EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import gc\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import r2_score\n",
    "import lightgbm as lgb\n",
    "from catboost import CatBoostRegressor\n",
    "from tqdm import tqdm_notebook\n",
    "from itertools import product\n",
    "from scipy import stats\n",
    "from scipy.stats import norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales_train = pd.read_csv('sales_train.csv.gz')\n",
    "shops = pd.read_csv('shops.csv')\n",
    "items = pd.read_csv('items.csv')\n",
    "item_cats = pd.read_csv('item_categories.csv')\n",
    "sample_sub = pd.read_csv('sample_submission.csv.gz')\n",
    "test = pd.read_csv('test.csv.gz')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First few rows of data, data statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>date_block_num</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_price</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>59</td>\n",
       "      <td>22154</td>\n",
       "      <td>999.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>03.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2552</td>\n",
       "      <td>899.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>05.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2552</td>\n",
       "      <td>899.00</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2554</td>\n",
       "      <td>1709.05</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2555</td>\n",
       "      <td>1099.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  date_block_num  shop_id  item_id  item_price  item_cnt_day\n",
       "0  02.01.2013               0       59    22154      999.00           1.0\n",
       "1  03.01.2013               0       25     2552      899.00           1.0\n",
       "2  05.01.2013               0       25     2552      899.00          -1.0\n",
       "3  06.01.2013               0       25     2554     1709.05           1.0\n",
       "4  15.01.2013               0       25     2555     1099.00           1.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shop_name</th>\n",
       "      <th>shop_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>!Якутск Орджоникидзе, 56 фран</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>!Якутск ТЦ \"Центральный\" фран</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Адыгея ТЦ \"Мега\"</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Балашиха ТРК \"Октябрь-Киномир\"</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Волжский ТЦ \"Волга Молл\"</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        shop_name  shop_id\n",
       "0   !Якутск Орджоникидзе, 56 фран        0\n",
       "1   !Якутск ТЦ \"Центральный\" фран        1\n",
       "2                Адыгея ТЦ \"Мега\"        2\n",
       "3  Балашиха ТРК \"Октябрь-Киномир\"        3\n",
       "4        Волжский ТЦ \"Волга Молл\"        4"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shops.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_name</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_category_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>! ВО ВЛАСТИ НАВАЖДЕНИЯ (ПЛАСТ.)         D</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>!ABBYY FineReader 12 Professional Edition Full...</td>\n",
       "      <td>1</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>***В ЛУЧАХ СЛАВЫ   (UNV)                    D</td>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>***ГОЛУБАЯ ВОЛНА  (Univ)                      D</td>\n",
       "      <td>3</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>***КОРОБКА (СТЕКЛО)                       D</td>\n",
       "      <td>4</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                           item_name  item_id  \\\n",
       "0          ! ВО ВЛАСТИ НАВАЖДЕНИЯ (ПЛАСТ.)         D        0   \n",
       "1  !ABBYY FineReader 12 Professional Edition Full...        1   \n",
       "2      ***В ЛУЧАХ СЛАВЫ   (UNV)                    D        2   \n",
       "3    ***ГОЛУБАЯ ВОЛНА  (Univ)                      D        3   \n",
       "4        ***КОРОБКА (СТЕКЛО)                       D        4   \n",
       "\n",
       "   item_category_id  \n",
       "0                40  \n",
       "1                76  \n",
       "2                40  \n",
       "3                40  \n",
       "4                40  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_category_name</th>\n",
       "      <th>item_category_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PC - Гарнитуры/Наушники</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Аксессуары - PS2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Аксессуары - PS3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Аксессуары - PS4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Аксессуары - PSP</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "        item_category_name  item_category_id\n",
       "0  PC - Гарнитуры/Наушники                 0\n",
       "1         Аксессуары - PS2                 1\n",
       "2         Аксессуары - PS3                 2\n",
       "3         Аксессуары - PS4                 3\n",
       "4         Аксессуары - PSP                 4"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_cats.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5268</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   ID  shop_id  item_id\n",
       "0   0        5     5037\n",
       "1   1        5     5320\n",
       "2   2        5     5233\n",
       "3   3        5     5232\n",
       "4   4        5     5268"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date_block_num</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_price</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.935849e+06</td>\n",
       "      <td>2.935849e+06</td>\n",
       "      <td>2.935849e+06</td>\n",
       "      <td>2.935849e+06</td>\n",
       "      <td>2.935849e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.456991e+01</td>\n",
       "      <td>3.300173e+01</td>\n",
       "      <td>1.019723e+04</td>\n",
       "      <td>8.908532e+02</td>\n",
       "      <td>1.242641e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.422988e+00</td>\n",
       "      <td>1.622697e+01</td>\n",
       "      <td>6.324297e+03</td>\n",
       "      <td>1.729800e+03</td>\n",
       "      <td>2.618834e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>-2.200000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.000000e+00</td>\n",
       "      <td>2.200000e+01</td>\n",
       "      <td>4.476000e+03</td>\n",
       "      <td>2.490000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.400000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>9.343000e+03</td>\n",
       "      <td>3.990000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.300000e+01</td>\n",
       "      <td>4.700000e+01</td>\n",
       "      <td>1.568400e+04</td>\n",
       "      <td>9.990000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.300000e+01</td>\n",
       "      <td>5.900000e+01</td>\n",
       "      <td>2.216900e+04</td>\n",
       "      <td>3.079800e+05</td>\n",
       "      <td>2.169000e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       date_block_num       shop_id       item_id    item_price  item_cnt_day\n",
       "count    2.935849e+06  2.935849e+06  2.935849e+06  2.935849e+06  2.935849e+06\n",
       "mean     1.456991e+01  3.300173e+01  1.019723e+04  8.908532e+02  1.242641e+00\n",
       "std      9.422988e+00  1.622697e+01  6.324297e+03  1.729800e+03  2.618834e+00\n",
       "min      0.000000e+00  0.000000e+00  0.000000e+00 -1.000000e+00 -2.200000e+01\n",
       "25%      7.000000e+00  2.200000e+01  4.476000e+03  2.490000e+02  1.000000e+00\n",
       "50%      1.400000e+01  3.100000e+01  9.343000e+03  3.990000e+02  1.000000e+00\n",
       "75%      2.300000e+01  4.700000e+01  1.568400e+04  9.990000e+02  1.000000e+00\n",
       "max      3.300000e+01  5.900000e+01  2.216900e+04  3.079800e+05  2.169000e+03"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "\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>shop_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>29.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>17.464249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>14.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>29.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>44.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>59.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         shop_id\n",
       "count  60.000000\n",
       "mean   29.500000\n",
       "std    17.464249\n",
       "min     0.000000\n",
       "25%    14.750000\n",
       "50%    29.500000\n",
       "75%    44.250000\n",
       "max    59.000000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shops.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>item_id</th>\n",
       "      <th>item_category_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>22170.00000</td>\n",
       "      <td>22170.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>11084.50000</td>\n",
       "      <td>46.290753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6400.07207</td>\n",
       "      <td>15.941486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5542.25000</td>\n",
       "      <td>37.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11084.50000</td>\n",
       "      <td>40.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>16626.75000</td>\n",
       "      <td>58.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>22169.00000</td>\n",
       "      <td>83.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           item_id  item_category_id\n",
       "count  22170.00000      22170.000000\n",
       "mean   11084.50000         46.290753\n",
       "std     6400.07207         15.941486\n",
       "min        0.00000          0.000000\n",
       "25%     5542.25000         37.000000\n",
       "50%    11084.50000         40.000000\n",
       "75%    16626.75000         58.000000\n",
       "max    22169.00000         83.000000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2935849 entries, 0 to 2935848\n",
      "Data columns (total 6 columns):\n",
      "date              object\n",
      "date_block_num    int64\n",
      "shop_id           int64\n",
      "item_id           int64\n",
      "item_price        float64\n",
      "item_cnt_day      float64\n",
      "dtypes: float64(2), int64(3), object(1)\n",
      "memory usage: 134.4+ MB\n"
     ]
    }
   ],
   "source": [
    "sales_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downcast data to save memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def downcast_dtypes(df):\n",
    "    '''\n",
    "        Changes column types in the dataframe: \n",
    "                `float64` type to `float32`\n",
    "                `int64`   type to `int32`\n",
    "    '''\n",
    "\n",
    "    # Select columns to downcast\n",
    "    float_cols = [c for c in df if df[c].dtype == \"float64\"]\n",
    "    int_cols =   [c for c in df if df[c].dtype == \"int64\"]\n",
    " \n",
    "    # Downcast\n",
    "    df[float_cols] = df[float_cols].astype(np.float32)\n",
    "    df[int_cols]   = df[int_cols].astype(np.int32)\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales_train=downcast_dtypes(sales_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2935849 entries, 0 to 2935848\n",
      "Data columns (total 6 columns):\n",
      "date              object\n",
      "date_block_num    int32\n",
      "shop_id           int32\n",
      "item_id           int32\n",
      "item_price        float32\n",
      "item_cnt_day      float32\n",
      "dtypes: float32(2), int32(3), object(1)\n",
      "memory usage: 78.4+ MB\n"
     ]
    }
   ],
   "source": [
    "sales_train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "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>feature</th>\n",
       "      <th>null percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>date</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>date_block_num</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>shop_id</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>item_id</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>item_price</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>item_cnt_day</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          feature  null percentage\n",
       "0            date              0.0\n",
       "1  date_block_num              0.0\n",
       "2         shop_id              0.0\n",
       "3         item_id              0.0\n",
       "4      item_price              0.0\n",
       "5    item_cnt_day              0.0"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame({'feature':sales_train.columns.values,'null percentage':np.array([sales_train[a].isnull().sum() for a in sales_train.columns.values])/sales_train.shape[0]})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Histogram of sales_train['item_price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAD8CAYAAACLrvgBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAFZFJREFUeJzt3X+sX3Wd5/Hna1pB118tcDWEki2OzcRqdio2WOPGuDALhUy2TAJJyUQah0knLmw0O8laZpJlRiUZNxnZkCgzzNK1GEdkUZdG6nYaZDKZRIGLIlBZpldkpQNLqwV016gLvveP76fjl8v33vvpvaXf74XnIzk557zP55zz+cC399Xz436bqkKSpB6/Nu4OSJKWD0NDktTN0JAkdTM0JEndDA1JUjdDQ5LUzdCQJHUzNCRJ3QwNSVK3lePuwPF22mmn1dq1a8fdDUlaVu67774fVtXUQu1edqGxdu1apqenx90NSVpWkvyvnnbenpIkdTM0JEndDA1JUjdDQ5LUzdCQJHUzNCRJ3QwNSVI3Q0OS1G3B0Ejy6iT3JPlOkv1J/rTVz0pyd5IDSb6Y5KRWP7mtz7Tta4eOdXWrP5LkgqH65labSbJjqD7yHJKk8ei50vg5cG5V/SawAdicZBPwSeC6qloHPA1c0dpfATxdVW8FrmvtSLIe2Aq8HdgMfCbJiiQrgE8DFwLrgctaW+Y5x8RZu+OOcXdBkl5yC4ZGDfyftvqqNhVwLnBbq+8CLm7LW9o6bft5SdLqt1TVz6vq+8AMcE6bZqrq0ar6BXALsKXtM9c5JElj0PVMo10R3A8cAvYB3wOeqarnWpODwBlt+QzgcYC2/Vng1OH6rH3mqp86zzkkSWPQFRpV9XxVbQDWMLgyeNuoZm2eObYdr/qLJNmeZDrJ9OHDh0c1kSQdB8f09lRVPQP8LbAJWJXk6LfkrgGeaMsHgTMB2vY3AkeG67P2mav+w3nOMbtfN1bVxqraODW14Df7SpIWqeftqakkq9rya4DfAh4G7gIuac22Abe35d1tnbb961VVrb61vV11FrAOuAe4F1jX3pQ6icHD8t1tn7nOIUkag55/T+N0YFd7y+nXgFur6qtJvgvckuQTwLeBm1r7m4DPJZlhcIWxFaCq9ie5Ffgu8BxwZVU9D5DkKmAvsALYWVX727E+Osc5JEljsGBoVNUDwDtH1B9l8Hxjdv1nwKVzHOta4NoR9T3Ant5zSJLGw98IlyR1MzQkSd0MDUlSN0NDktTN0JAkdTM0JEndDA1JUjdDQ5LUzdCQJHUzNCRJ3QwNSVI3Q0OS1M3QkCR1MzQkSd0MDUlSN0NDktTN0JAkdTM0JEndDA1JUjdDQ5LUzdCQJHUzNCRJ3QwNSVI3Q0OS1M3QkCR1WzA0kpyZ5K4kDyfZn+TDrf4nSf4xyf1tumhon6uTzCR5JMkFQ/XNrTaTZMdQ/awkdyc5kOSLSU5q9ZPb+kzbvvZ4Dl6SdGx6rjSeA/6wqt4GbAKuTLK+bbuuqja0aQ9A27YVeDuwGfhMkhVJVgCfBi4E1gOXDR3nk+1Y64CngSta/Qrg6ap6K3BdaydJGpMFQ6Oqnqyqb7XlnwAPA2fMs8sW4Jaq+nlVfR+YAc5p00xVPVpVvwBuAbYkCXAucFvbfxdw8dCxdrXl24DzWvtlYe2OO8bdBUk6ro7pmUa7PfRO4O5WuirJA0l2JlndamcAjw/tdrDV5qqfCjxTVc/Nqr/gWG37s629JGkMukMjyeuALwEfqaofAzcAvw5sAJ4E/vxo0xG71yLq8x1rdt+2J5lOMn348OF5xyFJWryu0EjyKgaB8fmq+jJAVT1VVc9X1S+Bv2Jw+wkGVwpnDu2+BnhinvoPgVVJVs6qv+BYbfsbgSOz+1dVN1bVxqraODU11TMkSdIi9Lw9FeAm4OGq+tRQ/fShZr8DPNSWdwNb25tPZwHrgHuAe4F17U2pkxg8LN9dVQXcBVzS9t8G3D50rG1t+RLg6629JGkMVi7chPcCHwAeTHJ/q/0Rg7efNjC4XfQY8AcAVbU/ya3Adxm8eXVlVT0PkOQqYC+wAthZVfvb8T4K3JLkE8C3GYQUbf65JDMMrjC2LmGskqQlWjA0qurvGf1sYc88+1wLXDuivmfUflX1KL+6vTVc/xlw6UJ9lCSdGP5GuCSpm6EhSepmaEiSuhkakqRuhoYkqZuhIUnqZmhIkroZGpKkboaGJKmboSFJ6mZoSJK6GRqSpG6GhiSpm6EhSepmaEiSuhkakqRuhoYkqZuhIUnqZmhIkroZGpKkboaGJKmboSFJ6mZoSJK6GRqSpG6GhiSp24KhkeTMJHcleTjJ/iQfbvVTkuxLcqDNV7d6klyfZCbJA0nOHjrWttb+QJJtQ/V3JXmw7XN9ksx3DknSePRcaTwH/GFVvQ3YBFyZZD2wA7izqtYBd7Z1gAuBdW3aDtwAgwAArgHeDZwDXDMUAje0tkf329zqc51DkjQGC4ZGVT1ZVd9qyz8BHgbOALYAu1qzXcDFbXkLcHMNfBNYleR04AJgX1UdqaqngX3A5rbtDVX1jaoq4OZZxxp1DknSGBzTM40ka4F3AncDb66qJ2EQLMCbWrMzgMeHdjvYavPVD46oM885JElj0B0aSV4HfAn4SFX9eL6mI2q1iHq3JNuTTCeZPnz48LHsKkk6Bl2hkeRVDALj81X15VZ+qt1aos0PtfpB4Myh3dcATyxQXzOiPt85XqCqbqyqjVW1cWpqqmdIS7J2xx0v+TkkaRL1vD0V4Cbg4ar61NCm3cDRN6C2AbcP1S9vb1FtAp5tt5b2AucnWd0egJ8P7G3bfpJkUzvX5bOONeockqQxWNnR5r3AB4AHk9zfan8E/Blwa5IrgB8Al7Zte4CLgBngp8AHAarqSJKPA/e2dh+rqiNt+UPAZ4HXAF9rE/OcQ5I0BguGRlX9PaOfOwCcN6J9AVfOcaydwM4R9WngHSPqPxp1DknSePgb4ZKkboaGJKmboSFJ6mZoSJK6GRqSpG6GhiSpm6EhSepmaEiSuhkakqRuhoYkqZuhIUnqZmhIkroZGpKkboaGJKmboSFJ6mZoSJK6GRqSpG6GhiSpm6EhSepmaEiSuhkakqRuhoYkqZuhIUnqZmhIkroZGpKkbguGRpKdSQ4leWio9idJ/jHJ/W26aGjb1UlmkjyS5IKh+uZWm0myY6h+VpK7kxxI8sUkJ7X6yW19pm1fe7wGLUlanJ4rjc8Cm0fUr6uqDW3aA5BkPbAVeHvb5zNJViRZAXwauBBYD1zW2gJ8sh1rHfA0cEWrXwE8XVVvBa5r7SRJY7RgaFTV3wFHOo+3Bbilqn5eVd8HZoBz2jRTVY9W1S+AW4AtSQKcC9zW9t8FXDx0rF1t+TbgvNZekjQmS3mmcVWSB9rtq9Wtdgbw+FCbg602V/1U4Jmqem5W/QXHatufbe0lSWOy2NC4Afh1YAPwJPDnrT7qSqAWUZ/vWC+SZHuS6STThw8fnq/fkqQlWFRoVNVTVfV8Vf0S+CsGt59gcKVw5lDTNcAT89R/CKxKsnJW/QXHatvfyBy3yarqxqraWFUbp6amFjMkSVKHRYVGktOHVn8HOPpm1W5ga3vz6SxgHXAPcC+wrr0pdRKDh+W7q6qAu4BL2v7bgNuHjrWtLV8CfL21lySNycqFGiT5AvB+4LQkB4FrgPcn2cDgdtFjwB8AVNX+JLcC3wWeA66squfbca4C9gIrgJ1Vtb+d4qPALUk+AXwbuKnVbwI+l2SGwRXG1iWPVpK0JAuGRlVdNqJ804ja0fbXAteOqO8B9oyoP8qvbm8N138GXLpQ/yRJJ46/ES5J6mZoSJK6GRqSpG6GhiSpm6EhSepmaEiSuhkakqRuhoYkqZuhIUnqZmhIkroZGpKkboaGJKmboSFJ6mZoSJK6GRqSpG6GhiSpm6EhSepmaEiSuhkakqRuhoYkqZuhIUnqZmhIkroZGpKkboaGJKmboSFJ6rZgaCTZmeRQkoeGaqck2ZfkQJuvbvUkuT7JTJIHkpw9tM+21v5Akm1D9XclebDtc32SzHcOSdL49FxpfBbYPKu2A7izqtYBd7Z1gAuBdW3aDtwAgwAArgHeDZwDXDMUAje0tkf327zAOSRJY7JgaFTV3wFHZpW3ALva8i7g4qH6zTXwTWBVktOBC4B9VXWkqp4G9gGb27Y3VNU3qqqAm2cda9Q5JEljsthnGm+uqicB2vxNrX4G8PhQu4OtNl/94Ij6fOeQJI3J8X4QnhG1WkT92E6abE8ynWT68OHDx7q7JKnTYkPjqXZriTY/1OoHgTOH2q0BnligvmZEfb5zvEhV3VhVG6tq49TU1CKHJElayGJDYzdw9A2obcDtQ/XL21tUm4Bn262lvcD5SVa3B+DnA3vbtp8k2dTemrp81rFGnUOSNCYrF2qQ5AvA+4HTkhxk8BbUnwG3JrkC+AFwaWu+B7gImAF+CnwQoKqOJPk4cG9r97GqOvpw/UMM3tB6DfC1NjHPOSRJY7JgaFTVZXNsOm9E2wKunOM4O4GdI+rTwDtG1H806hySpPHxN8IlSd0MDUlSN0NDktTN0DjB1u64Y9xdkKRFMzQkSd0MDUlSN0NDktTN0JhQPvuQNIkMDUlSN0NDktTN0JAkdTM0JEndDA1JUjdDQ5LUzdCQJHUzNCRJ3QwNSVI3Q0OS1M3QkCR1MzQkSd0MDUlSN0NDktTN0JAkdTM0JEndDA1JUrclhUaSx5I8mOT+JNOtdkqSfUkOtPnqVk+S65PMJHkgydlDx9nW2h9Ism2o/q52/Jm2b5bSX0nS0hyPK41/VVUbqmpjW98B3FlV64A72zrAhcC6Nm0HboBByADXAO8GzgGuORo0rc32of02H4f+SpIW6aW4PbUF2NWWdwEXD9VvroFvAquSnA5cAOyrqiNV9TSwD9jctr2hqr5RVQXcPHQsSdIYLDU0CvibJPcl2d5qb66qJwHa/E2tfgbw+NC+B1ttvvrBEXVJ0pgsNTTeW1VnM7j1dGWS983TdtTziFpE/cUHTrYnmU4yffjw4YX6rONk7Y47xt0FSSfYkkKjqp5o80PAVxg8k3iq3VqizQ+15geBM4d2XwM8sUB9zYj6qH7cWFUbq2rj1NTUUoYkSZrHokMjyWuTvP7oMnA+8BCwGzj6BtQ24Pa2vBu4vL1FtQl4tt2+2gucn2R1ewB+PrC3bftJkk3tranLh44lSRqDlUvY983AV9pbsCuBv66q/5HkXuDWJFcAPwAube33ABcBM8BPgQ8CVNWRJB8H7m3tPlZVR9ryh4DPAq8BvtYmSdKYLDo0qupR4DdH1H8EnDeiXsCVcxxrJ7BzRH0aeMdi+yhJOr78jXBJUjdDQ5LUzdCQJHUzNCRJ3QwNSVI3Q0OS1M3QkCR1MzQkSd0MDUlSN0NjiN/aqpeSny+9HBgakqRuhoYkqZuhIUnqZmhIkroZGsuAD1AlTQpDQy85Q096+TA0JEndDA2NhVcf0vJkaEiSuhkakqRuhsZLzNswkl5ODI2XOUNL0vFkaMzySv0h+0odt6RjY2h0Wg4/VJdDHyUtb4bGK5DhMtn8/6NJNvGhkWRzkkeSzCTZMY4+DP8hfjn9gZ60sUxafyS92ESHRpIVwKeBC4H1wGVJ1o+3VwNrd9wx5w+5SfzhN4l9mhT+t5H6TXRoAOcAM1X1aFX9ArgF2HIiTryYHyTHekVytM1c80kxaf1Zit6xLIcxL4c+LsXLfXzL1aSHxhnA40PrB1vtJTX8w3uhIDiWNqNCYXb72dvmCpLZx5yrP73bRrU9lvpivFTH8ofN4iyH/26T3sdx9u9EnTtVdUJOtBhJLgUuqKrfb+sfAM6pqn83q912YHtb/Q3gkUWe8jTgh4vcd9I4lsnzchkHOJZJtZSx/POqmlqo0cpFHvxEOQicObS+BnhidqOquhG4caknSzJdVRuXepxJ4Fgmz8tlHOBYJtWJGMuk3566F1iX5KwkJwFbgd1j7pMkvWJN9JVGVT2X5CpgL7AC2FlV+8fcLUl6xZro0ACoqj3AnhN0uiXf4pogjmXyvFzGAY5lUr3kY5noB+GSpMky6c80JEkTxNBoJuHrShaSZGeSQ0keGqqdkmRfkgNtvrrVk+T6Np4Hkpw9tM+21v5Akm1jGMeZSe5K8nCS/Uk+vIzH8uok9yT5ThvLn7b6WUnubv36YnuRgyQnt/WZtn3t0LGubvVHklxwosfS+rAiybeTfHWZj+OxJA8muT/JdKstu89X68OqJLcl+Z/tz8x7xjqWqnrFTwwesn8PeAtwEvAdYP24+zWin+8DzgYeGqr9J2BHW94BfLItXwR8DQiwCbi71U8BHm3z1W159Qkex+nA2W359cA/MPiamOU4lgCva8uvAu5ufbwV2NrqfwF8qC3/W+Av2vJW4ItteX373J0MnNU+jyvG8Bn798BfA19t68t1HI8Bp82qLbvPV+vHLuD32/JJwKpxjuWEDn5SJ+A9wN6h9auBq8fdrzn6upYXhsYjwOlt+XTgkbb8l8Bls9sBlwF/OVR/Qbsxjel24F8v97EA/wz4FvBuBr9gtXL254vBm4DvacsrW7vM/swNtzuB/V8D3AmcC3y19WvZjaOd9zFeHBrL7vMFvAH4Pu358ySMxdtTA2P5upLj5M1V9SRAm7+p1eca00SNtd3WeCeDv6Evy7G0Wzr3A4eAfQz+dv1MVT03ol//1Oe2/VngVCZjLP8Z+A/AL9v6qSzPcQAU8DdJ7svgGyNgeX6+3gIcBv5ru234X5K8ljGOxdAYyIjacn+tbK4xTcxYk7wO+BLwkar68XxNR9QmZixV9XxVbWDwN/VzgLeNatbmEzmWJL8NHKqq+4bLI5pO9DiGvLeqzmbwDdlXJnnfPG0neSwrGdySvqGq3gn8Xwa3o+byko/F0Bjo+rqSCfVUktMB2vxQq881pokYa5JXMQiMz1fVl1t5WY7lqKp6BvhbBveSVyU5+ntQw/36pz637W8EjjD+sbwX+DdJHmPwbdLnMrjyWG7jAKCqnmjzQ8BXGIT5cvx8HQQOVtXdbf02BiEytrEYGgPL+etKdgNH34TYxuD5wNH65e1tik3As+0ydi9wfpLV7Y2L81vthEkS4Cbg4ar61NCm5TiWqSSr2vJrgN8CHgbuAi5pzWaP5egYLwG+XoObzLuBre2tpLOAdcA9J2YUUFVXV9WaqlrL4PP/9ar6XZbZOACSvDbJ648uM/hcPMQy/HxV1f8GHk/yG610HvBdxjmWE/2AalInBm8d/AOD+9F/PO7+zNHHLwBPAv+Pwd8crmBwH/lO4ECbn9LahsE/YPU94EFg49Bxfg+YadMHxzCOf8ng0vgB4P42XbRMx/IvgG+3sTwE/MdWfwuDH5YzwH8DTm71V7f1mbb9LUPH+uM2xkeAC8f4OXs/v3p7atmNo/X5O23af/TP83L8fLU+bACm22fsvzN4+2lsY/E3wiVJ3bw9JUnqZmhIkroZGpKkboaGJKmboSFJ6mZoSJK6GRqSpG6GhiSp2/8HQS+bU9msnGkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2470c3d6e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(sales_train['item_price'][sales_train['item_price']<=np.percentile(sales_train['item_price'],99)],bins=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.00000e+00, 0.00000e+00, 0.00000e+00, 0.00000e+00, 0.00000e+00,\n",
       "        2.93600e+03, 1.00000e+00, 1.22600e+03, 4.95000e+02, 0.00000e+00,\n",
       "        2.20000e+01, 0.00000e+00, 1.23500e+03, 2.10000e+01, 1.20000e+02,\n",
       "        2.99640e+04, 1.00000e+00, 6.00000e+00, 2.30000e+01, 3.20000e+01,\n",
       "        9.00000e+00, 6.95000e+02, 6.75000e+02, 1.60000e+01, 3.84000e+02,\n",
       "        7.60000e+01, 1.00860e+04, 2.43600e+03, 2.74000e+02, 5.08000e+02,\n",
       "        1.00400e+03, 4.86400e+03, 9.38900e+03, 9.40900e+03, 1.55960e+04,\n",
       "        1.81200e+03, 6.81120e+04, 1.05540e+04, 6.97600e+03, 2.36050e+05,\n",
       "        3.37100e+04, 2.10877e+05, 1.30440e+04, 1.12822e+05, 1.63690e+04,\n",
       "        3.22185e+05, 1.26114e+05, 2.78423e+05, 5.85820e+04, 1.37516e+05,\n",
       "        1.23339e+05, 1.16143e+05, 1.13295e+05, 8.36170e+04, 1.13672e+05,\n",
       "        5.08500e+04, 1.08675e+05, 8.83220e+04, 5.47440e+04, 3.55710e+04,\n",
       "        7.94280e+04, 4.28640e+04, 7.35450e+04, 4.82980e+04, 2.31960e+04,\n",
       "        1.21240e+04, 7.22400e+03, 4.40800e+03, 3.59400e+03, 1.35000e+03,\n",
       "        1.36900e+03, 2.34600e+03, 3.48100e+03, 2.20800e+03, 2.29600e+03,\n",
       "        4.57400e+03, 1.59300e+03, 2.04900e+03, 1.49200e+03, 2.75500e+03,\n",
       "        1.69700e+03, 9.22000e+02, 1.34000e+02, 1.00000e+01, 1.00000e+01,\n",
       "        2.00000e+00, 1.00000e+00, 0.00000e+00, 0.00000e+00, 0.00000e+00,\n",
       "        0.00000e+00, 0.00000e+00, 0.00000e+00, 0.00000e+00, 0.00000e+00,\n",
       "        0.00000e+00, 0.00000e+00, 0.00000e+00, 0.00000e+00, 1.00000e+00]),\n",
       " array([ 0.        ,  0.12637796,  0.25275593,  0.37913389,  0.50551186,\n",
       "         0.63188982,  0.75826778,  0.88464575,  1.01102371,  1.13740168,\n",
       "         1.26377964,  1.3901576 ,  1.51653557,  1.64291353,  1.7692915 ,\n",
       "         1.89566946,  2.02204742,  2.14842539,  2.27480335,  2.40118132,\n",
       "         2.52755928,  2.65393724,  2.78031521,  2.90669317,  3.03307114,\n",
       "         3.1594491 ,  3.28582706,  3.41220503,  3.53858299,  3.66496096,\n",
       "         3.79133892,  3.91771688,  4.04409485,  4.17047281,  4.29685078,\n",
       "         4.42322874,  4.5496067 ,  4.67598467,  4.80236263,  4.9287406 ,\n",
       "         5.05511856,  5.18149652,  5.30787449,  5.43425245,  5.56063042,\n",
       "         5.68700838,  5.81338634,  5.93976431,  6.06614227,  6.19252024,\n",
       "         6.3188982 ,  6.44527617,  6.57165413,  6.69803209,  6.82441006,\n",
       "         6.95078802,  7.07716599,  7.20354395,  7.32992191,  7.45629988,\n",
       "         7.58267784,  7.70905581,  7.83543377,  7.96181173,  8.0881897 ,\n",
       "         8.21456766,  8.34094563,  8.46732359,  8.59370155,  8.72007952,\n",
       "         8.84645748,  8.97283545,  9.09921341,  9.22559137,  9.35196934,\n",
       "         9.4783473 ,  9.60472527,  9.73110323,  9.85748119,  9.98385916,\n",
       "        10.11023712, 10.23661509, 10.36299305, 10.48937101, 10.61574898,\n",
       "        10.74212694, 10.86850491, 10.99488287, 11.12126083, 11.2476388 ,\n",
       "        11.37401676, 11.50039473, 11.62677269, 11.75315065, 11.87952862,\n",
       "        12.00590658, 12.13228455, 12.25866251, 12.38504047, 12.51141844,\n",
       "        12.6377964 ]),\n",
       " <a list of 100 Patch objects>)"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2472ca91160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.log(sales_train['item_price']+2),bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2479d6dc5f8>"
      ]
     },
     "execution_count": 349,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2479d6362e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(sales_train['item_price'][sales_train['item_price']<=np.percentile(sales_train['item_price'],99)], fit=norm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore sales_train['item_price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "299.000000     291352\n",
       "399.000000     242603\n",
       "149.000000     218432\n",
       "199.000000     184044\n",
       "349.000000     101461\n",
       "599.000000      95673\n",
       "999.000000      82784\n",
       "799.000000      77882\n",
       "249.000000      77685\n",
       "699.000000      76493\n",
       "499.000000      73078\n",
       "899.000000      57156\n",
       "1199.000000     55448\n",
       "1999.000000     49672\n",
       "99.000000       48955\n",
       "2599.000000     47857\n",
       "1499.000000     47196\n",
       "449.000000      43205\n",
       "549.000000      39080\n",
       "5.000000        29702\n",
       "2999.000000     28929\n",
       "1299.000000     22381\n",
       "169.000000      20848\n",
       "1699.000000     18924\n",
       "1099.000000     17645\n",
       "749.000000      17351\n",
       "1799.000000     17292\n",
       "2499.000000     16713\n",
       "1399.000000     15694\n",
       "1599.000000     14293\n",
       "                ...  \n",
       "2684.510010         1\n",
       "2678.949951         1\n",
       "2677.571533         1\n",
       "2710.000000         1\n",
       "2710.939941         1\n",
       "2712.110107         1\n",
       "2735.419922         1\n",
       "2750.544922         1\n",
       "2750.510010         1\n",
       "2749.500000         1\n",
       "418.095245          1\n",
       "2748.833252         1\n",
       "2748.500000         1\n",
       "2748.399902         1\n",
       "2747.909180         1\n",
       "2741.307617         1\n",
       "418.299988          1\n",
       "2734.714355         1\n",
       "2714.384521         1\n",
       "2733.782715         1\n",
       "2732.666748         1\n",
       "2729.500000         1\n",
       "2729.024902         1\n",
       "2728.090820         1\n",
       "2724.879883         1\n",
       "2720.209961         1\n",
       "2719.149902         1\n",
       "418.450012          1\n",
       "2718.000000         1\n",
       "511.997498          1\n",
       "Name: item_price, Length: 19992, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train['item_price'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 1.0      2629372\n",
       " 2.0       194201\n",
       " 3.0        47350\n",
       " 4.0        19685\n",
       " 5.0        10474\n",
       "-1.0         7252\n",
       " 6.0         6338\n",
       " 7.0         4057\n",
       " 8.0         2903\n",
       " 9.0         2177\n",
       " 10.0        1820\n",
       " 11.0        1263\n",
       " 12.0        1083\n",
       " 13.0         918\n",
       " 14.0         716\n",
       " 15.0         638\n",
       " 16.0         544\n",
       " 17.0         438\n",
       " 18.0         391\n",
       " 20.0         364\n",
       " 19.0         347\n",
       " 21.0         290\n",
       " 22.0         242\n",
       " 24.0         204\n",
       " 23.0         198\n",
       " 25.0         180\n",
       " 26.0         176\n",
       " 30.0         147\n",
       " 28.0         131\n",
       " 27.0         130\n",
       "           ...   \n",
       " 95.0           1\n",
       " 96.0           1\n",
       " 102.0          1\n",
       " 105.0          1\n",
       " 109.0          1\n",
       " 112.0          1\n",
       " 113.0          1\n",
       " 118.0          1\n",
       " 128.0          1\n",
       " 129.0          1\n",
       " 131.0          1\n",
       " 132.0          1\n",
       " 135.0          1\n",
       " 146.0          1\n",
       " 200.0          1\n",
       " 147.0          1\n",
       " 149.0          1\n",
       " 153.0          1\n",
       " 154.0          1\n",
       " 156.0          1\n",
       " 157.0          1\n",
       " 504.0          1\n",
       " 163.0          1\n",
       " 164.0          1\n",
       " 167.0          1\n",
       " 179.0          1\n",
       " 187.0          1\n",
       " 194.0          1\n",
       " 195.0          1\n",
       " 508.0          1\n",
       "Name: item_cnt_day, Length: 198, dtype: int64"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_count = sales_train['item_cnt_day'].value_counts()\n",
    "sales_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2473fdda780>"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2473f964358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "sales_count = sales_train['item_cnt_day'].value_counts()\n",
    "aaa=np.log(sales_count.values+2)\n",
    "plt.scatter(sales_count.index,aaa)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore the relationship between 'item_cnt_day' and 'month'\n",
    "### In summary:\n",
    "- found seasonality: consider generating features utilizing this seasonality (such as 'prophet' forecasting?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = sales_train.groupby('date',as_index=False)['item_cnt_day'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['month'] = [aa[3:5] for aa in a['date']]\n",
    "a['day'] = [aa[0:2] for aa in a['date']]\n",
    "a['year'] = [aa[6:10] for aa in a['date']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "a['year_month'] = a['year']+'_'+a['month']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = a.groupby('year_month',as_index=False)['item_cnt_day'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "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>year_month</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013_01</td>\n",
       "      <td>131479.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013_02</td>\n",
       "      <td>128090.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013_03</td>\n",
       "      <td>147142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013_04</td>\n",
       "      <td>107190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013_05</td>\n",
       "      <td>106970.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013_06</td>\n",
       "      <td>125381.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013_07</td>\n",
       "      <td>116966.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2013_08</td>\n",
       "      <td>125291.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013_09</td>\n",
       "      <td>133332.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2013_10</td>\n",
       "      <td>127541.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2013_11</td>\n",
       "      <td>130009.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2013_12</td>\n",
       "      <td>183342.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014_01</td>\n",
       "      <td>116899.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014_02</td>\n",
       "      <td>109687.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014_03</td>\n",
       "      <td>115297.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014_04</td>\n",
       "      <td>96556.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014_05</td>\n",
       "      <td>97790.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014_06</td>\n",
       "      <td>97429.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014_07</td>\n",
       "      <td>91280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014_08</td>\n",
       "      <td>102721.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2014_09</td>\n",
       "      <td>99208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2014_10</td>\n",
       "      <td>107422.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2014_11</td>\n",
       "      <td>117845.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2014_12</td>\n",
       "      <td>168755.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2015_01</td>\n",
       "      <td>110971.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2015_02</td>\n",
       "      <td>84198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2015_03</td>\n",
       "      <td>82014.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2015_04</td>\n",
       "      <td>77827.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2015_05</td>\n",
       "      <td>72295.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2015_06</td>\n",
       "      <td>64114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2015_07</td>\n",
       "      <td>63187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2015_08</td>\n",
       "      <td>66079.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2015_09</td>\n",
       "      <td>72843.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2015_10</td>\n",
       "      <td>71056.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year_month  item_cnt_day\n",
       "0     2013_01      131479.0\n",
       "1     2013_02      128090.0\n",
       "2     2013_03      147142.0\n",
       "3     2013_04      107190.0\n",
       "4     2013_05      106970.0\n",
       "5     2013_06      125381.0\n",
       "6     2013_07      116966.0\n",
       "7     2013_08      125291.0\n",
       "8     2013_09      133332.0\n",
       "9     2013_10      127541.0\n",
       "10    2013_11      130009.0\n",
       "11    2013_12      183342.0\n",
       "12    2014_01      116899.0\n",
       "13    2014_02      109687.0\n",
       "14    2014_03      115297.0\n",
       "15    2014_04       96556.0\n",
       "16    2014_05       97790.0\n",
       "17    2014_06       97429.0\n",
       "18    2014_07       91280.0\n",
       "19    2014_08      102721.0\n",
       "20    2014_09       99208.0\n",
       "21    2014_10      107422.0\n",
       "22    2014_11      117845.0\n",
       "23    2014_12      168755.0\n",
       "24    2015_01      110971.0\n",
       "25    2015_02       84198.0\n",
       "26    2015_03       82014.0\n",
       "27    2015_04       77827.0\n",
       "28    2015_05       72295.0\n",
       "29    2015_06       64114.0\n",
       "30    2015_07       63187.0\n",
       "31    2015_08       66079.0\n",
       "32    2015_09       72843.0\n",
       "33    2015_10       71056.0"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.sort_values(by=['year_month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2471b48e3c8>]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2471b032390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[30,10])\n",
    "plt.plot(b['year_month'],b['item_cnt_day'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore any difference between test data distribution and training data distribution:\n",
    "### In summary \n",
    "- test data has some new item_ids not found in training data\n",
    "- test data is missing some shop_ids found in training data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check unique shop_id's in training and test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "       17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "       34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,\n",
       "       51, 52, 53, 54, 55, 56, 57, 58, 59], dtype=int64)"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sort(sales_train.shop_id.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  3,  4,  5,  6,  7, 10, 12, 14, 15, 16, 18, 19, 21, 22, 24, 25,\n",
       "       26, 28, 31, 34, 35, 36, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49,\n",
       "       50, 52, 53, 55, 56, 57, 58, 59], dtype=int64)"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sort(test.shop_id.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test data is missing these shop_id's"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 8, 9, 11, 13, 17, 20, 23, 27, 29, 30, 32, 33, 40, 43, 51, 54]"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x for x in np.sort(sales_train.shop_id.unique()) if x not in np.sort(test.shop_id.unique())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "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>date_block_num</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_price</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>522603.000000</td>\n",
       "      <td>522603.000000</td>\n",
       "      <td>522603.000000</td>\n",
       "      <td>522603.000000</td>\n",
       "      <td>522603.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>11.962618</td>\n",
       "      <td>36.321805</td>\n",
       "      <td>10537.915339</td>\n",
       "      <td>824.074768</td>\n",
       "      <td>1.258692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.393854</td>\n",
       "      <td>14.909747</td>\n",
       "      <td>6323.295740</td>\n",
       "      <td>1586.129761</td>\n",
       "      <td>2.018859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>4870.000000</td>\n",
       "      <td>210.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>10160.000000</td>\n",
       "      <td>399.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>19.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>16069.000000</td>\n",
       "      <td>899.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>22168.000000</td>\n",
       "      <td>35490.000000</td>\n",
       "      <td>502.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       date_block_num        shop_id        item_id     item_price  \\\n",
       "count   522603.000000  522603.000000  522603.000000  522603.000000   \n",
       "mean        11.962618      36.321805   10537.915339     824.074768   \n",
       "std          8.393854      14.909747    6323.295740    1586.129761   \n",
       "min          0.000000       0.000000       0.000000      -1.000000   \n",
       "25%          4.000000      27.000000    4870.000000     210.000000   \n",
       "50%         11.000000      30.000000   10160.000000     399.000000   \n",
       "75%         19.000000      54.000000   16069.000000     899.000000   \n",
       "max         33.000000      54.000000   22168.000000   35490.000000   \n",
       "\n",
       "        item_cnt_day  \n",
       "count  522603.000000  \n",
       "mean        1.258692  \n",
       "std         2.018859  \n",
       "min        -5.000000  \n",
       "25%         1.000000  \n",
       "50%         1.000000  \n",
       "75%         1.000000  \n",
       "max       502.000000  "
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train[sales_train.shop_id.isin([0, 1, 8, 9, 11, 13, 17, 20, 23, 27, 29, 30, 32, 33, 40, 43, 51, 54])].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     522603\n",
       "unique         2\n",
       "top        False\n",
       "freq      301036\n",
       "Name: item_id, dtype: object"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train[sales_train.shop_id.isin([0, 1, 8, 9, 11, 13, 17, 20, 23, 27, 29, 30, 32, 33, 40, 43, 51, 54])]['item_id'].isin(test.item_id).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "221567"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train[sales_train.shop_id.isin([0, 1, 8, 9, 11, 13, 17, 20, 23, 27, 29, 30, 32, 33, 40, 43, 51, 54])]['item_id'].isin(test.item_id).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check difference of shop_id's: test set and validation set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  3,  4,  5,  6,  7,  9, 10, 12, 14, 15, 16, 18, 19, 20, 21, 22,\n",
       "       24, 25, 26, 28, 31, 34, 35, 36, 37, 38, 39, 41, 42, 44, 45, 46, 47,\n",
       "       48, 49, 50, 52, 53, 55, 56, 57, 58, 59], dtype=int64)"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sort(sales_train[sales_train['date_block_num']==33].shop_id.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9, 20]"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x for x in np.sort(sales_train[sales_train['date_block_num']==33].shop_id.unique()) if x not in np.sort(test.shop_id.unique())]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check difference of item_id's: test set and training set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     214200\n",
       "unique         2\n",
       "top         True\n",
       "freq      198954\n",
       "Name: item_id, dtype: object"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.item_id.isin(sales_train.item_id).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scatterplot of 'item_price' and 'item_cnt_day'\n",
    "- found outlier: item_price over 300000, item_cnt_day  over 2000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2479ceccb38>"
      ]
     },
     "execution_count": 324,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2479c839a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(sales_train['item_price'],sales_train['item_cnt_day'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2479b692dd8>"
      ]
     },
     "execution_count": 340,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x247a55c5908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filter = (sales_train['item_price']<300000) & (sales_train['item_cnt_day'] < 2000)\n",
    "plt.scatter(sales_train['item_price'][filter],sales_train['item_cnt_day'][filter])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pairplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x24725651710>"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x247275c08d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(sales_train, size = 2.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x247299407b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrmat = sales_train.corr()\n",
    "sns.heatmap(corrmat, vmin=0, vmax=1, square=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2479470b6a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select first 4 features that correlate with 'item_price' most and draw correlation map with correlation coefficients annotated \n",
    "k=4\n",
    "cols=corrmat.nlargest(k, 'item_price')['item_price'].index\n",
    "cm = sales_train[cols].corr() # or cm = np.corrcoef(sales_train[cols].values.T)\n",
    "sns.set(font_scale=1.25)\n",
    "hm = sns.heatmap(cm, cbar=True, annot=True, square=True, fmt='.2f', annot_kws={'size': 10}, yticklabels=cols.values, xticklabels=cols.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date               object\n",
       "date_block_num      int32\n",
       "shop_id             int32\n",
       "item_id             int32\n",
       "item_price        float32\n",
       "item_cnt_day      float32\n",
       "dtype: object"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Boxplot：1: shop_id vs. item_price; 2: shop_id vs. item_cnt_day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 59.5, 0, 3000)"
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24763f21278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(30, 6))\n",
    "fig = sns.boxplot(x='shop_id', y=\"item_price\", data=sales_train.sort_values(['shop_id']))\n",
    "fig.axis(ymin=0, ymax=3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 59.5, 0, 10)"
      ]
     },
     "execution_count": 321,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2475ae23be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(30, 6))\n",
    "fig2 = sns.boxplot(x='shop_id', y=\"item_cnt_day\", data=sales_train.sort_values(['shop_id']))\n",
    "fig2.axis(ymin=0, ymax=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}