3.0_Prepr_train0_date.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data preprocessing: Date extraction\n",
    "\n",
    "**NOTEBOOK GOAL**: Extract attributes: Day, Month and Year from the Date attribute\n",
    "\n",
    "**DATASET TRANSFORMATION**: `(train|test).csv` >> `preprocessed0_date_(train|test).csv`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reoder variables to work on train or test dataset\n",
    "work_on = 'test'\n",
    "#work_on = 'train'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from import_man import *\n",
    "\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StoreID</th>\n",
       "      <th>Date</th>\n",
       "      <th>IsHoliday</th>\n",
       "      <th>IsOpen</th>\n",
       "      <th>HasPromotions</th>\n",
       "      <th>StoreType</th>\n",
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       "      <th>Region</th>\n",
       "      <th>Region_AreaKM2</th>\n",
       "      <th>...</th>\n",
       "      <th>Mean_TemperatureC</th>\n",
       "      <th>Mean_VisibilityKm</th>\n",
       "      <th>Mean_Wind_SpeedKm_h</th>\n",
       "      <th>Min_Dew_PointC</th>\n",
       "      <th>Min_Humidity</th>\n",
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       "      <th>Min_TemperatureC</th>\n",
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       "      <td>...</td>\n",
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       "      <td>13.0</td>\n",
       "      <td>11</td>\n",
       "      <td>-3</td>\n",
       "      <td>41</td>\n",
       "      <td>1013</td>\n",
       "      <td>-2</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000</td>\n",
       "      <td>04/03/2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   StoreID        Date  IsHoliday  IsOpen  HasPromotions     StoreType  \\\n",
       "0     1000  01/03/2018          0       1              0  Hyper Market   \n",
       "1     1000  02/03/2018          0       1              0  Hyper Market   \n",
       "2     1000  03/03/2018          0       1              0  Hyper Market   \n",
       "3     1000  04/03/2018          0       0              0  Hyper Market   \n",
       "4     1000  05/03/2018          0       1              1  Hyper Market   \n",
       "\n",
       "  AssortmentType  NearestCompetitor  Region  Region_AreaKM2       ...        \\\n",
       "0        General                326       7            9643       ...         \n",
       "1        General                326       7            9643       ...         \n",
       "2        General                326       7            9643       ...         \n",
       "3        General                326       7            9643       ...         \n",
       "4        General                326       7            9643       ...         \n",
       "\n",
       "   Mean_TemperatureC  Mean_VisibilityKm  Mean_Wind_SpeedKm_h Min_Dew_PointC  \\\n",
       "0                  6               14.0                    5             -1   \n",
       "1                  4               12.0                    6             -1   \n",
       "2                  3               13.0                   11             -3   \n",
       "3                  6               11.0                   18             -2   \n",
       "4                  6               10.0                   23             -5   \n",
       "\n",
       "   Min_Humidity  Min_Sea_Level_PressurehPa  Min_TemperatureC  \\\n",
       "0            46                       1011                 2   \n",
       "1            52                       1009                 3   \n",
       "2            41                       1013                -2   \n",
       "3            65                       1002                 1   \n",
       "4            25                       1000                 2   \n",
       "\n",
       "   Min_VisibilitykM  Precipitationmm  WindDirDegrees  \n",
       "0              10.0             0.00             180  \n",
       "1              10.0             5.08             315  \n",
       "2              10.0             0.00             210  \n",
       "3               6.0             3.05             193  \n",
       "4               8.0             0.25             247  \n",
       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('./dataset/' + work_on + '.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['D_Day'] =  df['Date'].apply(lambda x: datetime.strptime(x, '%d/%m/%Y').day)\n",
    "df['D_DayOfYear'] =  df['Date'].apply(lambda x: datetime.strptime(x, '%d/%m/%Y').timetuple().tm_yday)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['D_Month'] =  df['Date'].apply(lambda x: datetime.strptime(x, '%d/%m/%Y').month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['D_Year'] =  df['Date'].apply(lambda x: datetime.strptime(x, '%d/%m/%Y').year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['D_DayOfweek'] =  df['Date'].apply(lambda x: datetime.strptime(x, '%d/%m/%Y').weekday())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "      <td>5</td>\n",
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       "</table>\n",
       "<p>10 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   StoreID        Date  IsHoliday  IsOpen  HasPromotions     StoreType  \\\n",
       "0     1000  01/03/2018          0       1              0  Hyper Market   \n",
       "1     1000  02/03/2018          0       1              0  Hyper Market   \n",
       "2     1000  03/03/2018          0       1              0  Hyper Market   \n",
       "3     1000  04/03/2018          0       0              0  Hyper Market   \n",
       "4     1000  05/03/2018          0       1              1  Hyper Market   \n",
       "5     1000  06/03/2018          0       1              1  Hyper Market   \n",
       "6     1000  07/03/2018          0       1              1  Hyper Market   \n",
       "7     1000  08/03/2018          0       1              1  Hyper Market   \n",
       "8     1000  09/03/2018          0       1              1  Hyper Market   \n",
       "9     1000  10/03/2018          0       1              0  Hyper Market   \n",
       "\n",
       "  AssortmentType  NearestCompetitor  Region  Region_AreaKM2     ...       \\\n",
       "0        General                326       7            9643     ...        \n",
       "1        General                326       7            9643     ...        \n",
       "2        General                326       7            9643     ...        \n",
       "3        General                326       7            9643     ...        \n",
       "4        General                326       7            9643     ...        \n",
       "5        General                326       7            9643     ...        \n",
       "6        General                326       7            9643     ...        \n",
       "7        General                326       7            9643     ...        \n",
       "8        General                326       7            9643     ...        \n",
       "9        General                326       7            9643     ...        \n",
       "\n",
       "   Min_Sea_Level_PressurehPa  Min_TemperatureC  Min_VisibilitykM  \\\n",
       "0                       1011                 2              10.0   \n",
       "1                       1009                 3              10.0   \n",
       "2                       1013                -2              10.0   \n",
       "3                       1002                 1               6.0   \n",
       "4                       1000                 2               8.0   \n",
       "5                       1016                 0              10.0   \n",
       "6                       1020                 1              10.0   \n",
       "7                       1031                 1              10.0   \n",
       "8                       1034                -2              10.0   \n",
       "9                       1029                -3              18.0   \n",
       "\n",
       "  Precipitationmm  WindDirDegrees  D_Day  D_DayOfYear  D_Month  D_Year  \\\n",
       "0            0.00             180      1           60        3    2018   \n",
       "1            5.08             315      2           61        3    2018   \n",
       "2            0.00             210      3           62        3    2018   \n",
       "3            3.05             193      4           63        3    2018   \n",
       "4            0.25             247      5           64        3    2018   \n",
       "5            0.51             213      6           65        3    2018   \n",
       "6            0.25             230      7           66        3    2018   \n",
       "7            0.00             309      8           67        3    2018   \n",
       "8            0.00             190      9           68        3    2018   \n",
       "9            0.00             178     10           69        3    2018   \n",
       "\n",
       "   D_DayOfweek  \n",
       "0            3  \n",
       "1            4  \n",
       "2            5  \n",
       "3            6  \n",
       "4            0  \n",
       "5            1  \n",
       "6            2  \n",
       "7            3  \n",
       "8            4  \n",
       "9            5  \n",
       "\n",
       "[10 rows x 39 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ATTRIBUTES LIST:\n",
      "['StoreID',\n",
      " 'Date',\n",
      " 'IsHoliday',\n",
      " 'IsOpen',\n",
      " 'HasPromotions',\n",
      " 'StoreType',\n",
      " 'AssortmentType',\n",
      " 'NearestCompetitor',\n",
      " 'Region',\n",
      " 'NumberOfCustomers',\n",
      " 'NumberOfSales',\n",
      " 'Region_AreaKM2',\n",
      " 'Region_GDP',\n",
      " 'Region_PopulationK',\n",
      " 'CloudCover',\n",
      " 'Events',\n",
      " 'Max_Dew_PointC',\n",
      " 'Max_Gust_SpeedKm_h',\n",
      " 'Max_Humidity',\n",
      " 'Max_Sea_Level_PressurehPa',\n",
      " 'Max_TemperatureC',\n",
      " 'Max_VisibilityKm',\n",
      " 'Max_Wind_SpeedKm_h',\n",
      " 'Mean_Dew_PointC',\n",
      " 'Mean_Humidity',\n",
      " 'Mean_Sea_Level_PressurehPa',\n",
      " 'Mean_TemperatureC',\n",
      " 'Mean_VisibilityKm',\n",
      " 'Mean_Wind_SpeedKm_h',\n",
      " 'Min_Dew_PointC',\n",
      " 'Min_Humidity',\n",
      " 'Min_Sea_Level_PressurehPa',\n",
      " 'Min_TemperatureC',\n",
      " 'Min_VisibilitykM',\n",
      " 'Precipitationmm',\n",
      " 'WindDirDegrees',\n",
      " 'D_Day',\n",
      " 'D_DayOfYear',\n",
      " 'D_Month',\n",
      " 'D_Year',\n",
      " 'D_DayOfweek']\n",
      "\n",
      "\n",
      "SORTED ATTRIBUTES LIST:\n",
      "['AssortmentType',\n",
      " 'CloudCover',\n",
      " 'D_Day',\n",
      " 'D_DayOfYear',\n",
      " 'D_DayOfweek',\n",
      " 'D_Month',\n",
      " 'D_Year',\n",
      " 'Date',\n",
      " 'Events',\n",
      " 'HasPromotions',\n",
      " 'IsHoliday',\n",
      " 'IsOpen',\n",
      " 'Max_Dew_PointC',\n",
      " 'Max_Gust_SpeedKm_h',\n",
      " 'Max_Humidity',\n",
      " 'Max_Sea_Level_PressurehPa',\n",
      " 'Max_TemperatureC',\n",
      " 'Max_VisibilityKm',\n",
      " 'Max_Wind_SpeedKm_h',\n",
      " 'Mean_Dew_PointC',\n",
      " 'Mean_Humidity',\n",
      " 'Mean_Sea_Level_PressurehPa',\n",
      " 'Mean_TemperatureC',\n",
      " 'Mean_VisibilityKm',\n",
      " 'Mean_Wind_SpeedKm_h',\n",
      " 'Min_Dew_PointC',\n",
      " 'Min_Humidity',\n",
      " 'Min_Sea_Level_PressurehPa',\n",
      " 'Min_TemperatureC',\n",
      " 'Min_VisibilitykM',\n",
      " 'NearestCompetitor',\n",
      " 'NumberOfCustomers',\n",
      " 'NumberOfSales',\n",
      " 'Precipitationmm',\n",
      " 'Region',\n",
      " 'Region_AreaKM2',\n",
      " 'Region_GDP',\n",
      " 'Region_PopulationK',\n",
      " 'StoreID',\n",
      " 'StoreType',\n",
      " 'WindDirDegrees']\n"
     ]
    }
   ],
   "source": [
    "print(\"ATTRIBUTES LIST:\")\n",
    "pprint(list(df.columns))\n",
    "\n",
    "print(\"\\n\\nSORTED ATTRIBUTES LIST:\")\n",
    "pprint(sorted(list(df.columns)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Write to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save the dataset\n",
    "df.to_csv('./dataset/preprocessed0_date_' + work_on + '.csv', index=False)"
   ]
  }
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