# test = (test - test.mean()) / test.std()\n",
        "# # Retrieve actual Sales values and ID\n",
        "# train['sales'] = sales_series\n",
        "# test['id'] = id_series\n",
        "\n"
      ],
      "execution_count": 84,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "-XClk-vu96Dp",
        "outputId": "8cd18198-0ea6-4dd6-e986-edb0bb013980"
      },
      "source": [
        "train.head()"
      ],
      "execution_count": 263,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item code</th>\n",
              "      <th>sales</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>monthly_avg</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>16.025806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>16.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>14</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19.212903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>20.286667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>21.838710</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   item code  sales    year  month  dayofyear  dayofweek  monthly_avg\n",
              "0          1     13  2016.0    1.0        1.0        4.0    16.025806\n",
              "1          1     11  2016.0    2.0       32.0        0.0    16.333333\n",
              "2          1     14  2016.0    3.0       61.0        1.0    19.212903\n",
              "3          1     13  2016.0    4.0       92.0        4.0    20.286667\n",
              "4          1     10  2016.0    5.0      122.0        6.0    21.838710"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 263
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "5ThMC6Ci99da",
        "outputId": "be1b5325-4462-44c4-b8cb-c7b8ca62af3c"
      },
      "source": [
        "test.head()"
      ],
      "execution_count": 264,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>32</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>3</td>\n",
              "      <td>61</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>4</td>\n",
              "      <td>92</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>5</td>\n",
              "      <td>122</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   item code  year  month  dayofyear  dayofweek\n",
              "0          1  2020      1          1          2\n",
              "1          1  2020      2         32          5\n",
              "2          1  2020      3         61          6\n",
              "3          1  2020      4         92          2\n",
              "4          1  2020      5        122          4"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 264
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oTPLZUMh-d6x"
      },
      "source": [
        "import xgboost as xgb"
      ],
      "execution_count": 90,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AfPew13ymgna",
        "outputId": "dbf243cf-a6c6-40aa-be67-9de28278f74d"
      },
      "source": [
        "# Training Data\n",
        "X_train = train.drop('sales', axis=1).dropna()\n",
        "y_train = train['sales']\n",
        "# Test Data\n",
        "test.sort_values(by=['item code'], inplace=True)\n",
        "# X_test = test.drop('item code', axis=1)\n",
        "#df = train\n",
        "df_train = train.copy()\n",
        "\n",
        "# Train Test Split\n",
        "X_train , X_test ,y_train, y_test = train_test_split(df_train.drop('sales',axis=1),df_train.pop('sales'), random_state=123, test_size=0.2)\n",
        "\n",
        "# XGB Model\n",
        "matrix_train = xgb.DMatrix(X_train, label = y_train)\n",
        "matrix_test = xgb.DMatrix(X_test, label = y_test)\n",
        "\n",
        "# Run XGB \n",
        "model = xgb.train(params={'objective':'reg:linear','eval_metric':'mae'}\n",
        "                ,dtrain = matrix_train, num_boost_round = 500, \n",
        "                early_stopping_rounds = 20, evals = [(matrix_test,'test')],)"
      ],
      "execution_count": 265,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[00:01:44] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
            "[0]\ttest-mae:36.2639\n",
            "Will train until test-mae hasn't improved in 20 rounds.\n",
            "[1]\ttest-mae:25.4701\n",
            "[2]\ttest-mae:18.3672\n",
            "[3]\ttest-mae:14.0667\n",
            "[4]\ttest-mae:11.6155\n",
            "[5]\ttest-mae:10.2734\n",
            "[6]\ttest-mae:9.53663\n",
            "[7]\ttest-mae:9.11762\n",
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            "[11]\ttest-mae:8.31908\n",
            "[12]\ttest-mae:8.15298\n",
            "[13]\ttest-mae:8.04199\n",
            "[14]\ttest-mae:7.93128\n",
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            "[16]\ttest-mae:7.69721\n",
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            "[421]\ttest-mae:5.71936\n",
            "[422]\ttest-mae:5.71857\n",
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            "[427]\ttest-mae:5.71887\n",
            "[428]\ttest-mae:5.71867\n",
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            "[430]\ttest-mae:5.7179\n",
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            "[455]\ttest-mae:5.71282\n",
            "[456]\ttest-mae:5.71292\n",
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            "[461]\ttest-mae:5.71097\n",
            "[462]\ttest-mae:5.71105\n",
            "[463]\ttest-mae:5.71059\n",
            "[464]\ttest-mae:5.71004\n",
            "[465]\ttest-mae:5.70998\n",
            "[466]\ttest-mae:5.70989\n",
            "[467]\ttest-mae:5.70958\n",
            "[468]\ttest-mae:5.70943\n",
            "[469]\ttest-mae:5.70889\n",
            "[470]\ttest-mae:5.7082\n",
            "[471]\ttest-mae:5.70829\n",
            "[472]\ttest-mae:5.70835\n",
            "[473]\ttest-mae:5.70828\n",
            "[474]\ttest-mae:5.70829\n",
            "[475]\ttest-mae:5.70824\n",
            "[476]\ttest-mae:5.70835\n",
            "[477]\ttest-mae:5.70833\n",
            "[478]\ttest-mae:5.70821\n",
            "[479]\ttest-mae:5.70826\n",
            "[480]\ttest-mae:5.70792\n",
            "[481]\ttest-mae:5.70798\n",
            "[482]\ttest-mae:5.70796\n",
            "[483]\ttest-mae:5.70777\n",
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            "[486]\ttest-mae:5.7077\n",
            "[487]\ttest-mae:5.70768\n",
            "[488]\ttest-mae:5.70763\n",
            "[489]\ttest-mae:5.7077\n",
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            "[492]\ttest-mae:5.7072\n",
            "[493]\ttest-mae:5.7071\n",
            "[494]\ttest-mae:5.70634\n",
            "[495]\ttest-mae:5.7065\n",
            "[496]\ttest-mae:5.70649\n",
            "[497]\ttest-mae:5.70662\n",
            "[498]\ttest-mae:5.70639\n",
            "[499]\ttest-mae:5.70642\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "oXtDf5-pEnDM",
        "outputId": "7c397412-e12e-4da0-b054-357a4190d417"
      },
      "source": [
        "test.head()"
      ],
      "execution_count": 266,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>593</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>54</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>594</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>55</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>595</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>596</th>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>57</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     item code  year  month  dayofyear  dayofweek\n",
              "0            1  2020      1          1          2\n",
              "593          1  2020      2         54          6\n",
              "594          1  2020      2         55          0\n",
              "595          1  2020      2         56          1\n",
              "596          1  2020      2         57          2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 266
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "uKh4cIX2SXCo",
        "outputId": "e6c19ba4-e6ec-450f-da16-6e1f9754a9af"
      },
      "source": [
        "X_test.head()"
      ],
      "execution_count": 267,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "        vertical-align: top;\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>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>monthly_avg</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>534104</th>\n",
              "      <td>30</td>\n",
              "      <td>2018.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>38.851064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>592708</th>\n",
              "      <td>33</td>\n",
              "      <td>2018.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>355.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>44.845161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9456</th>\n",
              "      <td>1</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>328.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>17.486667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>639449</th>\n",
              "      <td>36</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>351.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>58.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137180</th>\n",
              "      <td>8</td>\n",
              "      <td>2016.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>232.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>62.735484</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        item code    year  month  dayofyear  dayofweek  monthly_avg\n",
              "534104         30  2018.0    2.0       38.0        2.0    38.851064\n",
              "592708         33  2018.0   12.0      355.0        4.0    44.845161\n",
              "9456            1  2016.0   11.0      328.0        2.0    17.486667\n",
              "639449         36  2016.0   12.0      351.0        4.0    58.800000\n",
              "137180          8  2016.0    8.0      232.0        4.0    62.735484"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 267
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yHgXH433UJE9"
      },
      "source": [
        "matrix_test = xgb.DMatrix(X_test)"
      ],
      "execution_count": 268,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TsKe7N6JmgqI"
      },
      "source": [
        "y_pred = model.predict(matrix_test)"
      ],
      "execution_count": 269,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fql9LJV3mgs7"
      },
      "source": [
        "predictions = [round(value) for value in y_pred]\n"
      ],
      "execution_count": 270,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_G4MciCaKGlu",
        "outputId": "7110df57-0506-4333-ece5-9e0e25a1d81d"
      },
      "source": [
        "print(predictions)"
      ],
      "execution_count": 271,
      "outputs": [
        {
          "output_type": "stream",
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46, 114, 45, 79, 16, 52, 63, 60, 21, 22, 111, 57, 14, 32, 66, 40, 58, 14, 63, 67, 21, 85, 63, 51, 105, 102, 47, 45, 57, 57, 40, 74, 82, 25, 20, 13, 98, 27, 75, 42, 20, 92, 77, 10, 8, 25, 41, 53, 97, 99, 46, 57, 98, 25, 34, 90, 40, 18, 54, 27, 68, 48, 51, 37, 17, 29, 31, 31, 17, 22, 27, 38, 42, 41, 70, 18, 26, 82, 43, 61, 11, 27, 41, 68, 67, 26, 51, 32, 30, 22, 91, 104, 24, 59, 33, 89, 27, 19, 34, 28, 57, 34, 22, 35, 65, 27, 59, 35, 25, 51, 62, 36, 22, 62, 75, 20, 45, 50, 52, 57, 94, 43, 49, 21, 58, 71, 75, 55, 99, 28, 45, 121, 107, 15, 23, 148, 80, 44, 77, 26, 16, 36, 68, 105, 64, 21, 54, 78, 34, 29, 30, 64, 35, 27, 23, 35, 30, 49, 19, 29, 21, 31, 86, 15, 50, 35, 53, 58, 74, 23, 30, 60, 69, 79, 53, 32, 64, 112, 76, 25, 21, 48, 131, 140, 6, 73, 34, 58, 68, 21, 63, 30, 132, 35, 24, 91, 49, 75, 88, 36, 69, 41, 59, 113, 87, 71, 50, 100, 83, 57, 27, 19, 65, 88, 40, 47, 58, 46, 51, 25, 76, 63, 86, 29, 47, 24, 73, 23, 58, 34, 25, 60, 92, 99, 79, 29, 56, 40, 58, 20, 79, 53, 68, 95, 21, 74, 78, 30, 21, 47, 23, 20, 60, 59, 16, 38, 40, 51, 42, 63, 14, 57, 56, 22, 54, 64, 33, 65, 40, 41, 66, 91, 88, 41, 75, 16, 54, 84, 12, 92, 69, 28, 59, 88, 97, 73, 21, 38, 93, 74, 120, 48, 71, 76, 38, 63, 76, 50, 31, 65, 23, 48, 63, 88, 22, 70, 45, 13, 33, 79, 16, 40, 43, 16, 37, 49, 53, 88, 80, 79, 55, 63, 50, 37, 33, 56, 29, 18, 37, 77, 19, 71, 45, 68, 40, 28, 30, 73, 52, 18, 69, 20, 38, 32, 79, 24, 102, 84, 74, 14, 16, 25, 64, 141, 33, 15, 11, 53, 69, 125, 29, 29, 26, 122, 86, 67, 53, 37, 48, 12, 16, 64, 58, 59, 78, 102, 43, 23, 57, 32, 46, 91, 64, 85, 53, 110, 31, 52, 26, 43, 24, 27, 17, 73, 77, 50, 45, 50, 48, 33, 9, 67, 115, 59, 34, 21, 54, 68, 53, 79, 62, 78, 107, 19, 99, 41, 72, 41, 97, 70, 37, 49, 27, 109, 39, 25, 43, 67, 39, 40, 48, 66, 19, 18, 67, 18, 105, 41, 75, 42, 86, 50, 64, 42, 15, 33, 34, 46, 76, 52, 49, 37, 31, 34, 20, 26, 45, 41, 19, 45, 32, 59, 18, 36, 16, 58, 24, 36, 82, 81, 35, 43, 69, 82, 95, 72, 73, 28, 47, 77, 81, 30, 47, 26, 57, 22, 66, 21, 44, 27, 45, 107, 63, 30, 51, 59, 54, 26, 68, 85, 32, 17, 121, 14, 28, 43, 36, 81, 43, 56, 21, 66, 84, 48, 26, 40, 46, 69, 29, 24, 69, 63, 128, 28, 53, 80, 79, 48, 71, 37, 19, 52, 59, 66, 47, 25, 57, 57, 24, 97, 41, 30, 27, 51, 57, 24, 47, 37, 50, 19, 18, 99, 55, 67, 18, 61, 58, 22, 20, 45, 30, 60, 29, 89, 61, 58, 96, 59, 40, 115, 95, 83, 35, 51, 72, 61, 13, 76, 26, 45, 63, 68, 20, 20, 50, 43, 30, 45, 60, 83, 20, 27, 45, 36, 74, 42, 50, 24, 31, 99, 26, 37, 18, 38, 62, 38, 75, 39, 29, 68, 43, 21, 41, 47, 25, 68, 86, 16, 59, 55, 32, 121, 29, 97, 22, 31, 109, 33, 72, 64, 59, 29, 58, 28, 97, 59, 41, 59, 87, 25, 47, 15, 70, 31, 53, 99, 74, 37, 71, 37, 19, 21, 55, 17, 12, 70, 32, 24, 50, 22, 26, 44, 43, 69, 59, 57, 67, 43, 58, 80, 70, 64, 15, 50, 40, 66, 46, 119, 65, 116, 56, 46, 28, 38, 80, 31, 24, 55, 36, 33, 11, 23, 27, 17, 47, 29, 81, 36, 52, 71, 88, 67, 46, 51, 23, 33, 24, 18, 38, 44, 40, 34, 78, 57, 35, 38, 104, 70, 18, 47, 76, 33, 35, 32, 36, 52, 66, 71, 21, 55, 90, 40, 105, 88, 27, 40, 25, 32, 49, 36, 59, 61, 97, 29, 66, 93, 77, 34, 50, 59, 95, 80, 75, 47, 50, 40, 21, 44, 47, 77, 85, 114, 101, 25, 24, 60, 48, 80, 44, 58, 94, 91, 21, 45, 36, 54, 65, 77, 80, 36, 60, 77, 67, 58, 59, 58, 24, 62, 40, 59, 46, 66, 75, 130, 59, 97, 65, 103, 52, 81, 35, 123, 150, 27, 44, 94, 20, 25, 17, 26, 35, 44, 27, 48, 29, 33, 39, 96, 89, 127, 33, 26, 18, 19, 14, 99, 42, 37, 33, 55, 12, 26, 172, 29, 50, 56, 72, 67, 33, 33, 35, 45, 31, 54, 18, 13, 53, 32, 34, 25, 36, 33, 34, 65, 26, 11, 56, 26, 60, 51, 13, 64, 48, 88, 26, 63, 41, 67, 88, 98, 23, 20, 66, 73, 52, 35, 35, 64, 57, 22, 39, 18, 72, 70, 61, 90, 31, 30, 52, 24, 16, 51, 35, 34, 65, 91, 109, 34, 57, 53, 43, 88, 42, 35, 74, 50, 119, 10, 70, 46, 36, 21, 63, 107, 84, 24, 99, 93, 33, 50, 84, 52, 71, 60, 32, 70, 83, 24, 14, 76, 36, 44, 41, 43, 13, 99, 50, 81, 30, 52, 59, 45, 92, 32, 20, 29, 78, 86, 71, 80, 31, 33, 93, 19, 20, 66, 65, 32, 32, 21, 54, 39, 10, 75, 14, 67, 26, 70, 87, 47, 20, 53, 90, 18, 65, 54, 49, 58, 38, 29, 79, 42, 92, 44, 48, 107, 39, 62, 55, 39, 13, 66, 20, 39, 23, 15, 41, 67, 23, 37, 28, 15, 23, 43, 76, 79, 34, 19, 32, 14, 27, 38, 36, 88, 64, 15, 35, 155, 47, 30, 97, 40, 70, 50, 46, 33, 94, 42, 68, 26, 16, 40, 59, 71, 36, 30, 105, 46, 84, 83, 60, 22, 69, 21, 27, 102, 62, 52, 16, 62, 54, 70, 69, 98, 36, 27, 29, 89, 111, 53, 63, 30, 37, 108, 17, 109, 44, 110, 34, 96, 39, 53, 104, 122, 43, 20, 40, 61, 32, 133, 15, 90, 48, 26, 87, 72, 41, 33, 68, 15, 64, 62, 27, 51, 51, 66, 47, 29, 17, 47, 74, 40, 31, 51, 146, 26, 19, 82, 21, 40, 139, 106, 24, 27, 48, 82]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4dOOUmP7mgyE"
      },
      "source": [
        "import pickle\n",
        "filename = 'finalized_model.sav'\n",
        "pickle.dump(model, open(filename, 'wb'))"
      ],
      "execution_count": 272,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NeZ0nFkkmg55",
        "outputId": "e9c9e933-003e-455f-99cf-0621fbbe9998"
      },
      "source": [
        "model = pickle.load(open( \"finalized_model.sav\", \"rb\"))"
      ],
      "execution_count": 274,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[00:09:34] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-ga6zofQWpb2"
      },
      "source": [
        "data = {\"item code\":8,\"year\": 2016, \"month\":8,\t\"dayofyear\":232,\t\"dayofweek\":4,\t\"monthly_avg\":62.7}"
      ],
      "execution_count": 282,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lq064DhaX-r2"
      },
      "source": [
        "df = pd.DataFrame(data, index = [0])"
      ],
      "execution_count": 283,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D_K6EzBLXsAK"
      },
      "source": [
        "cols=[\"item code\",\"year\", \"month\",\t\"dayofyear\",\t\"dayofweek\",\t\"monthly_avg\"]\n",
        "df = df[cols]"
      ],
      "execution_count": 284,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "PMe7-PcIY1n3",
        "outputId": "9614c653-b63d-468c-ef7e-8931f2d32f94"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 285,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item code</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofweek</th>\n",
              "      <th>monthly_avg</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>2016</td>\n",
              "      <td>8</td>\n",
              "      <td>232</td>\n",
              "      <td>4</td>\n",
              "      <td>62.7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   item code  year  month  dayofyear  dayofweek  monthly_avg\n",
              "0          8  2016      8        232          4         62.7"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 285
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i3l9r9UgZG8g"
      },
      "source": [
        "matrix_test = xgb.DMatrix(df)"
      ],
      "execution_count": 286,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A_vKG4NGVhsO"
      },
      "source": [
        "sales = model.predict(matrix_test)"
      ],
      "execution_count": 287,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BLFERgoZmg83",
        "outputId": "9a888411-5bff-4df3-d1d9-fd31c43e0a4b"
      },
      "source": [
        "val = [round(value) for value in sales]\n",
        "print(val[0])"
      ],
      "execution_count": 288,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "42\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zvbTcGwUmg_d"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lr9NacV_mhCQ"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ISwz7SJxmhEm"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "49BNoVdbmhHV"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Cmv0b1TmhJm"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qhgbpTXBmhLu"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hypiUH54mhNy"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Znz3th5WmhPl"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9adlem6QmhR9"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "09cprM-HmhWH"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5OpLg_ZAmhYu"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "knYVfSqEmhbi"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eUbJ43BEmhd7"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EMeJnDVsmhgi"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F7hyFgEEmhju"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}