03-durations-preprocess.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_train = pd.read_feather('joined_train_before_durations.fth')\n",
    "joined_test = pd.read_feather('joined_test_before_durations.fth')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Paso StateHoliday a booleana"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "StateHoliday\n",
       "0    986159\n",
       "a     20260\n",
       "b      6690\n",
       "c      4100\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_train['StateHoliday'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_train"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "a = public holiday, b = Easter holiday, c = Christmas, 0 = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_train['StateHoliday_bool'] = joined_train.StateHoliday!='0'\n",
    "joined_test['StateHoliday_bool'] = joined_test.StateHoliday!='0'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Durations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Agrega columnas con \"antes\" y \"despues\" de eventos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = [\"Date\", \"Store\", \"Promo\", \"StateHoliday_bool\", \"SchoolHoliday\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class elapsed(object):\n",
    "    def __init__(self, fld):\n",
    "        self.fld = fld\n",
    "        self.last = pd.to_datetime(np.nan)\n",
    "        self.last_store = 0\n",
    "        \n",
    "    def get(self, row):\n",
    "        if row.Store != self.last_store:\n",
    "            self.last = pd.to_datetime(np.nan)\n",
    "            self.last_store = row.Store\n",
    "        if (row[self.fld]): self.last = row.Date\n",
    "        return row.Date-self.last"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = joined_train[columns]\n",
    "df_test = joined_test[columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-07-31</td>\n",
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       "      <th>2</th>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "        Date  Store  Promo  StateHoliday_bool  SchoolHoliday\n",
       "0 2015-07-31      1      1              False              1\n",
       "1 2015-07-31      2      1              False              1\n",
       "2 2015-07-31      3      1              False              1\n",
       "3 2015-07-31      4      1              False              1\n",
       "4 2015-07-31      5      1              False              1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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   "outputs": [
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       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-09-17</td>\n",
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       "      <th>1</th>\n",
       "      <td>2015-09-17</td>\n",
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       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-09-17</td>\n",
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       "      <td>False</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
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      "text/plain": [
       "        Date  Store  Promo  StateHoliday_bool  SchoolHoliday\n",
       "0 2015-09-17      1      1              False              0\n",
       "1 2015-09-17      3      1              False              0\n",
       "2 2015-09-17      7      1              False              0\n",
       "3 2015-09-17      8      1              False              0\n",
       "4 2015-09-17      9      1              False              0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_elapsed(df, fld, prefix):\n",
    "    sh_el = elapsed(fld)\n",
    "    df[prefix+fld] = df.apply(sh_el.get, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>AfterSchoolHoliday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1016095</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1014980</th>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1013865</th>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1012750</th>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1011635</th>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "1016095 2013-01-01      1      0               True              1   \n",
       "1014980 2013-01-02      1      0              False              1   \n",
       "1013865 2013-01-03      1      0              False              1   \n",
       "1012750 2013-01-04      1      0              False              1   \n",
       "1011635 2013-01-05      1      0              False              1   \n",
       "\n",
       "        AfterSchoolHoliday  \n",
       "1016095             0 days  \n",
       "1014980             0 days  \n",
       "1013865             0 days  \n",
       "1012750             0 days  \n",
       "1011635             0 days  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fld = 'SchoolHoliday'\n",
    "df_train = df_train.sort_values(['Store', 'Date'])\n",
    "add_elapsed(df_train, fld, 'After')\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>AfterSchoolHoliday</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40232</th>\n",
       "      <td>2015-08-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
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       "    <tr>\n",
       "      <th>39376</th>\n",
       "      <td>2015-08-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
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       "    <tr>\n",
       "      <th>38520</th>\n",
       "      <td>2015-08-03</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37664</th>\n",
       "      <td>2015-08-04</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36808</th>\n",
       "      <td>2015-08-05</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "40232 2015-08-01      1      0              False              1   \n",
       "39376 2015-08-02      1      0              False              1   \n",
       "38520 2015-08-03      1      1              False              1   \n",
       "37664 2015-08-04      1      1              False              1   \n",
       "36808 2015-08-05      1      1              False              1   \n",
       "\n",
       "      AfterSchoolHoliday  \n",
       "40232             0 days  \n",
       "39376             0 days  \n",
       "38520             0 days  \n",
       "37664             0 days  \n",
       "36808             0 days  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test = df_test.sort_values(['Store', 'Date'])\n",
    "add_elapsed(df_test, fld, 'After')\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>AfterSchoolHoliday</th>\n",
       "      <th>BeforeSchoolHoliday</th>\n",
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       "      <th>0</th>\n",
       "      <td>2015-07-31</td>\n",
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       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
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       "    <tr>\n",
       "      <th>1115</th>\n",
       "      <td>2015-07-30</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2230</th>\n",
       "      <td>2015-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3345</th>\n",
       "      <td>2015-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4460</th>\n",
       "      <td>2015-07-27</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "0    2015-07-31      1      1              False              1   \n",
       "1115 2015-07-30      1      1              False              1   \n",
       "2230 2015-07-29      1      1              False              1   \n",
       "3345 2015-07-28      1      1              False              1   \n",
       "4460 2015-07-27      1      1              False              1   \n",
       "\n",
       "     AfterSchoolHoliday BeforeSchoolHoliday  \n",
       "0                0 days              0 days  \n",
       "1115             0 days              0 days  \n",
       "2230             0 days              0 days  \n",
       "3345             0 days              0 days  \n",
       "4460             0 days              0 days  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = df_train.sort_values(['Store', 'Date'], ascending=[True, False])\n",
    "add_elapsed(df_train, fld, 'Before')\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>AfterSchoolHoliday</th>\n",
       "      <th>BeforeSchoolHoliday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-09-17</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>13 days</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856</th>\n",
       "      <td>2015-09-16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>12 days</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1712</th>\n",
       "      <td>2015-09-15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>11 days</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2568</th>\n",
       "      <td>2015-09-14</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>10 days</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3424</th>\n",
       "      <td>2015-09-13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>9 days</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "0    2015-09-17      1      1              False              0   \n",
       "856  2015-09-16      1      1              False              0   \n",
       "1712 2015-09-15      1      1              False              0   \n",
       "2568 2015-09-14      1      1              False              0   \n",
       "3424 2015-09-13      1      0              False              0   \n",
       "\n",
       "     AfterSchoolHoliday BeforeSchoolHoliday  \n",
       "0               13 days                 NaT  \n",
       "856             12 days                 NaT  \n",
       "1712            11 days                 NaT  \n",
       "2568            10 days                 NaT  \n",
       "3424             9 days                 NaT  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test = df_test.sort_values(['Store', 'Date'], ascending=[True, False])\n",
    "add_elapsed(df_test, fld, 'Before')\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "fld = 'StateHoliday_bool'\n",
    "df_train = df_train.sort_values(['Store', 'Date'])\n",
    "add_elapsed(df_train, fld, 'After')\n",
    "df_train = df_train.sort_values(['Store', 'Date'], ascending=[True, False])\n",
    "add_elapsed(df_train, fld, 'Before')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "fld = 'StateHoliday_bool'\n",
    "df_test = df_test.sort_values(['Store', 'Date'])\n",
    "add_elapsed(df_test, fld, 'After')\n",
    "df_test = df_test.sort_values(['Store', 'Date'], ascending=[True, False])\n",
    "add_elapsed(df_test, fld, 'Before')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "fld = 'Promo'\n",
    "df_train = df_train.sort_values(['Store', 'Date'])\n",
    "add_elapsed(df_train, fld, 'After')\n",
    "df_train = df_train.sort_values(['Store', 'Date'], ascending=[True, False])\n",
    "add_elapsed(df_train, fld, 'Before')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "fld = 'Promo'\n",
    "df_test = df_test.sort_values(['Store', 'Date'])\n",
    "add_elapsed(df_test, fld, 'After')\n",
    "df_test = df_test.sort_values(['Store', 'Date'], ascending=[True, False])\n",
    "add_elapsed(df_test, fld, 'Before')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>9</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index       Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "0      0 2015-07-31      1      1              False              1   \n",
       "1      1 2015-07-30      1      1              False              1   \n",
       "2      2 2015-07-29      1      1              False              1   \n",
       "3      3 2015-07-28      1      1              False              1   \n",
       "4      4 2015-07-27      1      1              False              1   \n",
       "5      5 2015-07-26      1      0              False              0   \n",
       "6      6 2015-07-25      1      0              False              0   \n",
       "7      7 2015-07-24      1      0              False              0   \n",
       "8      8 2015-07-23      1      0              False              0   \n",
       "9      9 2015-07-22      1      0              False              0   \n",
       "\n",
       "   AfterSchoolHoliday  BeforeSchoolHoliday  AfterStateHoliday_bool  \\\n",
       "0                   0                    0                      57   \n",
       "1                   0                    0                      56   \n",
       "2                   0                    0                      55   \n",
       "3                   0                    0                      54   \n",
       "4                   0                    0                      53   \n",
       "5                 107                   -1                      52   \n",
       "6                 106                   -2                      51   \n",
       "7                 105                   -3                      50   \n",
       "8                 104                   -4                      49   \n",
       "9                 103                   -5                      48   \n",
       "\n",
       "   BeforeStateHoliday_bool  AfterPromo  BeforePromo  \n",
       "0                        0           0            0  \n",
       "1                        0           0            0  \n",
       "2                        0           0            0  \n",
       "3                        0           0            0  \n",
       "4                        0           0            0  \n",
       "5                        0           9           -1  \n",
       "6                        0           8           -2  \n",
       "7                        0           7           -3  \n",
       "8                        0           6           -4  \n",
       "9                        0           5           -5  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = df_train.set_index(\"Date\")\n",
    "df_test = df_test.set_index(\"Date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0 days</td>\n",
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       "      <td>0 days</td>\n",
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       "      <td>NaT</td>\n",
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       "      <th>2013-01-01</th>\n",
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       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-6 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Store  Promo  StateHoliday_bool  SchoolHoliday AfterSchoolHoliday  \\\n",
       "Date                                                                            \n",
       "2013-01-01   1115      0               True              1             0 days   \n",
       "2013-01-01    746      0               True              1             0 days   \n",
       "2013-01-01    171      0               True              1             0 days   \n",
       "2013-01-01    694      0               True              1             0 days   \n",
       "2013-01-01    396      0               True              1             0 days   \n",
       "\n",
       "           BeforeSchoolHoliday AfterStateHoliday_bool BeforeStateHoliday_bool  \\\n",
       "Date                                                                            \n",
       "2013-01-01              0 days                 0 days                  0 days   \n",
       "2013-01-01              0 days                 0 days                  0 days   \n",
       "2013-01-01              0 days                 0 days                  0 days   \n",
       "2013-01-01              0 days                 0 days                  0 days   \n",
       "2013-01-01              0 days                 0 days                  0 days   \n",
       "\n",
       "           AfterPromo BeforePromo  \n",
       "Date                               \n",
       "2013-01-01        NaT     -6 days  \n",
       "2013-01-01        NaT     -6 days  \n",
       "2013-01-01        NaT     -6 days  \n",
       "2013-01-01        NaT     -6 days  \n",
       "2013-01-01        NaT     -6 days  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.sort_values('Date').head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NaT: Not a Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2015-08-01</th>\n",
       "      <td>553</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-01</th>\n",
       "      <td>394</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0 days</td>\n",
       "      <td>0 days</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-01</th>\n",
       "      <td>393</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-01</th>\n",
       "      <td>392</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-01</th>\n",
       "      <td>391</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaT</td>\n",
       "      <td>-2 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Store  Promo  StateHoliday_bool  SchoolHoliday AfterSchoolHoliday  \\\n",
       "Date                                                                            \n",
       "2015-08-01    553      0              False              0                NaT   \n",
       "2015-08-01    394      0              False              1             0 days   \n",
       "2015-08-01    393      0              False              0                NaT   \n",
       "2015-08-01    392      0              False              0                NaT   \n",
       "2015-08-01    391      0              False              0                NaT   \n",
       "\n",
       "           BeforeSchoolHoliday AfterStateHoliday_bool BeforeStateHoliday_bool  \\\n",
       "Date                                                                            \n",
       "2015-08-01             -2 days                    NaT                     NaT   \n",
       "2015-08-01              0 days                    NaT                     NaT   \n",
       "2015-08-01             -2 days                    NaT                     NaT   \n",
       "2015-08-01             -2 days                    NaT                     NaT   \n",
       "2015-08-01             -2 days                    NaT                     NaT   \n",
       "\n",
       "           AfterPromo BeforePromo  \n",
       "Date                               \n",
       "2015-08-01        NaT     -2 days  \n",
       "2015-08-01        NaT     -2 days  \n",
       "2015-08-01        NaT     -2 days  \n",
       "2015-08-01        NaT     -2 days  \n",
       "2015-08-01        NaT     -2 days  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.sort_values('Date').head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Elimina los NaT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['SchoolHoliday', 'StateHoliday_bool', 'Promo']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "for o in ['Before', 'After']:\n",
    "    for p in columns:\n",
    "        a = o+p\n",
    "        df_train[a] = df_train[a].fillna(pd.Timedelta(0)).dt.days\n",
    "        df_test[a] = df_test[a].fillna(pd.Timedelta(0)).dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "            Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "Date                                                         \n",
       "2013-01-01   1115      0               True              1   \n",
       "2013-01-01    746      0               True              1   \n",
       "2013-01-01    171      0               True              1   \n",
       "2013-01-01    694      0               True              1   \n",
       "2013-01-01    396      0               True              1   \n",
       "2013-01-01    196      0               True              1   \n",
       "2013-01-01    271      0               True              1   \n",
       "2013-01-01     32      0               True              1   \n",
       "2013-01-01    440      0               True              1   \n",
       "2013-01-01   1090      0               True              1   \n",
       "\n",
       "            AfterSchoolHoliday  BeforeSchoolHoliday  AfterStateHoliday_bool  \\\n",
       "Date                                                                          \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "2013-01-01                   0                    0                       0   \n",
       "\n",
       "            BeforeStateHoliday_bool  AfterPromo  BeforePromo  \n",
       "Date                                                          \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  \n",
       "2013-01-01                        0           0           -6  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.sort_values('Date').head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "            Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "Date                                                         \n",
       "2015-08-01    553      0              False              0   \n",
       "2015-08-01    394      0              False              1   \n",
       "2015-08-01    393      0              False              0   \n",
       "2015-08-01    392      0              False              0   \n",
       "2015-08-01    391      0              False              0   \n",
       "2015-08-01    389      0              False              0   \n",
       "2015-08-01    388      0              False              0   \n",
       "2015-08-01    387      0              False              0   \n",
       "2015-08-01    386      0              False              0   \n",
       "2015-08-01    385      0              False              0   \n",
       "\n",
       "            AfterSchoolHoliday  BeforeSchoolHoliday  AfterStateHoliday_bool  \\\n",
       "Date                                                                          \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                    0                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "2015-08-01                   0                   -2                       0   \n",
       "\n",
       "            BeforeStateHoliday_bool  AfterPromo  BeforePromo  \n",
       "Date                                                          \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                        0           0           -2  \n",
       "2015-08-01                      -14           0           -2  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.sort_values('Date').head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,3))\n",
    "df_train[df_train['Store'] == 280]['BeforeSchoolHoliday'].plot()\n",
    "df_train[df_train['Store'] == 280]['BeforeStateHoliday_bool'].plot()\n",
    "df_train[df_train['Store'] == 280]['BeforePromo'].plot()\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20,3))\n",
    "df_train[df_train['Store'] == 280]['AfterSchoolHoliday'].plot()\n",
    "df_train[df_train['Store'] == 280]['AfterStateHoliday_bool'].plot()\n",
    "df_train[df_train['Store'] == 280]['AfterPromo'].plot()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### \"Suavizado\" de columnas temporales "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "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>index</th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>AfterSchoolHoliday</th>\n",
       "      <th>BeforeSchoolHoliday</th>\n",
       "      <th>AfterStateHoliday_bool</th>\n",
       "      <th>BeforeStateHoliday_bool</th>\n",
       "      <th>AfterPromo</th>\n",
       "      <th>BeforePromo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>941</th>\n",
       "      <td>941</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>940</th>\n",
       "      <td>940</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-86</td>\n",
       "      <td>0</td>\n",
       "      <td>-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>939</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>-85</td>\n",
       "      <td>0</td>\n",
       "      <td>-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>938</th>\n",
       "      <td>938</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-84</td>\n",
       "      <td>0</td>\n",
       "      <td>-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>937</td>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>-83</td>\n",
       "      <td>0</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>936</th>\n",
       "      <td>936</td>\n",
       "      <td>2013-01-06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>-82</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>935</th>\n",
       "      <td>935</td>\n",
       "      <td>2013-01-07</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>-81</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>934</th>\n",
       "      <td>934</td>\n",
       "      <td>2013-01-08</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>-80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>933</td>\n",
       "      <td>2013-01-09</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>-79</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>932</td>\n",
       "      <td>2013-01-10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>-78</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>931</td>\n",
       "      <td>2013-01-11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>-77</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>930</td>\n",
       "      <td>2013-01-12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-72</td>\n",
       "      <td>11</td>\n",
       "      <td>-76</td>\n",
       "      <td>1</td>\n",
       "      <td>-9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>929</td>\n",
       "      <td>2013-01-13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>-71</td>\n",
       "      <td>12</td>\n",
       "      <td>-75</td>\n",
       "      <td>2</td>\n",
       "      <td>-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>928</th>\n",
       "      <td>928</td>\n",
       "      <td>2013-01-14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-70</td>\n",
       "      <td>13</td>\n",
       "      <td>-74</td>\n",
       "      <td>3</td>\n",
       "      <td>-7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>927</th>\n",
       "      <td>927</td>\n",
       "      <td>2013-01-15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>-69</td>\n",
       "      <td>14</td>\n",
       "      <td>-73</td>\n",
       "      <td>4</td>\n",
       "      <td>-6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>926</th>\n",
       "      <td>926</td>\n",
       "      <td>2013-01-16</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>-68</td>\n",
       "      <td>15</td>\n",
       "      <td>-72</td>\n",
       "      <td>5</td>\n",
       "      <td>-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>925</th>\n",
       "      <td>925</td>\n",
       "      <td>2013-01-17</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>-67</td>\n",
       "      <td>16</td>\n",
       "      <td>-71</td>\n",
       "      <td>6</td>\n",
       "      <td>-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>924</th>\n",
       "      <td>924</td>\n",
       "      <td>2013-01-18</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>-66</td>\n",
       "      <td>17</td>\n",
       "      <td>-70</td>\n",
       "      <td>7</td>\n",
       "      <td>-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>923</th>\n",
       "      <td>923</td>\n",
       "      <td>2013-01-19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>-65</td>\n",
       "      <td>18</td>\n",
       "      <td>-69</td>\n",
       "      <td>8</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>922</th>\n",
       "      <td>922</td>\n",
       "      <td>2013-01-20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>-64</td>\n",
       "      <td>19</td>\n",
       "      <td>-68</td>\n",
       "      <td>9</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     index       Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "941    941 2013-01-01      1      0               True              1   \n",
       "940    940 2013-01-02      1      0              False              1   \n",
       "939    939 2013-01-03      1      0              False              1   \n",
       "938    938 2013-01-04      1      0              False              1   \n",
       "937    937 2013-01-05      1      0              False              1   \n",
       "936    936 2013-01-06      1      0              False              1   \n",
       "935    935 2013-01-07      1      1              False              1   \n",
       "934    934 2013-01-08      1      1              False              1   \n",
       "933    933 2013-01-09      1      1              False              1   \n",
       "932    932 2013-01-10      1      1              False              1   \n",
       "931    931 2013-01-11      1      1              False              1   \n",
       "930    930 2013-01-12      1      0              False              0   \n",
       "929    929 2013-01-13      1      0              False              0   \n",
       "928    928 2013-01-14      1      0              False              0   \n",
       "927    927 2013-01-15      1      0              False              0   \n",
       "926    926 2013-01-16      1      0              False              0   \n",
       "925    925 2013-01-17      1      0              False              0   \n",
       "924    924 2013-01-18      1      0              False              0   \n",
       "923    923 2013-01-19      1      0              False              0   \n",
       "922    922 2013-01-20      1      0              False              0   \n",
       "\n",
       "     AfterSchoolHoliday  BeforeSchoolHoliday  AfterStateHoliday_bool  \\\n",
       "941                   0                    0                       0   \n",
       "940                   0                    0                       1   \n",
       "939                   0                    0                       2   \n",
       "938                   0                    0                       3   \n",
       "937                   0                    0                       4   \n",
       "936                   0                    0                       5   \n",
       "935                   0                    0                       6   \n",
       "934                   0                    0                       7   \n",
       "933                   0                    0                       8   \n",
       "932                   0                    0                       9   \n",
       "931                   0                    0                      10   \n",
       "930                   1                  -72                      11   \n",
       "929                   2                  -71                      12   \n",
       "928                   3                  -70                      13   \n",
       "927                   4                  -69                      14   \n",
       "926                   5                  -68                      15   \n",
       "925                   6                  -67                      16   \n",
       "924                   7                  -66                      17   \n",
       "923                   8                  -65                      18   \n",
       "922                   9                  -64                      19   \n",
       "\n",
       "     BeforeStateHoliday_bool  AfterPromo  BeforePromo  \n",
       "941                        0           0           -6  \n",
       "940                      -86           0           -5  \n",
       "939                      -85           0           -4  \n",
       "938                      -84           0           -3  \n",
       "937                      -83           0           -2  \n",
       "936                      -82           0           -1  \n",
       "935                      -81           0            0  \n",
       "934                      -80           0            0  \n",
       "933                      -79           0            0  \n",
       "932                      -78           0            0  \n",
       "931                      -77           0            0  \n",
       "930                      -76           1           -9  \n",
       "929                      -75           2           -8  \n",
       "928                      -74           3           -7  \n",
       "927                      -73           4           -6  \n",
       "926                      -72           5           -5  \n",
       "925                      -71           6           -4  \n",
       "924                      -70           7           -3  \n",
       "923                      -69           8           -2  \n",
       "922                      -68           9           -1  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Datos del store 1 ordenados por fecha\n",
    "df_train[df_train[['Store']+columns]['Store'] == 1].sort_values('Date').head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "ename": "DataError",
     "evalue": "Cannot aggregate non-numeric type: datetime64[ns]",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNotImplementedError\u001b[0m                       Traceback (most recent call last)",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:489\u001b[0m, in \u001b[0;36mBaseWindow._apply_columnwise\u001b[0;34m(self, homogeneous_func, name, numeric_only)\u001b[0m\n\u001b[1;32m    488\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 489\u001b[0m     arr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_prep_values\u001b[49m\u001b[43m(\u001b[49m\u001b[43marr\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    490\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mTypeError\u001b[39;00m, \u001b[38;5;167;01mNotImplementedError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:361\u001b[0m, in \u001b[0;36mBaseWindow._prep_values\u001b[0;34m(self, values)\u001b[0m\n\u001b[1;32m    360\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m needs_i8_conversion(values\u001b[38;5;241m.\u001b[39mdtype):\n\u001b[0;32m--> 361\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m(\n\u001b[1;32m    362\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mops for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    363\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvalues\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m are not implemented\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    364\u001b[0m     )\n\u001b[1;32m    365\u001b[0m \u001b[38;5;66;03m# GH #12373 : rolling functions error on float32 data\u001b[39;00m\n\u001b[1;32m    366\u001b[0m \u001b[38;5;66;03m# make sure the data is coerced to float64\u001b[39;00m\n",
      "\u001b[0;31mNotImplementedError\u001b[0m: ops for RollingGroupby for this dtype datetime64[ns] are not implemented",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mDataError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[66], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m bwd_train \u001b[38;5;241m=\u001b[39m \u001b[43mdf_train\u001b[49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mStore\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mDate\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msort_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroupby\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mStore\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrolling\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m7\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmin_periods\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msum\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m bwd_test \u001b[38;5;241m=\u001b[39m df_test[[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mStore\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDate\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m+\u001b[39mcolumns]\u001b[38;5;241m.\u001b[39msort_index()\u001b[38;5;241m.\u001b[39mgroupby(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mStore\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mrolling(\u001b[38;5;241m7\u001b[39m, min_periods\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\u001b[38;5;241m.\u001b[39msum()\n\u001b[1;32m      3\u001b[0m bwd_train\u001b[38;5;241m.\u001b[39mhead(\u001b[38;5;241m20\u001b[39m)\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:2127\u001b[0m, in \u001b[0;36mRolling.sum\u001b[0;34m(self, numeric_only, engine, engine_kwargs)\u001b[0m\n\u001b[1;32m   2058\u001b[0m \u001b[38;5;129m@doc\u001b[39m(\n\u001b[1;32m   2059\u001b[0m     template_header,\n\u001b[1;32m   2060\u001b[0m     create_section_header(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mParameters\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2125\u001b[0m     engine_kwargs: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, \u001b[38;5;28mbool\u001b[39m] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   2126\u001b[0m ):\n\u001b[0;32m-> 2127\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msum\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   2128\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnumeric_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnumeric_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2129\u001b[0m \u001b[43m        \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2130\u001b[0m \u001b[43m        \u001b[49m\u001b[43mengine_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   2131\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:1559\u001b[0m, in \u001b[0;36mRollingAndExpandingMixin.sum\u001b[0;34m(self, numeric_only, engine, engine_kwargs)\u001b[0m\n\u001b[1;32m   1557\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_numba_apply(sliding_sum, engine_kwargs)\n\u001b[1;32m   1558\u001b[0m window_func \u001b[38;5;241m=\u001b[39m window_aggregations\u001b[38;5;241m.\u001b[39mroll_sum\n\u001b[0;32m-> 1559\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mwindow_func\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msum\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumeric_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnumeric_only\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:723\u001b[0m, in \u001b[0;36mBaseWindowGroupby._apply\u001b[0;34m(self, func, name, numeric_only, numba_args, **kwargs)\u001b[0m\n\u001b[1;32m    715\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_apply\u001b[39m(\n\u001b[1;32m    716\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    717\u001b[0m     func: Callable[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, Any],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    721\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m    722\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m Series:\n\u001b[0;32m--> 723\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    724\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    725\u001b[0m \u001b[43m        \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    726\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnumeric_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    727\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnumba_args\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    728\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    729\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    730\u001b[0m     \u001b[38;5;66;03m# Reconstruct the resulting MultiIndex\u001b[39;00m\n\u001b[1;32m    731\u001b[0m     \u001b[38;5;66;03m# 1st set of levels = group by labels\u001b[39;00m\n\u001b[1;32m    732\u001b[0m     \u001b[38;5;66;03m# 2nd set of levels = original DataFrame/Series index\u001b[39;00m\n\u001b[1;32m    733\u001b[0m     grouped_object_index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39mindex\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:619\u001b[0m, in \u001b[0;36mBaseWindow._apply\u001b[0;34m(self, func, name, numeric_only, numba_args, **kwargs)\u001b[0m\n\u001b[1;32m    616\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\n\u001b[1;32m    618\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmethod \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msingle\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m--> 619\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply_columnwise\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhomogeneous_func\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumeric_only\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    620\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    621\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_apply_tablewise(homogeneous_func, name, numeric_only)\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/window/rolling.py:491\u001b[0m, in \u001b[0;36mBaseWindow._apply_columnwise\u001b[0;34m(self, homogeneous_func, name, numeric_only)\u001b[0m\n\u001b[1;32m    489\u001b[0m     arr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prep_values(arr)\n\u001b[1;32m    490\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mTypeError\u001b[39;00m, \u001b[38;5;167;01mNotImplementedError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 491\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m DataError(\n\u001b[1;32m    492\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot aggregate non-numeric type: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00marr\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    493\u001b[0m     ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m    494\u001b[0m res \u001b[38;5;241m=\u001b[39m homogeneous_func(arr)\n\u001b[1;32m    495\u001b[0m res_values\u001b[38;5;241m.\u001b[39mappend(res)\n",
      "\u001b[0;31mDataError\u001b[0m: Cannot aggregate non-numeric type: datetime64[ns]"
     ]
    }
   ],
   "source": [
    "bwd_train = df_train[['Store']+columns].sort_index().groupby(\"Store\").rolling(7, min_periods=1).sum()\n",
    "bwd_test = df_test[['Store']+columns].sort_index().groupby(\"Store\").rolling(7, min_periods=1).sum()\n",
    "bwd_train.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>SchoolHoliday</th>\n",
       "      <th>StateHoliday_bool</th>\n",
       "      <th>Promo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Store</th>\n",
       "      <th></th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">1115</th>\n",
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       "    <tr>\n",
       "      <th>1017205</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1017206</th>\n",
       "      <td>7.0</td>\n",
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       "<p>1017209 rows × 3 columns</p>\n",
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      ],
      "text/plain": [
       "               SchoolHoliday  StateHoliday_bool  Promo\n",
       "Store                                                 \n",
       "1     0                  1.0                0.0    1.0\n",
       "      1                  2.0                0.0    2.0\n",
       "      2                  3.0                0.0    3.0\n",
       "      3                  4.0                0.0    4.0\n",
       "      4                  5.0                0.0    5.0\n",
       "...                      ...                ...    ...\n",
       "1115  1017204            7.0                0.0    5.0\n",
       "      1017205            7.0                0.0    4.0\n",
       "      1017206            7.0                0.0    3.0\n",
       "      1017207            7.0                0.0    2.0\n",
       "      1017208            7.0                1.0    1.0\n",
       "\n",
       "[1017209 rows x 3 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bwd_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
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       "      <td>1</td>\n",
       "      <td>2015-07-30</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-07-27</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017204</th>\n",
       "      <td>1017204</td>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>-83</td>\n",
       "      <td>0</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017205</th>\n",
       "      <td>1017205</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-84</td>\n",
       "      <td>0</td>\n",
       "      <td>-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017206</th>\n",
       "      <td>1017206</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>-85</td>\n",
       "      <td>0</td>\n",
       "      <td>-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017207</th>\n",
       "      <td>1017207</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-86</td>\n",
       "      <td>0</td>\n",
       "      <td>-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017208</th>\n",
       "      <td>1017208</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1017209 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           index       Date  Store  Promo  StateHoliday_bool  SchoolHoliday  \\\n",
       "0              0 2015-07-31      1      1              False              1   \n",
       "1              1 2015-07-30      1      1              False              1   \n",
       "2              2 2015-07-29      1      1              False              1   \n",
       "3              3 2015-07-28      1      1              False              1   \n",
       "4              4 2015-07-27      1      1              False              1   \n",
       "...          ...        ...    ...    ...                ...            ...   \n",
       "1017204  1017204 2013-01-05   1115      0              False              1   \n",
       "1017205  1017205 2013-01-04   1115      0              False              1   \n",
       "1017206  1017206 2013-01-03   1115      0              False              1   \n",
       "1017207  1017207 2013-01-02   1115      0              False              1   \n",
       "1017208  1017208 2013-01-01   1115      0               True              1   \n",
       "\n",
       "         AfterSchoolHoliday  BeforeSchoolHoliday  AfterStateHoliday_bool  \\\n",
       "0                         0                    0                      57   \n",
       "1                         0                    0                      56   \n",
       "2                         0                    0                      55   \n",
       "3                         0                    0                      54   \n",
       "4                         0                    0                      53   \n",
       "...                     ...                  ...                     ...   \n",
       "1017204                   0                    0                       4   \n",
       "1017205                   0                    0                       3   \n",
       "1017206                   0                    0                       2   \n",
       "1017207                   0                    0                       1   \n",
       "1017208                   0                    0                       0   \n",
       "\n",
       "         BeforeStateHoliday_bool  AfterPromo  BeforePromo  \n",
       "0                              0           0            0  \n",
       "1                              0           0            0  \n",
       "2                              0           0            0  \n",
       "3                              0           0            0  \n",
       "4                              0           0            0  \n",
       "...                          ...         ...          ...  \n",
       "1017204                      -83           0           -2  \n",
       "1017205                      -84           0           -3  \n",
       "1017206                      -85           0           -4  \n",
       "1017207                      -86           0           -5  \n",
       "1017208                        0           0           -6  \n",
       "\n",
       "[1017209 rows x 12 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "bwd_train.reset_index(inplace=True)\n",
    "#bwd_train.drop('Store',axis = 1,inplace=True)\n",
    "bwd_test.reset_index(inplace=True)\n",
    "#bwd_test.drop('Store',axis = 1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "    Store  level_1  SchoolHoliday  StateHoliday_bool  Promo\n",
       "0       1        0            1.0                0.0    1.0\n",
       "1       1        1            2.0                0.0    2.0\n",
       "2       1        2            3.0                0.0    3.0\n",
       "3       1        3            4.0                0.0    4.0\n",
       "4       1        4            5.0                0.0    5.0\n",
       "5       1        5            5.0                0.0    5.0\n",
       "6       1        6            5.0                0.0    5.0\n",
       "7       1        7            4.0                0.0    4.0\n",
       "8       1        8            3.0                0.0    3.0\n",
       "9       1        9            2.0                0.0    2.0\n",
       "10      1       10            1.0                0.0    1.0\n",
       "11      1       11            0.0                0.0    0.0\n",
       "12      1       12            0.0                0.0    0.0\n",
       "13      1       13            0.0                0.0    0.0\n",
       "14      1       14            0.0                0.0    1.0\n",
       "15      1       15            0.0                0.0    2.0\n",
       "16      1       16            0.0                0.0    3.0\n",
       "17      1       17            0.0                0.0    4.0\n",
       "18      1       18            0.0                0.0    5.0\n",
       "19      1       19            0.0                0.0    5.0"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bwd_train.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ordena al reves\n",
    "fwd_train = df_train[['Store']+columns].sort_index(ascending=False).groupby(\"Store\").rolling(7, min_periods=1).sum()\n",
    "fwd_test = df_test[['Store']+columns].sort_index(ascending=False).groupby(\"Store\").rolling(7, min_periods=1).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>926</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>925</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>924</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>923</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>922</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           SchoolHoliday  StateHoliday_bool  Promo\n",
       "Store                                             \n",
       "1     941            1.0                1.0    0.0\n",
       "      940            2.0                1.0    0.0\n",
       "      939            3.0                1.0    0.0\n",
       "      938            4.0                1.0    0.0\n",
       "      937            5.0                1.0    0.0\n",
       "      936            6.0                1.0    0.0\n",
       "      935            7.0                1.0    1.0\n",
       "      934            7.0                0.0    2.0\n",
       "      933            7.0                0.0    3.0\n",
       "      932            7.0                0.0    4.0\n",
       "      931            7.0                0.0    5.0\n",
       "      930            6.0                0.0    5.0\n",
       "      929            5.0                0.0    5.0\n",
       "      928            4.0                0.0    4.0\n",
       "      927            3.0                0.0    3.0\n",
       "      926            2.0                0.0    2.0\n",
       "      925            1.0                0.0    1.0\n",
       "      924            0.0                0.0    0.0\n",
       "      923            0.0                0.0    0.0\n",
       "      922            0.0                0.0    0.0"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fwd_train.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "fwd_train.reset_index(inplace=True)\n",
    "#fwd_train.drop('Store',axis=1,inplace=True)\n",
    "fwd_test.reset_index(inplace=True)\n",
    "#fwd_test.drop('Store',axis = 1,inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.reset_index(inplace=True)\n",
    "df_test.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>BeforeStateHoliday_bool</th>\n",
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       "      <td>2</td>\n",
       "      <td>2015-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
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       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2015-07-28</td>\n",
       "      <td>1</td>\n",
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       "      <td>2015-07-27</td>\n",
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       "      <th>1017204</th>\n",
       "      <td>1017204</td>\n",
       "      <td>1017204</td>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1017205</th>\n",
       "      <td>1017205</td>\n",
       "      <td>1017205</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-84</td>\n",
       "      <td>0</td>\n",
       "      <td>-3</td>\n",
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       "    <tr>\n",
       "      <th>1017206</th>\n",
       "      <td>1017206</td>\n",
       "      <td>1017206</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
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       "      <th>1017207</th>\n",
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       "      <td>0</td>\n",
       "      <td>False</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-86</td>\n",
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       "      <td>-5</td>\n",
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       "    <tr>\n",
       "      <th>1017208</th>\n",
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       "      <td>1017208</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>1115</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1017209 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         level_0    index       Date  Store  Promo  StateHoliday_bool  \\\n",
       "0              0        0 2015-07-31      1      1              False   \n",
       "1              1        1 2015-07-30      1      1              False   \n",
       "2              2        2 2015-07-29      1      1              False   \n",
       "3              3        3 2015-07-28      1      1              False   \n",
       "4              4        4 2015-07-27      1      1              False   \n",
       "...          ...      ...        ...    ...    ...                ...   \n",
       "1017204  1017204  1017204 2013-01-05   1115      0              False   \n",
       "1017205  1017205  1017205 2013-01-04   1115      0              False   \n",
       "1017206  1017206  1017206 2013-01-03   1115      0              False   \n",
       "1017207  1017207  1017207 2013-01-02   1115      0              False   \n",
       "1017208  1017208  1017208 2013-01-01   1115      0               True   \n",
       "\n",
       "         SchoolHoliday  AfterSchoolHoliday  BeforeSchoolHoliday  \\\n",
       "0                    1                   0                    0   \n",
       "1                    1                   0                    0   \n",
       "2                    1                   0                    0   \n",
       "3                    1                   0                    0   \n",
       "4                    1                   0                    0   \n",
       "...                ...                 ...                  ...   \n",
       "1017204              1                   0                    0   \n",
       "1017205              1                   0                    0   \n",
       "1017206              1                   0                    0   \n",
       "1017207              1                   0                    0   \n",
       "1017208              1                   0                    0   \n",
       "\n",
       "         AfterStateHoliday_bool  BeforeStateHoliday_bool  AfterPromo  \\\n",
       "0                            57                        0           0   \n",
       "1                            56                        0           0   \n",
       "2                            55                        0           0   \n",
       "3                            54                        0           0   \n",
       "4                            53                        0           0   \n",
       "...                         ...                      ...         ...   \n",
       "1017204                       4                      -83           0   \n",
       "1017205                       3                      -84           0   \n",
       "1017206                       2                      -85           0   \n",
       "1017207                       1                      -86           0   \n",
       "1017208                       0                        0           0   \n",
       "\n",
       "         BeforePromo  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "...              ...  \n",
       "1017204           -2  \n",
       "1017205           -3  \n",
       "1017206           -4  \n",
       "1017207           -5  \n",
       "1017208           -6  \n",
       "\n",
       "[1017209 rows x 13 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = df_train.merge(bwd_train, 'left', left_on=['level_0', 'Store'],right_on = ['level_1','Store'], suffixes=['', '_bw'])\n",
    "df_train = df_train.merge(fwd_train, 'left', left_on=['level_0', 'Store'],right_on = ['level_1','Store'], suffixes=['', '_fw'])\n",
    "df_test = df_test.merge(bwd_test, 'left', left_on=['level_0', 'Store'],right_on = ['level_1','Store'], suffixes=['', '_bw'])\n",
    "df_test = df_test.merge(fwd_test, 'left', left_on=['level_0', 'Store'],right_on = ['level_1','Store'], suffixes=['', '_fw'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.drop(columns,axis=1,inplace=True)\n",
    "df_test.drop(columns,axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.drop(columns=[\"level_0\", \"level_1\", \"level_1_fw\"], inplace = True)\n",
    "df_test.drop(columns=[\"level_0\", \"level_1\", \"level_1_fw\"], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>StateHoliday_bool_fw</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>4.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
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       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-07-28</td>\n",
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       "      <td>0</td>\n",
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       "      <td>54</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-07-27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index       Date  Store  AfterSchoolHoliday  BeforeSchoolHoliday  \\\n",
       "0      0 2015-07-31      1                   0                    0   \n",
       "1      1 2015-07-30      1                   0                    0   \n",
       "2      2 2015-07-29      1                   0                    0   \n",
       "3      3 2015-07-28      1                   0                    0   \n",
       "4      4 2015-07-27      1                   0                    0   \n",
       "\n",
       "   AfterStateHoliday_bool  BeforeStateHoliday_bool  AfterPromo  BeforePromo  \\\n",
       "0                      57                        0           0            0   \n",
       "1                      56                        0           0            0   \n",
       "2                      55                        0           0            0   \n",
       "3                      54                        0           0            0   \n",
       "4                      53                        0           0            0   \n",
       "\n",
       "   SchoolHoliday_bw  StateHoliday_bool_bw  Promo_bw  SchoolHoliday_fw  \\\n",
       "0               1.0                   0.0       1.0               5.0   \n",
       "1               2.0                   0.0       2.0               4.0   \n",
       "2               3.0                   0.0       3.0               3.0   \n",
       "3               4.0                   0.0       4.0               2.0   \n",
       "4               5.0                   0.0       5.0               1.0   \n",
       "\n",
       "   StateHoliday_bool_fw  Promo_fw  \n",
       "0                   0.0       5.0  \n",
       "1                   0.0       4.0  \n",
       "2                   0.0       3.0  \n",
       "3                   0.0       2.0  \n",
       "4                   0.0       1.0  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train[\"Date\"] = pd.to_datetime(df_train.Date)\n",
    "df_test[\"Date\"] = pd.to_datetime(df_test.Date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "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>index</th>\n",
       "      <th>Date</th>\n",
       "      <th>Store</th>\n",
       "      <th>AfterSchoolHoliday</th>\n",
       "      <th>BeforeSchoolHoliday</th>\n",
       "      <th>AfterStateHoliday_bool</th>\n",
       "      <th>BeforeStateHoliday_bool</th>\n",
       "      <th>AfterPromo</th>\n",
       "      <th>BeforePromo</th>\n",
       "      <th>SchoolHoliday_bw</th>\n",
       "      <th>StateHoliday_bool_bw</th>\n",
       "      <th>Promo_bw</th>\n",
       "      <th>SchoolHoliday_fw</th>\n",
       "      <th>StateHoliday_bool_fw</th>\n",
       "      <th>Promo_fw</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-07-30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-07-27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index       Date  Store  AfterSchoolHoliday  BeforeSchoolHoliday  \\\n",
       "0      0 2015-07-31      1                   0                    0   \n",
       "1      1 2015-07-30      1                   0                    0   \n",
       "2      2 2015-07-29      1                   0                    0   \n",
       "3      3 2015-07-28      1                   0                    0   \n",
       "4      4 2015-07-27      1                   0                    0   \n",
       "\n",
       "   AfterStateHoliday_bool  BeforeStateHoliday_bool  AfterPromo  BeforePromo  \\\n",
       "0                      57                        0           0            0   \n",
       "1                      56                        0           0            0   \n",
       "2                      55                        0           0            0   \n",
       "3                      54                        0           0            0   \n",
       "4                      53                        0           0            0   \n",
       "\n",
       "   SchoolHoliday_bw  StateHoliday_bool_bw  Promo_bw  SchoolHoliday_fw  \\\n",
       "0               1.0                   0.0       1.0               5.0   \n",
       "1               2.0                   0.0       2.0               4.0   \n",
       "2               3.0                   0.0       3.0               3.0   \n",
       "3               4.0                   0.0       4.0               2.0   \n",
       "4               5.0                   0.0       5.0               1.0   \n",
       "\n",
       "   StateHoliday_bool_fw  Promo_fw  \n",
       "0                   0.0       5.0  \n",
       "1                   0.0       4.0  \n",
       "2                   0.0       3.0  \n",
       "3                   0.0       2.0  \n",
       "4                   0.0       1.0  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,3))\n",
    "df_train[df_train['Store'] == 280]['BeforeSchoolHoliday'].plot()\n",
    "df_train[df_train['Store'] == 280]['BeforeStateHoliday_bool'].plot()\n",
    "df_train[df_train['Store'] == 280]['BeforePromo'].plot()\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(20,3))\n",
    "df_train[df_train['Store'] == 280]['AfterSchoolHoliday'].plot()\n",
    "df_train[df_train['Store'] == 280]['AfterStateHoliday_bool'].plot()\n",
    "df_train[df_train['Store'] == 280]['AfterPromo'].plot()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "def join_df(left, right, left_on, right_on=None):\n",
    "    if right_on is None: right_on = left_on\n",
    "    return left.merge(right, how='left', left_on=left_on, right_on=right_on, \n",
    "                      suffixes=(\"\", \"_y\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_train = join_df(joined_train, df_train, ['Store', 'Date'])\n",
    "joined_test = join_df(joined_test, df_test, ['Store', 'Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1017209, 82)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_train.to_feather('all_preprocessed_train.fth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "joined_test.to_feather('all_preprocessed_test.fth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Promo')"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,3))\n",
    "plt.plot(joined_train[joined_train['Store']==280]['StateHoliday_bool'].values[100:310]*1.0, c='b', marker='.', linestyle='None')\n",
    "plt.plot(joined_train[joined_train['Store']==280]['StateHoliday_bool_bw'].values[100:310]*1.0, c='r', label='backward')\n",
    "plt.plot(joined_train[joined_train['Store']==280]['StateHoliday_bool_fw'].values[100:310]*1.0, c='g', label='forward')\n",
    "plt.legend()\n",
    "plt.title('State Holidays')\n",
    "plt.figure(figsize=(20,3))\n",
    "plt.plot(joined_train[joined_train['Store']==280]['Promo'].values[100:310]*1.0, c='b', marker='.', linestyle='None')\n",
    "plt.plot(joined_train[joined_train['Store']==280]['Promo_bw'].values[100:310]*1.0, c='r', label='backward')\n",
    "plt.plot(joined_train[joined_train['Store']==280]['Promo_fw'].values[100:310]*1.0, c='g', label='forward')\n",
    "plt.legend()\n",
    "plt.title('Promo')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "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>DayOfWeek</th>\n",
       "      <th>Date</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Customers</th>\n",
       "      <th>Open</th>\n",
       "      <th>Promo</th>\n",
       "      <th>StateHoliday</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>Year</th>\n",
       "      <th>...</th>\n",
       "      <th>AfterStateHoliday_bool</th>\n",
       "      <th>BeforeStateHoliday_bool</th>\n",
       "      <th>AfterPromo</th>\n",
       "      <th>BeforePromo</th>\n",
       "      <th>SchoolHoliday_bw</th>\n",
       "      <th>StateHoliday_bool_bw</th>\n",
       "      <th>Promo_bw</th>\n",
       "      <th>SchoolHoliday_fw</th>\n",
       "      <th>StateHoliday_bool_fw</th>\n",
       "      <th>Promo_fw</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>5263</td>\n",
       "      <td>555</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>6064</td>\n",
       "      <td>625</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>8314</td>\n",
       "      <td>821</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>13995</td>\n",
       "      <td>1498</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2015-07-31</td>\n",
       "      <td>4822</td>\n",
       "      <td>559</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017204</th>\n",
       "      <td>1111</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2013</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017205</th>\n",
       "      <td>1112</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2013</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017206</th>\n",
       "      <td>1113</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2013</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017207</th>\n",
       "      <td>1114</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2013</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017208</th>\n",
       "      <td>1115</td>\n",
       "      <td>2</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2013</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-6</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1017209 rows × 82 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Store  DayOfWeek       Date  Sales  Customers  Open  Promo  \\\n",
       "0            1          5 2015-07-31   5263        555     1      1   \n",
       "1            2          5 2015-07-31   6064        625     1      1   \n",
       "2            3          5 2015-07-31   8314        821     1      1   \n",
       "3            4          5 2015-07-31  13995       1498     1      1   \n",
       "4            5          5 2015-07-31   4822        559     1      1   \n",
       "...        ...        ...        ...    ...        ...   ...    ...   \n",
       "1017204   1111          2 2013-01-01      0          0     0      0   \n",
       "1017205   1112          2 2013-01-01      0          0     0      0   \n",
       "1017206   1113          2 2013-01-01      0          0     0      0   \n",
       "1017207   1114          2 2013-01-01      0          0     0      0   \n",
       "1017208   1115          2 2013-01-01      0          0     0      0   \n",
       "\n",
       "        StateHoliday  SchoolHoliday  Year  ...  AfterStateHoliday_bool  \\\n",
       "0                  0              1  2015  ...                      57   \n",
       "1                  0              1  2015  ...                      67   \n",
       "2                  0              1  2015  ...                      57   \n",
       "3                  0              1  2015  ...                      67   \n",
       "4                  0              1  2015  ...                      57   \n",
       "...              ...            ...   ...  ...                     ...   \n",
       "1017204            a              1  2013  ...                       0   \n",
       "1017205            a              1  2013  ...                       0   \n",
       "1017206            a              1  2013  ...                       0   \n",
       "1017207            a              1  2013  ...                       0   \n",
       "1017208            a              1  2013  ...                       0   \n",
       "\n",
       "         BeforeStateHoliday_bool  AfterPromo BeforePromo SchoolHoliday_bw  \\\n",
       "0                              0           0           0              1.0   \n",
       "1                              0           0           0              1.0   \n",
       "2                              0           0           0              1.0   \n",
       "3                              0           0           0              1.0   \n",
       "4                              0           0           0              1.0   \n",
       "...                          ...         ...         ...              ...   \n",
       "1017204                        0           0          -6              4.0   \n",
       "1017205                        0           0          -6              4.0   \n",
       "1017206                        0           0          -6              4.0   \n",
       "1017207                        0           0          -6              4.0   \n",
       "1017208                        0           0          -6              7.0   \n",
       "\n",
       "         StateHoliday_bool_bw  Promo_bw  SchoolHoliday_fw  \\\n",
       "0                         0.0       1.0               5.0   \n",
       "1                         0.0       1.0               5.0   \n",
       "2                         0.0       1.0               5.0   \n",
       "3                         0.0       1.0               5.0   \n",
       "4                         0.0       1.0               5.0   \n",
       "...                       ...       ...               ...   \n",
       "1017204                   1.0       1.0               1.0   \n",
       "1017205                   1.0       1.0               1.0   \n",
       "1017206                   1.0       1.0               1.0   \n",
       "1017207                   1.0       1.0               1.0   \n",
       "1017208                   1.0       1.0               1.0   \n",
       "\n",
       "         StateHoliday_bool_fw  Promo_fw  \n",
       "0                         0.0       5.0  \n",
       "1                         0.0       5.0  \n",
       "2                         0.0       5.0  \n",
       "3                         0.0       5.0  \n",
       "4                         0.0       5.0  \n",
       "...                       ...       ...  \n",
       "1017204                   1.0       0.0  \n",
       "1017205                   1.0       0.0  \n",
       "1017206                   1.0       0.0  \n",
       "1017207                   1.0       0.0  \n",
       "1017208                   1.0       0.0  \n",
       "\n",
       "[1017209 rows x 82 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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