Mini Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disclaimer\n",
    "\n",
    "Ini adalah mini project yang diberikan oleh [Academy DQLab](https://dqlab.id).\n",
    "\n",
    "Dalam kasus ini, perusahaan membutuhkan perbandingan performa dari setiap cabang di berbagai kota. Ambil lima (5) kota terbesar di Pulau Jawa untuk dianalisis dari segi order size, customer count, product count, brand count, dan GMV dalam basis bulanan.\n",
    "\n",
    "Dataset yang diberikan adalah data bersih dari performa cabang perusahaan pada tahun 2019.\n",
    "\n",
    "\n",
    "## Data Penjualan di Setiap Cabang\n",
    "- Diberikan 4 csv files yang isinya retail data untuk tiap Quarter:\n",
    "    - csv (data dari bulan January - March) --> [here](https://dqlab-dataset.s3-ap-southeast-1.amazonaws.com/LO4/retail_data_from_1_until_3.csv)\n",
    "    - csv (data dari bulan April - June) --> [here](https://dqlab-dataset.s3-ap-southeast-1.amazonaws.com/LO4/retail_data_from_4_until_6.csv)\n",
    "    - csv (data dari bulan July - September) --> [here](https://dqlab-dataset.s3-ap-southeast-1.amazonaws.com/LO4/retail_data_from_7_until_9.csv)\n",
    "    - csv (data dari bulan October - December) --> [here](https://dqlab-dataset.s3-ap-southeast-1.amazonaws.com/LO4/retail_data_from_10_until_12.csv)\n",
    "- Goal : Automation untuk pembuatan grafik dari measurement yang dibutuhkan.   \n",
    "\n",
    "## Step by step\n",
    "\n",
    "1. Load masing-masing data *.csv dengan Pandas   \n",
    "2. Pengecekan dan Transformasi Data \n",
    "    - Cek data sekilas (melihat bentuk data biasanya 5 data teratas)\n",
    "    - Cek list kolom untuk semua dataframe apakah seluruh kolom dari keempat dataframe yang terpisah itu sama\n",
    "    - Jika sama digabungkan.\n",
    "    - Cek informasi dataframe yang telah digabungkan\n",
    "    - Statistik deskriptif dari dataframe yang telah digabungkan.   \n",
    "3. Transformasi Data \n",
    "    - Jika ada data yang tidak seharusnya maka dapat dibuang\n",
    "    - Jika ada kolom yang seharusnya bertipe datetime64 ubahlah\n",
    "    - Cek kembali informasi dataframe \n",
    "    - Tampilkan kembali statistik deskriptif dari dataframe\n",
    "4. Filter province yang hanya termasuk 5 provinsi besar di Jawa (DKI Jakarta, Jawa Barat, Jawa Tengah, Jawa Timur, dan Yogyakarta)\n",
    "5. Mengelompokkan data berdasarkan order_date dan province yang sudah difilter dan menghitung order unique count, customer unique count, product unique count, brand unique count, dan GMV (Gross Merchandise Volume = total_price untuk semua penjualan)\n",
    "6. Melakukan unstack untuk mendapatkan order_date di bagian baris dan province di bagian column\n",
    "7. Slicing data untuk masing-masing measurement (kolom), misal: kolom order\n",
    "8. Lakukan resampling pada data tersebut untuk dilakukan perhitungan secara bulanan\n",
    "9. Plot untuk hasil resampling\n",
    "10. Membuat sebuah perulangan dengan dataframe 'unstack_city_province' yang digunakan (hasil dari langkah ke 5)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import library\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load masing-masing data\n",
    "retail_Q1 = pd.read_csv('data/retail_data_from_1_until_3.csv', low_memory=False)\n",
    "retail_Q2 = pd.read_csv('data/retail_data_from_4_until_6.csv', low_memory=False)\n",
    "retail_Q3 = pd.read_csv('data/retail_data_from_7_until_9.csv', low_memory=False)\n",
    "retail_Q4 = pd.read_csv('data/retail_data_from_10_until_12.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Unnamed: 0</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>city</th>\n",
       "      <th>province</th>\n",
       "      <th>product_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>quantity</th>\n",
       "      <th>item_price</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1612339</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>18055</td>\n",
       "      <td>Jakarta Selatan</td>\n",
       "      <td>DKI Jakarta</td>\n",
       "      <td>P0648</td>\n",
       "      <td>BRAND_C</td>\n",
       "      <td>4</td>\n",
       "      <td>1934000</td>\n",
       "      <td>7736000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1612339</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>18055</td>\n",
       "      <td>Jakarta Selatan</td>\n",
       "      <td>DKI Jakarta</td>\n",
       "      <td>P3826</td>\n",
       "      <td>BRAND_V</td>\n",
       "      <td>8</td>\n",
       "      <td>604000</td>\n",
       "      <td>4832000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1612339</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>18055</td>\n",
       "      <td>Jakarta Selatan</td>\n",
       "      <td>DKI Jakarta</td>\n",
       "      <td>P1508</td>\n",
       "      <td>BRAND_G</td>\n",
       "      <td>12</td>\n",
       "      <td>747000</td>\n",
       "      <td>8964000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1612339</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>18055</td>\n",
       "      <td>Jakarta Selatan</td>\n",
       "      <td>DKI Jakarta</td>\n",
       "      <td>P0520</td>\n",
       "      <td>BRAND_B</td>\n",
       "      <td>12</td>\n",
       "      <td>450000</td>\n",
       "      <td>5400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1612339</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>18055</td>\n",
       "      <td>Jakarta Selatan</td>\n",
       "      <td>DKI Jakarta</td>\n",
       "      <td>P1513</td>\n",
       "      <td>BRAND_G</td>\n",
       "      <td>3</td>\n",
       "      <td>1500000</td>\n",
       "      <td>4500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  order_id  order_date  customer_id             city  \\\n",
       "0           0   1612339  2019-01-01        18055  Jakarta Selatan   \n",
       "1           1   1612339  2019-01-01        18055  Jakarta Selatan   \n",
       "2           2   1612339  2019-01-01        18055  Jakarta Selatan   \n",
       "3           3   1612339  2019-01-01        18055  Jakarta Selatan   \n",
       "4           4   1612339  2019-01-01        18055  Jakarta Selatan   \n",
       "\n",
       "      province product_id    brand  quantity  item_price  total_price  \n",
       "0  DKI Jakarta      P0648  BRAND_C         4     1934000      7736000  \n",
       "1  DKI Jakarta      P3826  BRAND_V         8      604000      4832000  \n",
       "2  DKI Jakarta      P1508  BRAND_G        12      747000      8964000  \n",
       "3  DKI Jakarta      P0520  BRAND_B        12      450000      5400000  \n",
       "4  DKI Jakarta      P1513  BRAND_G         3     1500000      4500000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cek data sekilas (tampilkan 5 baris teratas)\n",
    "retail_Q1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kolom retail_data1: Index(['Unnamed: 0', 'order_id', 'order_date', 'customer_id', 'city',\n",
      "       'province', 'product_id', 'brand', 'quantity', 'item_price',\n",
      "       'total_price'],\n",
      "      dtype='object')\n",
      "Kolom retail_data2: Index(['Unnamed: 0', 'order_id', 'order_date', 'customer_id', 'city',\n",
      "       'province', 'product_id', 'brand', 'quantity', 'item_price',\n",
      "       'total_price'],\n",
      "      dtype='object')\n",
      "Kolom retail_data3: Index(['Unnamed: 0', 'order_id', 'order_date', 'customer_id', 'city',\n",
      "       'province', 'product_id', 'brand', 'quantity', 'item_price',\n",
      "       'total_price'],\n",
      "      dtype='object')\n",
      "Kolom retail_data4: Index(['Unnamed: 0', 'order_id', 'order_date', 'customer_id', 'city',\n",
      "       'province', 'product_id', 'brand', 'quantity', 'item_price',\n",
      "       'total_price'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Cek list kolom untuk semua dataframe\n",
    "print('Kolom retail_data1: %s' %retail_Q1.columns)\n",
    "print('Kolom retail_data2: %s' %retail_Q2.columns)\n",
    "print('Kolom retail_data3: %s' %retail_Q3.columns)\n",
    "print('Kolom retail_data4: %s' %retail_Q4.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Jumlah baris: 508557\n"
     ]
    }
   ],
   "source": [
    "# Concat multiple dataframe menjadi 1 dataframe\n",
    "retail_table = pd.concat([retail_Q1, retail_Q2, retail_Q3, retail_Q4])\n",
    "print('\\nJumlah baris:', retail_table.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 508557 entries, 0 to 201825\n",
      "Data columns (total 11 columns):\n",
      " #   Column       Non-Null Count   Dtype \n",
      "---  ------       --------------   ----- \n",
      " 0   Unnamed: 0   508557 non-null  int64 \n",
      " 1   order_id     508557 non-null  object\n",
      " 2   order_date   508557 non-null  object\n",
      " 3   customer_id  508557 non-null  int64 \n",
      " 4   city         508557 non-null  object\n",
      " 5   province     508557 non-null  object\n",
      " 6   product_id   508557 non-null  object\n",
      " 7   brand        508557 non-null  object\n",
      " 8   quantity     508557 non-null  int64 \n",
      " 9   item_price   508557 non-null  int64 \n",
      " 10  total_price  508557 non-null  int64 \n",
      "dtypes: int64(5), object(6)\n",
      "memory usage: 46.6+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# Pengecekan dataframe info\n",
    "print('\\nInfo:')\n",
    "print(retail_table.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistik deskriptif:\n",
      "           Unnamed: 0    customer_id       quantity    item_price   total_price\n",
      "count  508557.000000  508557.000000  508557.000000  5.085570e+05  5.085570e+05\n",
      "mean    71004.479982   11509.957582      10.571326  1.357347e+06  7.043305e+06\n",
      "std     49737.328863    6758.489806     112.805119  1.481544e+07  5.135112e+07\n",
      "min         0.000000       0.000000       1.000000 -3.871709e+09 -3.871709e+09\n",
      "25%     31784.000000   12370.000000       1.000000  4.500000e+05  1.356000e+06\n",
      "50%     63569.000000   14388.000000       4.000000  7.400000e+05  3.498000e+06\n",
      "75%     95509.000000   16261.000000      11.000000  1.458000e+06  6.270000e+06\n",
      "max    201825.000000   18287.000000   74215.000000  4.739478e+09  2.790484e+10\n"
     ]
    }
   ],
   "source": [
    "# Pengecekan statistik deskriptif\n",
    "print('\\nStatistik deskriptif:\\n', retail_table.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Unnamed: 0</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>city</th>\n",
       "      <th>province</th>\n",
       "      <th>product_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>quantity</th>\n",
       "      <th>item_price</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Unnamed: 0, order_id, order_date, customer_id, city, province, product_id, brand, quantity, item_price, total_price]\n",
       "Index: []"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transformasi Data\n",
    "# Memastikan data yang memiliki item_price < 0 atau total_price < 0\n",
    "cek = retail_table.loc[(retail_table['item_price'] < 0) | retail_table['total_price'] < 0]\n",
    "cek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_date</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>city</th>\n",
       "      <th>province</th>\n",
       "      <th>product_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>quantity</th>\n",
       "      <th>item_price</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>83663</th>\n",
       "      <td>83663</td>\n",
       "      <td>undefined</td>\n",
       "      <td>2019-09-06</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>unknown</td>\n",
       "      <td>P0153</td>\n",
       "      <td>BRAND_A</td>\n",
       "      <td>1</td>\n",
       "      <td>3871733000</td>\n",
       "      <td>3871733000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83664</th>\n",
       "      <td>83664</td>\n",
       "      <td>undefined</td>\n",
       "      <td>2019-09-06</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>unknown</td>\n",
       "      <td>P0153</td>\n",
       "      <td>BRAND_A</td>\n",
       "      <td>1</td>\n",
       "      <td>-3871709000</td>\n",
       "      <td>-3871709000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83665</th>\n",
       "      <td>83665</td>\n",
       "      <td>undefined</td>\n",
       "      <td>2019-09-06</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "      <td>unknown</td>\n",
       "      <td>P0153</td>\n",
       "      <td>BRAND_A</td>\n",
       "      <td>1</td>\n",
       "      <td>-3871709000</td>\n",
       "      <td>-3871709000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0   order_id  order_date  customer_id     city province  \\\n",
       "83663       83663  undefined  2019-09-06            0  unknown  unknown   \n",
       "83664       83664  undefined  2019-09-06            0  unknown  unknown   \n",
       "83665       83665  undefined  2019-09-06            0  unknown  unknown   \n",
       "\n",
       "      product_id    brand  quantity  item_price  total_price  \n",
       "83663      P0153  BRAND_A         1  3871733000   3871733000  \n",
       "83664      P0153  BRAND_A         1 -3871709000  -3871709000  \n",
       "83665      P0153  BRAND_A         1 -3871709000  -3871709000  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Jika tidak masuk akal datanya dapat dibuang\n",
    "if cek.shape[0] != 0:\n",
    "    retail_table = retail_table.loc[(retail_table['item_price'] > 0) & (retail_table['total_price'] > 0)]\n",
    "\n",
    "# Cek apakah masih ada order_id yang bernilai undefined dan delete row tersebut\n",
    "cek = retail_table.loc[retail_table['order_id'] == 'undefined']\n",
    "cek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Jika ada maka buang baris tersebut\n",
    "if cek.shape[0] != 0:\n",
    "    retail_table = retail_table.loc[retail_table['order_id'] != 'undefined']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transform order_id menjadi int64\n",
    "retail_table['order_id'] = retail_table['order_id'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transform order_date menjadi datetime Pandas\n",
    "retail_table['order_date'] = pd.to_datetime(retail_table['order_date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 508554 entries, 0 to 201825\n",
      "Data columns (total 11 columns):\n",
      " #   Column       Non-Null Count   Dtype         \n",
      "---  ------       --------------   -----         \n",
      " 0   Unnamed: 0   508554 non-null  int64         \n",
      " 1   order_id     508554 non-null  int64         \n",
      " 2   order_date   508554 non-null  datetime64[ns]\n",
      " 3   customer_id  508554 non-null  int64         \n",
      " 4   city         508554 non-null  object        \n",
      " 5   province     508554 non-null  object        \n",
      " 6   product_id   508554 non-null  object        \n",
      " 7   brand        508554 non-null  object        \n",
      " 8   quantity     508554 non-null  int64         \n",
      " 9   item_price   508554 non-null  int64         \n",
      " 10  total_price  508554 non-null  int64         \n",
      "dtypes: datetime64[ns](1), int64(6), object(4)\n",
      "memory usage: 46.6+ MB\n"
     ]
    }
   ],
   "source": [
    "# Cek dataframe kembali untuk memastikan\n",
    "retail_table.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>Unnamed: 0</th>\n",
       "      <th>order_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>quantity</th>\n",
       "      <th>item_price</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>508554.000000</td>\n",
       "      <td>5.085540e+05</td>\n",
       "      <td>508554.000000</td>\n",
       "      <td>508554.000000</td>\n",
       "      <td>5.085540e+05</td>\n",
       "      <td>5.085540e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>71004.405302</td>\n",
       "      <td>1.680676e+06</td>\n",
       "      <td>11510.025480</td>\n",
       "      <td>10.571383</td>\n",
       "      <td>1.364968e+06</td>\n",
       "      <td>7.050960e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>49737.466061</td>\n",
       "      <td>3.865433e+04</td>\n",
       "      <td>6758.451924</td>\n",
       "      <td>112.805449</td>\n",
       "      <td>1.144767e+07</td>\n",
       "      <td>5.048185e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.612339e+06</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.200000e+04</td>\n",
       "      <td>1.200000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>31784.000000</td>\n",
       "      <td>1.646143e+06</td>\n",
       "      <td>12370.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.500000e+05</td>\n",
       "      <td>1.356000e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>63569.000000</td>\n",
       "      <td>1.682617e+06</td>\n",
       "      <td>14388.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>7.400000e+05</td>\n",
       "      <td>3.498000e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>95509.750000</td>\n",
       "      <td>1.714960e+06</td>\n",
       "      <td>16261.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>1.458000e+06</td>\n",
       "      <td>6.270000e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>201825.000000</td>\n",
       "      <td>1.742998e+06</td>\n",
       "      <td>18287.000000</td>\n",
       "      <td>74215.000000</td>\n",
       "      <td>4.739478e+09</td>\n",
       "      <td>2.790484e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Unnamed: 0      order_id    customer_id       quantity  \\\n",
       "count  508554.000000  5.085540e+05  508554.000000  508554.000000   \n",
       "mean    71004.405302  1.680676e+06   11510.025480      10.571383   \n",
       "std     49737.466061  3.865433e+04    6758.451924     112.805449   \n",
       "min         0.000000  1.612339e+06       0.000000       1.000000   \n",
       "25%     31784.000000  1.646143e+06   12370.000000       1.000000   \n",
       "50%     63569.000000  1.682617e+06   14388.000000       4.000000   \n",
       "75%     95509.750000  1.714960e+06   16261.000000      11.000000   \n",
       "max    201825.000000  1.742998e+06   18287.000000   74215.000000   \n",
       "\n",
       "         item_price   total_price  \n",
       "count  5.085540e+05  5.085540e+05  \n",
       "mean   1.364968e+06  7.050960e+06  \n",
       "std    1.144767e+07  5.048185e+07  \n",
       "min    1.200000e+04  1.200000e+04  \n",
       "25%    4.500000e+05  1.356000e+06  \n",
       "50%    7.400000e+05  3.498000e+06  \n",
       "75%    1.458000e+06  6.270000e+06  \n",
       "max    4.739478e+09  2.790484e+10  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cek statistik deskriptif kembali, untuk memastikan\n",
    "retail_table.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "FILTER 5 PROVINCE TERBESAR DI PULAU JAWA\n",
      "\n",
      "['DKI Jakarta' 'Jawa Barat' 'Jawa Timur' 'Yogyakarta' 'Jawa Tengah']\n"
     ]
    }
   ],
   "source": [
    "# Filter hanya 5 province terbesar di pulau Jawa\n",
    "print('\\nFILTER 5 PROVINCE TERBESAR DI PULAU JAWA\\n')\n",
    "java = ['DKI Jakarta','Jawa Barat','Jawa Tengah','Jawa Timur','Yogyakarta']\n",
    "retail_table = retail_table.loc[retail_table['province'].isin(java)]\n",
    "\n",
    "# Untuk memastikan kolom provinsi isinya sudah sama dengan java\n",
    "print(retail_table['province'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Kelompokkan sesuai dengan order_date dan province kemudian aggregasikan\n",
    "groupby_city_province = retail_table.groupby(['order_date','province']).agg({\n",
    "   'order_id': 'nunique',\n",
    "   'customer_id': 'nunique',\n",
    "   'product_id': 'nunique',\n",
    "   'brand': 'nunique',\n",
    "   'total_price': sum\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>order_date</th>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2019-01-01</th>\n",
       "      <th>DKI Jakarta</th>\n",
       "      <td>34</td>\n",
       "      <td>33</td>\n",
       "      <td>328</td>\n",
       "      <td>22</td>\n",
       "      <td>4717083000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Barat</th>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>136</td>\n",
       "      <td>18</td>\n",
       "      <td>1557289000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Tengah</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>116</td>\n",
       "      <td>20</td>\n",
       "      <td>352052000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Timur</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>83</td>\n",
       "      <td>15</td>\n",
       "      <td>1106603000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yogyakarta</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>88</td>\n",
       "      <td>16</td>\n",
       "      <td>9454007000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2019-12-31</th>\n",
       "      <th>DKI Jakarta</th>\n",
       "      <td>55</td>\n",
       "      <td>53</td>\n",
       "      <td>854</td>\n",
       "      <td>24</td>\n",
       "      <td>7761539000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Barat</th>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>186</td>\n",
       "      <td>21</td>\n",
       "      <td>1148204000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Tengah</th>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>113</td>\n",
       "      <td>17</td>\n",
       "      <td>2017737000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Timur</th>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>279</td>\n",
       "      <td>23</td>\n",
       "      <td>3115149000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yogyakarta</th>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>90</td>\n",
       "      <td>19</td>\n",
       "      <td>728770000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1455 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        order_id  customer_id  product_id  brand  total_price\n",
       "order_date province                                                          \n",
       "2019-01-01 DKI Jakarta        34           33         328     22   4717083000\n",
       "           Jawa Barat         11            9         136     18   1557289000\n",
       "           Jawa Tengah         4            4         116     20    352052000\n",
       "           Jawa Timur          6            6          83     15   1106603000\n",
       "           Yogyakarta          7            4          88     16   9454007000\n",
       "...                          ...          ...         ...    ...          ...\n",
       "2019-12-31 DKI Jakarta        55           53         854     24   7761539000\n",
       "           Jawa Barat         12           11         186     21   1148204000\n",
       "           Jawa Tengah        10            8         113     17   2017737000\n",
       "           Jawa Timur         11           10         279     23   3115149000\n",
       "           Yogyakarta          9            8          90     19    728770000\n",
       "\n",
       "[1455 rows x 5 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_city_province"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>order</th>\n",
       "      <th>customer</th>\n",
       "      <th>product</th>\n",
       "      <th>brand</th>\n",
       "      <th>GMV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>order_date</th>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2019-01-01</th>\n",
       "      <th>DKI Jakarta</th>\n",
       "      <td>34</td>\n",
       "      <td>33</td>\n",
       "      <td>328</td>\n",
       "      <td>22</td>\n",
       "      <td>4717083000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Barat</th>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>136</td>\n",
       "      <td>18</td>\n",
       "      <td>1557289000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Tengah</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>116</td>\n",
       "      <td>20</td>\n",
       "      <td>352052000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Timur</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>83</td>\n",
       "      <td>15</td>\n",
       "      <td>1106603000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yogyakarta</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>88</td>\n",
       "      <td>16</td>\n",
       "      <td>9454007000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2019-01-02</th>\n",
       "      <th>DKI Jakarta</th>\n",
       "      <td>58</td>\n",
       "      <td>50</td>\n",
       "      <td>590</td>\n",
       "      <td>25</td>\n",
       "      <td>6218886000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Barat</th>\n",
       "      <td>17</td>\n",
       "      <td>14</td>\n",
       "      <td>246</td>\n",
       "      <td>21</td>\n",
       "      <td>1458207000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Tengah</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>67</td>\n",
       "      <td>18</td>\n",
       "      <td>968273000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jawa Timur</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>69</td>\n",
       "      <td>17</td>\n",
       "      <td>901676000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yogyakarta</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>238</td>\n",
       "      <td>23</td>\n",
       "      <td>1509057000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        order  customer  product  brand         GMV\n",
       "order_date province                                                \n",
       "2019-01-01 DKI Jakarta     34        33      328     22  4717083000\n",
       "           Jawa Barat      11         9      136     18  1557289000\n",
       "           Jawa Tengah      4         4      116     20   352052000\n",
       "           Jawa Timur       6         6       83     15  1106603000\n",
       "           Yogyakarta       7         4       88     16  9454007000\n",
       "2019-01-02 DKI Jakarta     58        50      590     25  6218886000\n",
       "           Jawa Barat      17        14      246     21  1458207000\n",
       "           Jawa Tengah      8         7       67     18   968273000\n",
       "           Jawa Timur       6         6       69     17   901676000\n",
       "           Yogyakarta      12        12      238     23  1509057000"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ubah nama kolomnya menjadi 'order','customer','product','brand','GMV'\n",
    "groupby_city_province.columns = ['order','customer','product','brand','GMV']\n",
    "groupby_city_province.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th colspan=\"5\" halign=\"left\">order</th>\n",
       "      <th colspan=\"5\" halign=\"left\">customer</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"5\" halign=\"left\">brand</th>\n",
       "      <th colspan=\"5\" halign=\"left\">GMV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>province</th>\n",
       "      <th>DKI Jakarta</th>\n",
       "      <th>Jawa Barat</th>\n",
       "      <th>Jawa Tengah</th>\n",
       "      <th>Jawa Timur</th>\n",
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       "      <th>Jawa Tengah</th>\n",
       "      <th>Jawa Timur</th>\n",
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       "      <th>Jawa Tengah</th>\n",
       "      <th>Jawa Timur</th>\n",
       "      <th>Yogyakarta</th>\n",
       "      <th>DKI Jakarta</th>\n",
       "      <th>Jawa Barat</th>\n",
       "      <th>Jawa Tengah</th>\n",
       "      <th>Jawa Timur</th>\n",
       "      <th>Yogyakarta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>order_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-01</th>\n",
       "      <td>34.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>22.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>4.717083e+09</td>\n",
       "      <td>1.557289e+09</td>\n",
       "      <td>352052000.0</td>\n",
       "      <td>1.106603e+09</td>\n",
       "      <td>9.454007e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-02</th>\n",
       "      <td>58.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>6.218886e+09</td>\n",
       "      <td>1.458207e+09</td>\n",
       "      <td>968273000.0</td>\n",
       "      <td>9.016760e+08</td>\n",
       "      <td>1.509057e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-03</th>\n",
       "      <td>43.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>4.670172e+09</td>\n",
       "      <td>1.797040e+09</td>\n",
       "      <td>663258000.0</td>\n",
       "      <td>1.189519e+09</td>\n",
       "      <td>1.582902e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04</th>\n",
       "      <td>39.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>6.724529e+09</td>\n",
       "      <td>1.805267e+09</td>\n",
       "      <td>710456000.0</td>\n",
       "      <td>2.418780e+08</td>\n",
       "      <td>5.945680e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-06</th>\n",
       "      <td>22.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.483318e+09</td>\n",
       "      <td>1.558771e+09</td>\n",
       "      <td>308975000.0</td>\n",
       "      <td>2.157180e+08</td>\n",
       "      <td>1.221680e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 order                                               \\\n",
       "province   DKI Jakarta Jawa Barat Jawa Tengah Jawa Timur Yogyakarta   \n",
       "order_date                                                            \n",
       "2019-01-01        34.0       11.0         4.0        6.0        7.0   \n",
       "2019-01-02        58.0       17.0         8.0        6.0       12.0   \n",
       "2019-01-03        43.0       13.0         8.0        8.0       10.0   \n",
       "2019-01-04        39.0        9.0        11.0        2.0        3.0   \n",
       "2019-01-06        22.0        9.0         3.0        4.0        2.0   \n",
       "\n",
       "              customer                                               ...  \\\n",
       "province   DKI Jakarta Jawa Barat Jawa Tengah Jawa Timur Yogyakarta  ...   \n",
       "order_date                                                           ...   \n",
       "2019-01-01        33.0        9.0         4.0        6.0        4.0  ...   \n",
       "2019-01-02        50.0       14.0         7.0        6.0       12.0  ...   \n",
       "2019-01-03        40.0       13.0         7.0        6.0        9.0  ...   \n",
       "2019-01-04        25.0        7.0         9.0        2.0        3.0  ...   \n",
       "2019-01-06        22.0        9.0         3.0        3.0        2.0  ...   \n",
       "\n",
       "                 brand                                               \\\n",
       "province   DKI Jakarta Jawa Barat Jawa Tengah Jawa Timur Yogyakarta   \n",
       "order_date                                                            \n",
       "2019-01-01        22.0       18.0        20.0       15.0       16.0   \n",
       "2019-01-02        25.0       21.0        18.0       17.0       23.0   \n",
       "2019-01-03        23.0       22.0        18.0       18.0       23.0   \n",
       "2019-01-04        24.0       18.0        17.0       14.0       19.0   \n",
       "2019-01-06        25.0       23.0        10.0       19.0       12.0   \n",
       "\n",
       "                     GMV                                           \\\n",
       "province     DKI Jakarta    Jawa Barat  Jawa Tengah    Jawa Timur   \n",
       "order_date                                                          \n",
       "2019-01-01  4.717083e+09  1.557289e+09  352052000.0  1.106603e+09   \n",
       "2019-01-02  6.218886e+09  1.458207e+09  968273000.0  9.016760e+08   \n",
       "2019-01-03  4.670172e+09  1.797040e+09  663258000.0  1.189519e+09   \n",
       "2019-01-04  6.724529e+09  1.805267e+09  710456000.0  2.418780e+08   \n",
       "2019-01-06  2.483318e+09  1.558771e+09  308975000.0  2.157180e+08   \n",
       "\n",
       "                          \n",
       "province      Yogyakarta  \n",
       "order_date                \n",
       "2019-01-01  9.454007e+09  \n",
       "2019-01-02  1.509057e+09  \n",
       "2019-01-03  1.582902e+09  \n",
       "2019-01-04  5.945680e+08  \n",
       "2019-01-06  1.221680e+08  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unstack untuk mendapatkan order_date di bagian baris dan province di bagian column\n",
    "unstack_city_province = groupby_city_province.unstack('province').fillna(0)\n",
    "unstack_city_province.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "by order (5 data teratas):\n",
      " province    DKI Jakarta  Jawa Barat  Jawa Tengah  Jawa Timur  Yogyakarta\n",
      "order_date                                                              \n",
      "2019-01-01         34.0        11.0          4.0         6.0         7.0\n",
      "2019-01-02         58.0        17.0          8.0         6.0        12.0\n",
      "2019-01-03         43.0        13.0          8.0         8.0        10.0\n",
      "2019-01-04         39.0         9.0         11.0         2.0         3.0\n",
      "2019-01-06         22.0         9.0          3.0         4.0         2.0\n"
     ]
    }
   ],
   "source": [
    "# Slicing data untuk masing-masing measurement, misal: order\n",
    "idx = pd.IndexSlice['order']\n",
    "by_order = unstack_city_province.loc[:,idx]\n",
    "print('\\nby order (5 data teratas):\\n', by_order.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "by_order_monthly_mean (5 data teratas):\n",
      " province    DKI Jakarta  Jawa Barat  Jawa Tengah  Jawa Timur  Yogyakarta\n",
      "order_date                                                              \n",
      "2019-01-31    27.222222   10.500000     5.111111    3.500000    4.555556\n",
      "2019-02-28    19.083333    7.458333     3.250000    3.208333    2.833333\n",
      "2019-03-31    18.576923    6.615385     3.615385    3.192308    3.038462\n",
      "2019-04-30    22.923077    8.000000     4.038462    3.730769    3.807692\n",
      "2019-05-31    27.318182    9.181818     4.318182    5.181818    5.000000\n"
     ]
    }
   ],
   "source": [
    "# Lakukan resampling pada data tersebut untuk dilakukan perhitungan rata-rata bulanan \n",
    "by_order_monthly_mean = by_order.resample('M').mean()\n",
    "print('\\nby_order_monthly_mean (5 data teratas):\\n', by_order_monthly_mean.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot untuk hasil resampling\n",
    "by_order_monthly_mean.plot(\n",
    "   figsize = (8,5),\n",
    "   title = 'Average Daily order Size in Month View for all Province'\n",
    ")\n",
    "plt.ylabel('avg order size')\n",
    "plt.xlabel('month')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Langah 7 s/d 9 yang telah dilakukan baru untuk satu measurement yaitu order. Berarti ada empat kali lagi kode seperti ini harus dibuat. Karena struktur code masih sama, dapat menggunakan perulangan sesuai dengan jumlah measurement yaitu 5, sehingga kelima measurement dapat ditampilkan grafiknya dalam satu canvas figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x1800 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create figure canvas dan axes for 5 line plots\n",
    "fig, axes = plt.subplots(5, 1, figsize=(8, 25))\n",
    "\n",
    "# Slicing index\n",
    "idx = pd.IndexSlice\n",
    "for i, measurement in enumerate(groupby_city_province.columns):\n",
    "    # Slicing data untuk masing-masing measurement\n",
    "    by_measurement = unstack_city_province.loc[:,idx[measurement]]\n",
    "    # Lakukan resampling pada data tersebut untuk dilakukan perhitungan rata-rata bulanan \n",
    "    by_measurement_monthly_mean = by_measurement.resample('M').mean()\n",
    "    # Plot by_measurement_monthly_mean\n",
    "    by_measurement_monthly_mean.plot(\n",
    "        title = 'Average Daily ' + measurement + ' Size in Month View for all Province',\n",
    "        ax = axes[i]\n",
    "    )\n",
    "    axes[i].set_ylabel('avg ' + measurement + ' size')\n",
    "    axes[i].set_xlabel('month')\n",
    "\n",
    "# Adjust the layout and show the plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}