submission_analisis_data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Proyek Analisis Data: E-Commerce Public Dataset\n",
    "- **Nama:** Rahman Ilyas Al Kahfi\n",
    "- **Email:** ilyasalkahfi98@gmail.com\n",
    "- **ID Dicoding:** kahfii"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Menentukan Pertanyaan Bisnis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Apa saja 5 kategori produk yang paling sering di beli oleh pelanggan e-commerce?\n",
    "- Apa saja 5 daerah yang menjadi target pasar potensial di platform e-commerce?\n",
    "- Di bulan dan tahun berapa e-commerce mencatatkan pendapatan tertinggi dan terendah?\n",
    "- Pelanggan mana yang menjadi pelanggan terbaik berdasarkan RFM Analysis?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Semua Packages/Library yang Digunakan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Wrangling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gathering Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>customer_id</th>\n",
       "      <th>customer_unique_id</th>\n",
       "      <th>customer_zip_code_prefix</th>\n",
       "      <th>customer_city</th>\n",
       "      <th>customer_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06b8999e2fba1a1fbc88172c00ba8bc7</td>\n",
       "      <td>861eff4711a542e4b93843c6dd7febb0</td>\n",
       "      <td>14409</td>\n",
       "      <td>franca</td>\n",
       "      <td>SP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18955e83d337fd6b2def6b18a428ac77</td>\n",
       "      <td>290c77bc529b7ac935b93aa66c333dc3</td>\n",
       "      <td>9790</td>\n",
       "      <td>sao bernardo do campo</td>\n",
       "      <td>SP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4e7b3e00288586ebd08712fdd0374a03</td>\n",
       "      <td>060e732b5b29e8181a18229c7b0b2b5e</td>\n",
       "      <td>1151</td>\n",
       "      <td>sao paulo</td>\n",
       "      <td>SP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b2b6027bc5c5109e529d4dc6358b12c3</td>\n",
       "      <td>259dac757896d24d7702b9acbbff3f3c</td>\n",
       "      <td>8775</td>\n",
       "      <td>mogi das cruzes</td>\n",
       "      <td>SP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4f2d8ab171c80ec8364f7c12e35b23ad</td>\n",
       "      <td>345ecd01c38d18a9036ed96c73b8d066</td>\n",
       "      <td>13056</td>\n",
       "      <td>campinas</td>\n",
       "      <td>SP</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        customer_id                customer_unique_id  \\\n",
       "0  06b8999e2fba1a1fbc88172c00ba8bc7  861eff4711a542e4b93843c6dd7febb0   \n",
       "1  18955e83d337fd6b2def6b18a428ac77  290c77bc529b7ac935b93aa66c333dc3   \n",
       "2  4e7b3e00288586ebd08712fdd0374a03  060e732b5b29e8181a18229c7b0b2b5e   \n",
       "3  b2b6027bc5c5109e529d4dc6358b12c3  259dac757896d24d7702b9acbbff3f3c   \n",
       "4  4f2d8ab171c80ec8364f7c12e35b23ad  345ecd01c38d18a9036ed96c73b8d066   \n",
       "\n",
       "   customer_zip_code_prefix          customer_city customer_state  \n",
       "0                     14409                 franca             SP  \n",
       "1                      9790  sao bernardo do campo             SP  \n",
       "2                      1151              sao paulo             SP  \n",
       "3                      8775        mogi das cruzes             SP  \n",
       "4                     13056               campinas             SP  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_customers = pd.read_csv(\"E-Commerce Public Dataset/customers_dataset.csv\")\n",
    "df_customers.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>order_status</th>\n",
       "      <th>order_purchase_timestamp</th>\n",
       "      <th>order_approved_at</th>\n",
       "      <th>order_delivered_carrier_date</th>\n",
       "      <th>order_delivered_customer_date</th>\n",
       "      <th>order_estimated_delivery_date</th>\n",
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       "      <td>9ef432eb6251297304e76186b10a928d</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-10-02 10:56:33</td>\n",
       "      <td>2017-10-02 11:07:15</td>\n",
       "      <td>2017-10-04 19:55:00</td>\n",
       "      <td>2017-10-10 21:25:13</td>\n",
       "      <td>2017-10-18 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53cdb2fc8bc7dce0b6741e2150273451</td>\n",
       "      <td>b0830fb4747a6c6d20dea0b8c802d7ef</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-07-24 20:41:37</td>\n",
       "      <td>2018-07-26 03:24:27</td>\n",
       "      <td>2018-07-26 14:31:00</td>\n",
       "      <td>2018-08-07 15:27:45</td>\n",
       "      <td>2018-08-13 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>47770eb9100c2d0c44946d9cf07ec65d</td>\n",
       "      <td>41ce2a54c0b03bf3443c3d931a367089</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-08-08 08:38:49</td>\n",
       "      <td>2018-08-08 08:55:23</td>\n",
       "      <td>2018-08-08 13:50:00</td>\n",
       "      <td>2018-08-17 18:06:29</td>\n",
       "      <td>2018-09-04 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>949d5b44dbf5de918fe9c16f97b45f8a</td>\n",
       "      <td>f88197465ea7920adcdbec7375364d82</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-11-18 19:28:06</td>\n",
       "      <td>2017-11-18 19:45:59</td>\n",
       "      <td>2017-11-22 13:39:59</td>\n",
       "      <td>2017-12-02 00:28:42</td>\n",
       "      <td>2017-12-15 00:00:00</td>\n",
       "    </tr>\n",
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       "      <th>4</th>\n",
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       "      <td>8ab97904e6daea8866dbdbc4fb7aad2c</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-02-13 21:18:39</td>\n",
       "      <td>2018-02-13 22:20:29</td>\n",
       "      <td>2018-02-14 19:46:34</td>\n",
       "      <td>2018-02-16 18:17:02</td>\n",
       "      <td>2018-02-26 00:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           order_id                       customer_id  \\\n",
       "0  e481f51cbdc54678b7cc49136f2d6af7  9ef432eb6251297304e76186b10a928d   \n",
       "1  53cdb2fc8bc7dce0b6741e2150273451  b0830fb4747a6c6d20dea0b8c802d7ef   \n",
       "2  47770eb9100c2d0c44946d9cf07ec65d  41ce2a54c0b03bf3443c3d931a367089   \n",
       "3  949d5b44dbf5de918fe9c16f97b45f8a  f88197465ea7920adcdbec7375364d82   \n",
       "4  ad21c59c0840e6cb83a9ceb5573f8159  8ab97904e6daea8866dbdbc4fb7aad2c   \n",
       "\n",
       "  order_status order_purchase_timestamp    order_approved_at  \\\n",
       "0    delivered      2017-10-02 10:56:33  2017-10-02 11:07:15   \n",
       "1    delivered      2018-07-24 20:41:37  2018-07-26 03:24:27   \n",
       "2    delivered      2018-08-08 08:38:49  2018-08-08 08:55:23   \n",
       "3    delivered      2017-11-18 19:28:06  2017-11-18 19:45:59   \n",
       "4    delivered      2018-02-13 21:18:39  2018-02-13 22:20:29   \n",
       "\n",
       "  order_delivered_carrier_date order_delivered_customer_date  \\\n",
       "0          2017-10-04 19:55:00           2017-10-10 21:25:13   \n",
       "1          2018-07-26 14:31:00           2018-08-07 15:27:45   \n",
       "2          2018-08-08 13:50:00           2018-08-17 18:06:29   \n",
       "3          2017-11-22 13:39:59           2017-12-02 00:28:42   \n",
       "4          2018-02-14 19:46:34           2018-02-16 18:17:02   \n",
       "\n",
       "  order_estimated_delivery_date  \n",
       "0           2017-10-18 00:00:00  \n",
       "1           2018-08-13 00:00:00  \n",
       "2           2018-09-04 00:00:00  \n",
       "3           2017-12-15 00:00:00  \n",
       "4           2018-02-26 00:00:00  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_orders = pd.read_csv(\"E-Commerce Public Dataset/orders_dataset.csv\")\n",
    "df_orders.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_item_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>seller_id</th>\n",
       "      <th>shipping_limit_date</th>\n",
       "      <th>price</th>\n",
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       "      <th>0</th>\n",
       "      <td>00010242fe8c5a6d1ba2dd792cb16214</td>\n",
       "      <td>1</td>\n",
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       "      <td>48436dade18ac8b2bce089ec2a041202</td>\n",
       "      <td>2017-09-19 09:45:35</td>\n",
       "      <td>58.90</td>\n",
       "      <td>13.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00018f77f2f0320c557190d7a144bdd3</td>\n",
       "      <td>1</td>\n",
       "      <td>e5f2d52b802189ee658865ca93d83a8f</td>\n",
       "      <td>dd7ddc04e1b6c2c614352b383efe2d36</td>\n",
       "      <td>2017-05-03 11:05:13</td>\n",
       "      <td>239.90</td>\n",
       "      <td>19.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000229ec398224ef6ca0657da4fc703e</td>\n",
       "      <td>1</td>\n",
       "      <td>c777355d18b72b67abbeef9df44fd0fd</td>\n",
       "      <td>5b51032eddd242adc84c38acab88f23d</td>\n",
       "      <td>2018-01-18 14:48:30</td>\n",
       "      <td>199.00</td>\n",
       "      <td>17.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00024acbcdf0a6daa1e931b038114c75</td>\n",
       "      <td>1</td>\n",
       "      <td>7634da152a4610f1595efa32f14722fc</td>\n",
       "      <td>9d7a1d34a5052409006425275ba1c2b4</td>\n",
       "      <td>2018-08-15 10:10:18</td>\n",
       "      <td>12.99</td>\n",
       "      <td>12.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00042b26cf59d7ce69dfabb4e55b4fd9</td>\n",
       "      <td>1</td>\n",
       "      <td>ac6c3623068f30de03045865e4e10089</td>\n",
       "      <td>df560393f3a51e74553ab94004ba5c87</td>\n",
       "      <td>2017-02-13 13:57:51</td>\n",
       "      <td>199.90</td>\n",
       "      <td>18.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "                           order_id  order_item_id  \\\n",
       "0  00010242fe8c5a6d1ba2dd792cb16214              1   \n",
       "1  00018f77f2f0320c557190d7a144bdd3              1   \n",
       "2  000229ec398224ef6ca0657da4fc703e              1   \n",
       "3  00024acbcdf0a6daa1e931b038114c75              1   \n",
       "4  00042b26cf59d7ce69dfabb4e55b4fd9              1   \n",
       "\n",
       "                         product_id                         seller_id  \\\n",
       "0  4244733e06e7ecb4970a6e2683c13e61  48436dade18ac8b2bce089ec2a041202   \n",
       "1  e5f2d52b802189ee658865ca93d83a8f  dd7ddc04e1b6c2c614352b383efe2d36   \n",
       "2  c777355d18b72b67abbeef9df44fd0fd  5b51032eddd242adc84c38acab88f23d   \n",
       "3  7634da152a4610f1595efa32f14722fc  9d7a1d34a5052409006425275ba1c2b4   \n",
       "4  ac6c3623068f30de03045865e4e10089  df560393f3a51e74553ab94004ba5c87   \n",
       "\n",
       "   shipping_limit_date   price  freight_value  \n",
       "0  2017-09-19 09:45:35   58.90          13.29  \n",
       "1  2017-05-03 11:05:13  239.90          19.93  \n",
       "2  2018-01-18 14:48:30  199.00          17.87  \n",
       "3  2018-08-15 10:10:18   12.99          12.79  \n",
       "4  2017-02-13 13:57:51  199.90          18.14  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_order_items = pd.read_csv(\"E-Commerce Public Dataset/order_items_dataset.csv\")\n",
    "df_order_items.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product_id</th>\n",
       "      <th>product_category_name</th>\n",
       "      <th>product_name_lenght</th>\n",
       "      <th>product_description_lenght</th>\n",
       "      <th>product_photos_qty</th>\n",
       "      <th>product_weight_g</th>\n",
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       "      <th>0</th>\n",
       "      <td>1e9e8ef04dbcff4541ed26657ea517e5</td>\n",
       "      <td>perfumaria</td>\n",
       "      <td>40.0</td>\n",
       "      <td>287.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3aa071139cb16b67ca9e5dea641aaa2f</td>\n",
       "      <td>artes</td>\n",
       "      <td>44.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>20.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96bd76ec8810374ed1b65e291975717f</td>\n",
       "      <td>esporte_lazer</td>\n",
       "      <td>46.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cef67bcfe19066a932b7673e239eb23d</td>\n",
       "      <td>bebes</td>\n",
       "      <td>27.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9dc1a7de274444849c219cff195d0b71</td>\n",
       "      <td>utilidades_domesticas</td>\n",
       "      <td>37.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>625.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         product_id  product_category_name  \\\n",
       "0  1e9e8ef04dbcff4541ed26657ea517e5             perfumaria   \n",
       "1  3aa071139cb16b67ca9e5dea641aaa2f                  artes   \n",
       "2  96bd76ec8810374ed1b65e291975717f          esporte_lazer   \n",
       "3  cef67bcfe19066a932b7673e239eb23d                  bebes   \n",
       "4  9dc1a7de274444849c219cff195d0b71  utilidades_domesticas   \n",
       "\n",
       "   product_name_lenght  product_description_lenght  product_photos_qty  \\\n",
       "0                 40.0                       287.0                 1.0   \n",
       "1                 44.0                       276.0                 1.0   \n",
       "2                 46.0                       250.0                 1.0   \n",
       "3                 27.0                       261.0                 1.0   \n",
       "4                 37.0                       402.0                 4.0   \n",
       "\n",
       "   product_weight_g  product_length_cm  product_height_cm  product_width_cm  \n",
       "0             225.0               16.0               10.0              14.0  \n",
       "1            1000.0               30.0               18.0              20.0  \n",
       "2             154.0               18.0                9.0              15.0  \n",
       "3             371.0               26.0                4.0              26.0  \n",
       "4             625.0               20.0               17.0              13.0  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_product = pd.read_csv(\"E-Commerce Public Dataset/products_dataset.csv\")\n",
    "df_product.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>product_category_name</th>\n",
       "      <th>product_category_name_english</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>beleza_saude</td>\n",
       "      <td>health_beauty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>informatica_acessorios</td>\n",
       "      <td>computers_accessories</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>automotivo</td>\n",
       "      <td>auto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cama_mesa_banho</td>\n",
       "      <td>bed_bath_table</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>moveis_decoracao</td>\n",
       "      <td>furniture_decor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product_category_name product_category_name_english\n",
       "0            beleza_saude                 health_beauty\n",
       "1  informatica_acessorios         computers_accessories\n",
       "2              automotivo                          auto\n",
       "3         cama_mesa_banho                bed_bath_table\n",
       "4        moveis_decoracao               furniture_decor"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_product_eng = pd.read_csv(\"E-Commerce Public Dataset/product_category_name_translation.csv\")\n",
    "df_product_eng.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_order_df = pd.merge(\n",
    "    left=df_customers,\n",
    "    right=df_orders,\n",
    "    how=\"inner\",\n",
    "    left_on=\"customer_id\",\n",
    "    right_on=\"customer_id\"\n",
    ").merge(\n",
    "    right=df_order_items,\n",
    "    how=\"inner\",\n",
    "    left_on=\"order_id\",\n",
    "    right_on=\"order_id\"\n",
    ").merge(\n",
    "    right=df_product,\n",
    "    how=\"inner\",\n",
    "    left_on=\"product_id\",\n",
    "    right_on=\"product_id\"\n",
    ").merge(\n",
    "    right=df_product_eng,\n",
    "    how=\"inner\",\n",
    "    left_on=\"product_category_name\",\n",
    "    right_on=\"product_category_name\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>customer_id</th>\n",
       "      <th>customer_unique_id</th>\n",
       "      <th>customer_zip_code_prefix</th>\n",
       "      <th>customer_city</th>\n",
       "      <th>customer_state</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_status</th>\n",
       "      <th>order_purchase_timestamp</th>\n",
       "      <th>order_approved_at</th>\n",
       "      <th>order_delivered_carrier_date</th>\n",
       "      <th>...</th>\n",
       "      <th>freight_value</th>\n",
       "      <th>product_category_name</th>\n",
       "      <th>product_name_lenght</th>\n",
       "      <th>product_description_lenght</th>\n",
       "      <th>product_photos_qty</th>\n",
       "      <th>product_weight_g</th>\n",
       "      <th>product_length_cm</th>\n",
       "      <th>product_height_cm</th>\n",
       "      <th>product_width_cm</th>\n",
       "      <th>product_category_name_english</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06b8999e2fba1a1fbc88172c00ba8bc7</td>\n",
       "      <td>861eff4711a542e4b93843c6dd7febb0</td>\n",
       "      <td>14409</td>\n",
       "      <td>franca</td>\n",
       "      <td>SP</td>\n",
       "      <td>00e7ee1b050b8499577073aeb2a297a1</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-05-16 15:05:35</td>\n",
       "      <td>2017-05-16 15:22:12</td>\n",
       "      <td>2017-05-23 10:47:57</td>\n",
       "      <td>...</td>\n",
       "      <td>21.88</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1141.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8683.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>office_furniture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18955e83d337fd6b2def6b18a428ac77</td>\n",
       "      <td>290c77bc529b7ac935b93aa66c333dc3</td>\n",
       "      <td>9790</td>\n",
       "      <td>sao bernardo do campo</td>\n",
       "      <td>SP</td>\n",
       "      <td>29150127e6685892b6eab3eec79f59c7</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-01-12 20:48:24</td>\n",
       "      <td>2018-01-12 20:58:32</td>\n",
       "      <td>2018-01-15 17:14:59</td>\n",
       "      <td>...</td>\n",
       "      <td>46.48</td>\n",
       "      <td>utilidades_domesticas</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10150.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>housewares</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4e7b3e00288586ebd08712fdd0374a03</td>\n",
       "      <td>060e732b5b29e8181a18229c7b0b2b5e</td>\n",
       "      <td>1151</td>\n",
       "      <td>sao paulo</td>\n",
       "      <td>SP</td>\n",
       "      <td>b2059ed67ce144a36e2aa97d2c9e9ad2</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-05-19 16:07:45</td>\n",
       "      <td>2018-05-20 16:19:10</td>\n",
       "      <td>2018-06-11 14:31:00</td>\n",
       "      <td>...</td>\n",
       "      <td>17.79</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>55.0</td>\n",
       "      <td>955.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8267.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>office_furniture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b2b6027bc5c5109e529d4dc6358b12c3</td>\n",
       "      <td>259dac757896d24d7702b9acbbff3f3c</td>\n",
       "      <td>8775</td>\n",
       "      <td>mogi das cruzes</td>\n",
       "      <td>SP</td>\n",
       "      <td>951670f92359f4fe4a63112aa7306eba</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-03-13 16:06:38</td>\n",
       "      <td>2018-03-13 17:29:19</td>\n",
       "      <td>2018-03-27 23:22:42</td>\n",
       "      <td>...</td>\n",
       "      <td>23.36</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1066.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12160.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>office_furniture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4f2d8ab171c80ec8364f7c12e35b23ad</td>\n",
       "      <td>345ecd01c38d18a9036ed96c73b8d066</td>\n",
       "      <td>13056</td>\n",
       "      <td>campinas</td>\n",
       "      <td>SP</td>\n",
       "      <td>6b7d50bd145f6fc7f33cebabd7e49d0f</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-07-29 09:51:30</td>\n",
       "      <td>2018-07-29 10:10:09</td>\n",
       "      <td>2018-07-30 15:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>22.25</td>\n",
       "      <td>casa_conforto</td>\n",
       "      <td>61.0</td>\n",
       "      <td>407.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5200.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>home_confort</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        customer_id                customer_unique_id  \\\n",
       "0  06b8999e2fba1a1fbc88172c00ba8bc7  861eff4711a542e4b93843c6dd7febb0   \n",
       "1  18955e83d337fd6b2def6b18a428ac77  290c77bc529b7ac935b93aa66c333dc3   \n",
       "2  4e7b3e00288586ebd08712fdd0374a03  060e732b5b29e8181a18229c7b0b2b5e   \n",
       "3  b2b6027bc5c5109e529d4dc6358b12c3  259dac757896d24d7702b9acbbff3f3c   \n",
       "4  4f2d8ab171c80ec8364f7c12e35b23ad  345ecd01c38d18a9036ed96c73b8d066   \n",
       "\n",
       "   customer_zip_code_prefix          customer_city customer_state  \\\n",
       "0                     14409                 franca             SP   \n",
       "1                      9790  sao bernardo do campo             SP   \n",
       "2                      1151              sao paulo             SP   \n",
       "3                      8775        mogi das cruzes             SP   \n",
       "4                     13056               campinas             SP   \n",
       "\n",
       "                           order_id order_status order_purchase_timestamp  \\\n",
       "0  00e7ee1b050b8499577073aeb2a297a1    delivered      2017-05-16 15:05:35   \n",
       "1  29150127e6685892b6eab3eec79f59c7    delivered      2018-01-12 20:48:24   \n",
       "2  b2059ed67ce144a36e2aa97d2c9e9ad2    delivered      2018-05-19 16:07:45   \n",
       "3  951670f92359f4fe4a63112aa7306eba    delivered      2018-03-13 16:06:38   \n",
       "4  6b7d50bd145f6fc7f33cebabd7e49d0f    delivered      2018-07-29 09:51:30   \n",
       "\n",
       "     order_approved_at order_delivered_carrier_date  ... freight_value  \\\n",
       "0  2017-05-16 15:22:12          2017-05-23 10:47:57  ...         21.88   \n",
       "1  2018-01-12 20:58:32          2018-01-15 17:14:59  ...         46.48   \n",
       "2  2018-05-20 16:19:10          2018-06-11 14:31:00  ...         17.79   \n",
       "3  2018-03-13 17:29:19          2018-03-27 23:22:42  ...         23.36   \n",
       "4  2018-07-29 10:10:09          2018-07-30 15:16:00  ...         22.25   \n",
       "\n",
       "   product_category_name  product_name_lenght product_description_lenght  \\\n",
       "0      moveis_escritorio                 41.0                     1141.0   \n",
       "1  utilidades_domesticas                 43.0                     1002.0   \n",
       "2      moveis_escritorio                 55.0                      955.0   \n",
       "3      moveis_escritorio                 48.0                     1066.0   \n",
       "4          casa_conforto                 61.0                      407.0   \n",
       "\n",
       "  product_photos_qty product_weight_g  product_length_cm  product_height_cm  \\\n",
       "0                1.0           8683.0               54.0               64.0   \n",
       "1                3.0          10150.0               89.0               15.0   \n",
       "2                1.0           8267.0               52.0               52.0   \n",
       "3                1.0          12160.0               56.0               51.0   \n",
       "4                1.0           5200.0               45.0               15.0   \n",
       "\n",
       "  product_width_cm  product_category_name_english  \n",
       "0             31.0               office_furniture  \n",
       "1             40.0                     housewares  \n",
       "2             17.0               office_furniture  \n",
       "3             28.0               office_furniture  \n",
       "4             35.0                   home_confort  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_order_df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Assessing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 111023 entries, 0 to 111022\n",
      "Data columns (total 27 columns):\n",
      " #   Column                         Non-Null Count   Dtype  \n",
      "---  ------                         --------------   -----  \n",
      " 0   customer_id                    111023 non-null  object \n",
      " 1   customer_unique_id             111023 non-null  object \n",
      " 2   customer_zip_code_prefix       111023 non-null  int64  \n",
      " 3   customer_city                  111023 non-null  object \n",
      " 4   customer_state                 111023 non-null  object \n",
      " 5   order_id                       111023 non-null  object \n",
      " 6   order_status                   111023 non-null  object \n",
      " 7   order_purchase_timestamp       111023 non-null  object \n",
      " 8   order_approved_at              111009 non-null  object \n",
      " 9   order_delivered_carrier_date   109868 non-null  object \n",
      " 10  order_delivered_customer_date  108637 non-null  object \n",
      " 11  order_estimated_delivery_date  111023 non-null  object \n",
      " 12  order_item_id                  111023 non-null  int64  \n",
      " 13  product_id                     111023 non-null  object \n",
      " 14  seller_id                      111023 non-null  object \n",
      " 15  shipping_limit_date            111023 non-null  object \n",
      " 16  price                          111023 non-null  float64\n",
      " 17  freight_value                  111023 non-null  float64\n",
      " 18  product_category_name          111023 non-null  object \n",
      " 19  product_name_lenght            111023 non-null  float64\n",
      " 20  product_description_lenght     111023 non-null  float64\n",
      " 21  product_photos_qty             111023 non-null  float64\n",
      " 22  product_weight_g               111022 non-null  float64\n",
      " 23  product_length_cm              111022 non-null  float64\n",
      " 24  product_height_cm              111022 non-null  float64\n",
      " 25  product_width_cm               111022 non-null  float64\n",
      " 26  product_category_name_english  111023 non-null  object \n",
      "dtypes: float64(9), int64(2), object(16)\n",
      "memory usage: 22.9+ MB\n"
     ]
    }
   ],
   "source": [
    "new_order_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pengecekkan missing value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customer_id                         0\n",
       "customer_unique_id                  0\n",
       "customer_zip_code_prefix            0\n",
       "customer_city                       0\n",
       "customer_state                      0\n",
       "order_id                            0\n",
       "order_status                        0\n",
       "order_purchase_timestamp            0\n",
       "order_approved_at                  14\n",
       "order_delivered_carrier_date     1155\n",
       "order_delivered_customer_date    2386\n",
       "order_estimated_delivery_date       0\n",
       "order_item_id                       0\n",
       "product_id                          0\n",
       "seller_id                           0\n",
       "shipping_limit_date                 0\n",
       "price                               0\n",
       "freight_value                       0\n",
       "product_category_name               0\n",
       "product_name_lenght                 0\n",
       "product_description_lenght          0\n",
       "product_photos_qty                  0\n",
       "product_weight_g                    1\n",
       "product_length_cm                   1\n",
       "product_height_cm                   1\n",
       "product_width_cm                    1\n",
       "product_category_name_english       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_order_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>customer_zip_code_prefix</th>\n",
       "      <th>order_item_id</th>\n",
       "      <th>price</th>\n",
       "      <th>freight_value</th>\n",
       "      <th>product_name_lenght</th>\n",
       "      <th>product_description_lenght</th>\n",
       "      <th>product_photos_qty</th>\n",
       "      <th>product_weight_g</th>\n",
       "      <th>product_length_cm</th>\n",
       "      <th>product_height_cm</th>\n",
       "      <th>product_width_cm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111023.000000</td>\n",
       "      <td>111022.000000</td>\n",
       "      <td>111022.000000</td>\n",
       "      <td>111022.000000</td>\n",
       "      <td>111022.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>35111.280104</td>\n",
       "      <td>1.198229</td>\n",
       "      <td>120.755104</td>\n",
       "      <td>20.025548</td>\n",
       "      <td>48.774533</td>\n",
       "      <td>787.871549</td>\n",
       "      <td>2.209569</td>\n",
       "      <td>2099.897507</td>\n",
       "      <td>30.212210</td>\n",
       "      <td>16.624966</td>\n",
       "      <td>23.042172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>29854.973997</td>\n",
       "      <td>0.706931</td>\n",
       "      <td>183.372746</td>\n",
       "      <td>15.841472</td>\n",
       "      <td>10.025953</td>\n",
       "      <td>652.169930</td>\n",
       "      <td>1.721428</td>\n",
       "      <td>3754.972723</td>\n",
       "      <td>16.190473</td>\n",
       "      <td>13.468184</td>\n",
       "      <td>11.717712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1003.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>11320.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>39.900000</td>\n",
       "      <td>13.080000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>348.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>24340.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>74.990000</td>\n",
       "      <td>16.310000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>603.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>700.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>59020.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>134.900000</td>\n",
       "      <td>21.180000</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>987.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1800.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>30.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>99980.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>6735.000000</td>\n",
       "      <td>409.680000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>3992.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>40425.000000</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>118.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       customer_zip_code_prefix  order_item_id          price  freight_value  \\\n",
       "count             111023.000000  111023.000000  111023.000000  111023.000000   \n",
       "mean               35111.280104       1.198229     120.755104      20.025548   \n",
       "std                29854.973997       0.706931     183.372746      15.841472   \n",
       "min                 1003.000000       1.000000       0.850000       0.000000   \n",
       "25%                11320.000000       1.000000      39.900000      13.080000   \n",
       "50%                24340.000000       1.000000      74.990000      16.310000   \n",
       "75%                59020.000000       1.000000     134.900000      21.180000   \n",
       "max                99980.000000      21.000000    6735.000000     409.680000   \n",
       "\n",
       "       product_name_lenght  product_description_lenght  product_photos_qty  \\\n",
       "count        111023.000000               111023.000000       111023.000000   \n",
       "mean             48.774533                  787.871549            2.209569   \n",
       "std              10.025953                  652.169930            1.721428   \n",
       "min               5.000000                    4.000000            1.000000   \n",
       "25%              42.000000                  348.000000            1.000000   \n",
       "50%              52.000000                  603.000000            1.000000   \n",
       "75%              57.000000                  987.000000            3.000000   \n",
       "max              76.000000                 3992.000000           20.000000   \n",
       "\n",
       "       product_weight_g  product_length_cm  product_height_cm  \\\n",
       "count     111022.000000      111022.000000      111022.000000   \n",
       "mean        2099.897507          30.212210          16.624966   \n",
       "std         3754.972723          16.190473          13.468184   \n",
       "min            0.000000           7.000000           2.000000   \n",
       "25%          300.000000          18.000000           8.000000   \n",
       "50%          700.000000          25.000000          13.000000   \n",
       "75%         1800.000000          38.000000          20.000000   \n",
       "max        40425.000000         105.000000         105.000000   \n",
       "\n",
       "       product_width_cm  \n",
       "count     111022.000000  \n",
       "mean          23.042172  \n",
       "std           11.717712  \n",
       "min            6.000000  \n",
       "25%           15.000000  \n",
       "50%           20.000000  \n",
       "75%           30.000000  \n",
       "max          118.000000  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_order_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleaning Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>customer_id</th>\n",
       "      <th>customer_unique_id</th>\n",
       "      <th>customer_zip_code_prefix</th>\n",
       "      <th>customer_city</th>\n",
       "      <th>customer_state</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_status</th>\n",
       "      <th>order_purchase_timestamp</th>\n",
       "      <th>order_approved_at</th>\n",
       "      <th>order_delivered_carrier_date</th>\n",
       "      <th>...</th>\n",
       "      <th>product_category_name</th>\n",
       "      <th>product_name_lenght</th>\n",
       "      <th>product_description_lenght</th>\n",
       "      <th>product_photos_qty</th>\n",
       "      <th>product_weight_g</th>\n",
       "      <th>product_length_cm</th>\n",
       "      <th>product_height_cm</th>\n",
       "      <th>product_width_cm</th>\n",
       "      <th>product_category_name_english</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06b8999e2fba1a1fbc88172c00ba8bc7</td>\n",
       "      <td>861eff4711a542e4b93843c6dd7febb0</td>\n",
       "      <td>14409</td>\n",
       "      <td>franca</td>\n",
       "      <td>SP</td>\n",
       "      <td>00e7ee1b050b8499577073aeb2a297a1</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-05-16 15:05:35</td>\n",
       "      <td>2017-05-16 15:22:12</td>\n",
       "      <td>2017-05-23 10:47:57</td>\n",
       "      <td>...</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1141.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8683.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>146.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18955e83d337fd6b2def6b18a428ac77</td>\n",
       "      <td>290c77bc529b7ac935b93aa66c333dc3</td>\n",
       "      <td>9790</td>\n",
       "      <td>sao bernardo do campo</td>\n",
       "      <td>SP</td>\n",
       "      <td>29150127e6685892b6eab3eec79f59c7</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-01-12 20:48:24</td>\n",
       "      <td>2018-01-12 20:58:32</td>\n",
       "      <td>2018-01-15 17:14:59</td>\n",
       "      <td>...</td>\n",
       "      <td>utilidades_domesticas</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10150.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>housewares</td>\n",
       "      <td>335.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4e7b3e00288586ebd08712fdd0374a03</td>\n",
       "      <td>060e732b5b29e8181a18229c7b0b2b5e</td>\n",
       "      <td>1151</td>\n",
       "      <td>sao paulo</td>\n",
       "      <td>SP</td>\n",
       "      <td>b2059ed67ce144a36e2aa97d2c9e9ad2</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-05-19 16:07:45</td>\n",
       "      <td>2018-05-20 16:19:10</td>\n",
       "      <td>2018-06-11 14:31:00</td>\n",
       "      <td>...</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>55.0</td>\n",
       "      <td>955.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8267.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>157.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b2b6027bc5c5109e529d4dc6358b12c3</td>\n",
       "      <td>259dac757896d24d7702b9acbbff3f3c</td>\n",
       "      <td>8775</td>\n",
       "      <td>mogi das cruzes</td>\n",
       "      <td>SP</td>\n",
       "      <td>951670f92359f4fe4a63112aa7306eba</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-03-13 16:06:38</td>\n",
       "      <td>2018-03-13 17:29:19</td>\n",
       "      <td>2018-03-27 23:22:42</td>\n",
       "      <td>...</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1066.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12160.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>173.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4f2d8ab171c80ec8364f7c12e35b23ad</td>\n",
       "      <td>345ecd01c38d18a9036ed96c73b8d066</td>\n",
       "      <td>13056</td>\n",
       "      <td>campinas</td>\n",
       "      <td>SP</td>\n",
       "      <td>6b7d50bd145f6fc7f33cebabd7e49d0f</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-07-29 09:51:30</td>\n",
       "      <td>2018-07-29 10:10:09</td>\n",
       "      <td>2018-07-30 15:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>casa_conforto</td>\n",
       "      <td>61.0</td>\n",
       "      <td>407.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5200.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>home_confort</td>\n",
       "      <td>252.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        customer_id                customer_unique_id  \\\n",
       "0  06b8999e2fba1a1fbc88172c00ba8bc7  861eff4711a542e4b93843c6dd7febb0   \n",
       "1  18955e83d337fd6b2def6b18a428ac77  290c77bc529b7ac935b93aa66c333dc3   \n",
       "2  4e7b3e00288586ebd08712fdd0374a03  060e732b5b29e8181a18229c7b0b2b5e   \n",
       "3  b2b6027bc5c5109e529d4dc6358b12c3  259dac757896d24d7702b9acbbff3f3c   \n",
       "4  4f2d8ab171c80ec8364f7c12e35b23ad  345ecd01c38d18a9036ed96c73b8d066   \n",
       "\n",
       "   customer_zip_code_prefix          customer_city customer_state  \\\n",
       "0                     14409                 franca             SP   \n",
       "1                      9790  sao bernardo do campo             SP   \n",
       "2                      1151              sao paulo             SP   \n",
       "3                      8775        mogi das cruzes             SP   \n",
       "4                     13056               campinas             SP   \n",
       "\n",
       "                           order_id order_status order_purchase_timestamp  \\\n",
       "0  00e7ee1b050b8499577073aeb2a297a1    delivered      2017-05-16 15:05:35   \n",
       "1  29150127e6685892b6eab3eec79f59c7    delivered      2018-01-12 20:48:24   \n",
       "2  b2059ed67ce144a36e2aa97d2c9e9ad2    delivered      2018-05-19 16:07:45   \n",
       "3  951670f92359f4fe4a63112aa7306eba    delivered      2018-03-13 16:06:38   \n",
       "4  6b7d50bd145f6fc7f33cebabd7e49d0f    delivered      2018-07-29 09:51:30   \n",
       "\n",
       "     order_approved_at order_delivered_carrier_date  ...  \\\n",
       "0  2017-05-16 15:22:12          2017-05-23 10:47:57  ...   \n",
       "1  2018-01-12 20:58:32          2018-01-15 17:14:59  ...   \n",
       "2  2018-05-20 16:19:10          2018-06-11 14:31:00  ...   \n",
       "3  2018-03-13 17:29:19          2018-03-27 23:22:42  ...   \n",
       "4  2018-07-29 10:10:09          2018-07-30 15:16:00  ...   \n",
       "\n",
       "   product_category_name product_name_lenght  product_description_lenght  \\\n",
       "0      moveis_escritorio                41.0                      1141.0   \n",
       "1  utilidades_domesticas                43.0                      1002.0   \n",
       "2      moveis_escritorio                55.0                       955.0   \n",
       "3      moveis_escritorio                48.0                      1066.0   \n",
       "4          casa_conforto                61.0                       407.0   \n",
       "\n",
       "  product_photos_qty product_weight_g product_length_cm  product_height_cm  \\\n",
       "0                1.0           8683.0              54.0               64.0   \n",
       "1                3.0          10150.0              89.0               15.0   \n",
       "2                1.0           8267.0              52.0               52.0   \n",
       "3                1.0          12160.0              56.0               51.0   \n",
       "4                1.0           5200.0              45.0               15.0   \n",
       "\n",
       "   product_width_cm product_category_name_english  total_price  \n",
       "0              31.0              office_furniture       146.87  \n",
       "1              40.0                    housewares       335.48  \n",
       "2              17.0              office_furniture       157.73  \n",
       "3              28.0              office_furniture       173.30  \n",
       "4              35.0                  home_confort       252.25  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_order_df[\"total_price\"] = new_order_df[\"price\"] + new_order_df[\"freight_value\"]\n",
    "new_order_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['SP' 'SC' 'PR' 'MG' 'RJ' 'RS' 'PA' 'GO' 'ES' 'BA' 'MA' 'MS' 'CE' 'DF'\n",
      " 'RN' 'PE' 'MT' 'AM' 'AP' 'AL' 'RO' 'PB' 'TO' 'PI' 'AC' 'SE' 'RR']\n"
     ]
    }
   ],
   "source": [
    "customer_state = new_order_df['customer_state'].unique()\n",
    "print(customer_state)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ilyas\\AppData\\Local\\Temp\\ipykernel_2344\\3310572498.py:30: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
      "\n",
      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
      "\n",
      "\n",
      "  new_order_df['customer_state'].replace(name_of_state,inplace=True)\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>customer_id</th>\n",
       "      <th>customer_unique_id</th>\n",
       "      <th>customer_zip_code_prefix</th>\n",
       "      <th>customer_city</th>\n",
       "      <th>customer_state</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_status</th>\n",
       "      <th>order_purchase_timestamp</th>\n",
       "      <th>order_approved_at</th>\n",
       "      <th>order_delivered_carrier_date</th>\n",
       "      <th>...</th>\n",
       "      <th>product_category_name</th>\n",
       "      <th>product_name_lenght</th>\n",
       "      <th>product_description_lenght</th>\n",
       "      <th>product_photos_qty</th>\n",
       "      <th>product_weight_g</th>\n",
       "      <th>product_length_cm</th>\n",
       "      <th>product_height_cm</th>\n",
       "      <th>product_width_cm</th>\n",
       "      <th>product_category_name_english</th>\n",
       "      <th>total_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06b8999e2fba1a1fbc88172c00ba8bc7</td>\n",
       "      <td>861eff4711a542e4b93843c6dd7febb0</td>\n",
       "      <td>14409</td>\n",
       "      <td>franca</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>00e7ee1b050b8499577073aeb2a297a1</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-05-16 15:05:35</td>\n",
       "      <td>2017-05-16 15:22:12</td>\n",
       "      <td>2017-05-23 10:47:57</td>\n",
       "      <td>...</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1141.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8683.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>146.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18955e83d337fd6b2def6b18a428ac77</td>\n",
       "      <td>290c77bc529b7ac935b93aa66c333dc3</td>\n",
       "      <td>9790</td>\n",
       "      <td>sao bernardo do campo</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>29150127e6685892b6eab3eec79f59c7</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-01-12 20:48:24</td>\n",
       "      <td>2018-01-12 20:58:32</td>\n",
       "      <td>2018-01-15 17:14:59</td>\n",
       "      <td>...</td>\n",
       "      <td>utilidades_domesticas</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10150.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>housewares</td>\n",
       "      <td>335.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4e7b3e00288586ebd08712fdd0374a03</td>\n",
       "      <td>060e732b5b29e8181a18229c7b0b2b5e</td>\n",
       "      <td>1151</td>\n",
       "      <td>sao paulo</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>b2059ed67ce144a36e2aa97d2c9e9ad2</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-05-19 16:07:45</td>\n",
       "      <td>2018-05-20 16:19:10</td>\n",
       "      <td>2018-06-11 14:31:00</td>\n",
       "      <td>...</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>55.0</td>\n",
       "      <td>955.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8267.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>157.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b2b6027bc5c5109e529d4dc6358b12c3</td>\n",
       "      <td>259dac757896d24d7702b9acbbff3f3c</td>\n",
       "      <td>8775</td>\n",
       "      <td>mogi das cruzes</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>951670f92359f4fe4a63112aa7306eba</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-03-13 16:06:38</td>\n",
       "      <td>2018-03-13 17:29:19</td>\n",
       "      <td>2018-03-27 23:22:42</td>\n",
       "      <td>...</td>\n",
       "      <td>moveis_escritorio</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1066.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12160.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>173.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4f2d8ab171c80ec8364f7c12e35b23ad</td>\n",
       "      <td>345ecd01c38d18a9036ed96c73b8d066</td>\n",
       "      <td>13056</td>\n",
       "      <td>campinas</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>6b7d50bd145f6fc7f33cebabd7e49d0f</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-07-29 09:51:30</td>\n",
       "      <td>2018-07-29 10:10:09</td>\n",
       "      <td>2018-07-30 15:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>casa_conforto</td>\n",
       "      <td>61.0</td>\n",
       "      <td>407.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5200.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>home_confort</td>\n",
       "      <td>252.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        customer_id                customer_unique_id  \\\n",
       "0  06b8999e2fba1a1fbc88172c00ba8bc7  861eff4711a542e4b93843c6dd7febb0   \n",
       "1  18955e83d337fd6b2def6b18a428ac77  290c77bc529b7ac935b93aa66c333dc3   \n",
       "2  4e7b3e00288586ebd08712fdd0374a03  060e732b5b29e8181a18229c7b0b2b5e   \n",
       "3  b2b6027bc5c5109e529d4dc6358b12c3  259dac757896d24d7702b9acbbff3f3c   \n",
       "4  4f2d8ab171c80ec8364f7c12e35b23ad  345ecd01c38d18a9036ed96c73b8d066   \n",
       "\n",
       "   customer_zip_code_prefix          customer_city customer_state  \\\n",
       "0                     14409                 franca      São Paulo   \n",
       "1                      9790  sao bernardo do campo      São Paulo   \n",
       "2                      1151              sao paulo      São Paulo   \n",
       "3                      8775        mogi das cruzes      São Paulo   \n",
       "4                     13056               campinas      São Paulo   \n",
       "\n",
       "                           order_id order_status order_purchase_timestamp  \\\n",
       "0  00e7ee1b050b8499577073aeb2a297a1    delivered      2017-05-16 15:05:35   \n",
       "1  29150127e6685892b6eab3eec79f59c7    delivered      2018-01-12 20:48:24   \n",
       "2  b2059ed67ce144a36e2aa97d2c9e9ad2    delivered      2018-05-19 16:07:45   \n",
       "3  951670f92359f4fe4a63112aa7306eba    delivered      2018-03-13 16:06:38   \n",
       "4  6b7d50bd145f6fc7f33cebabd7e49d0f    delivered      2018-07-29 09:51:30   \n",
       "\n",
       "     order_approved_at order_delivered_carrier_date  ...  \\\n",
       "0  2017-05-16 15:22:12          2017-05-23 10:47:57  ...   \n",
       "1  2018-01-12 20:58:32          2018-01-15 17:14:59  ...   \n",
       "2  2018-05-20 16:19:10          2018-06-11 14:31:00  ...   \n",
       "3  2018-03-13 17:29:19          2018-03-27 23:22:42  ...   \n",
       "4  2018-07-29 10:10:09          2018-07-30 15:16:00  ...   \n",
       "\n",
       "   product_category_name product_name_lenght  product_description_lenght  \\\n",
       "0      moveis_escritorio                41.0                      1141.0   \n",
       "1  utilidades_domesticas                43.0                      1002.0   \n",
       "2      moveis_escritorio                55.0                       955.0   \n",
       "3      moveis_escritorio                48.0                      1066.0   \n",
       "4          casa_conforto                61.0                       407.0   \n",
       "\n",
       "  product_photos_qty product_weight_g product_length_cm  product_height_cm  \\\n",
       "0                1.0           8683.0              54.0               64.0   \n",
       "1                3.0          10150.0              89.0               15.0   \n",
       "2                1.0           8267.0              52.0               52.0   \n",
       "3                1.0          12160.0              56.0               51.0   \n",
       "4                1.0           5200.0              45.0               15.0   \n",
       "\n",
       "   product_width_cm product_category_name_english  total_price  \n",
       "0              31.0              office_furniture       146.87  \n",
       "1              40.0                    housewares       335.48  \n",
       "2              17.0              office_furniture       157.73  \n",
       "3              28.0              office_furniture       173.30  \n",
       "4              35.0                  home_confort       252.25  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name_of_state = {\n",
    "    \"AC\": \"Acre\",\n",
    "\"AL\" : \"Alagoas\",\n",
    "\"AM\" : \"Amazonas\",\n",
    "\"AP\" : \"Amapá\",\n",
    "\"BA\" : \"Bahia\",\n",
    "\"CE\" : \"Ceará\",\n",
    "\"DF\" : \"Distrito Federal\",\n",
    "\"ES\" : \"Espírito Santo\",\n",
    "\"GO\" : \"Goiás\",\n",
    "\"MA\" : \"Maranhão\",\n",
    "\"MG\" : \"Minas Gerais\",\n",
    "\"MS\" : \"Mato Grosso do Sul\",\n",
    "\"MT\" : \"Mato Grosso\",\n",
    "\"PA\" : \"Pará\",\n",
    "\"PB\" : \"Paraíba\",\n",
    "\"PE\" : \"Pernambuco\",\n",
    "\"PI\" : \"Piauí\",\n",
    "\"PR\" : \"Paraná\",\n",
    "\"RJ\" : \"Rio de Janeiro\",\n",
    "\"RN\" : \"Rio Grande do Norte\",\n",
    "\"RO\" : \"Rondônia\",\n",
    "\"RR\" : \"Roraima\",\n",
    "\"RS\" : \"Rio Grande do Sul\",\n",
    "\"SC\" : \"Santa Catarina\",\n",
    "\"SE\" : \"Sergipe\",\n",
    "\"SP\" : \"São Paulo\",\n",
    "\"TO\" : \"Tocantins\",\n",
    "}\n",
    "new_order_df['customer_state'].replace(name_of_state,inplace=True)\n",
    "new_order_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>customer_id</th>\n",
       "      <th>customer_unique_id</th>\n",
       "      <th>customer_zip_code_prefix</th>\n",
       "      <th>customer_city</th>\n",
       "      <th>customer_state</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_status</th>\n",
       "      <th>order_purchase_timestamp</th>\n",
       "      <th>order_approved_at</th>\n",
       "      <th>order_delivered_carrier_date</th>\n",
       "      <th>...</th>\n",
       "      <th>product_weight_g</th>\n",
       "      <th>product_length_cm</th>\n",
       "      <th>product_height_cm</th>\n",
       "      <th>product_width_cm</th>\n",
       "      <th>product_category_name_english</th>\n",
       "      <th>total_price</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06b8999e2fba1a1fbc88172c00ba8bc7</td>\n",
       "      <td>861eff4711a542e4b93843c6dd7febb0</td>\n",
       "      <td>14409</td>\n",
       "      <td>franca</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>00e7ee1b050b8499577073aeb2a297a1</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-05-16 15:05:35</td>\n",
       "      <td>2017-05-16 15:22:12</td>\n",
       "      <td>2017-05-23 10:47:57</td>\n",
       "      <td>...</td>\n",
       "      <td>8683.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>146.87</td>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>15:05:35</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18955e83d337fd6b2def6b18a428ac77</td>\n",
       "      <td>290c77bc529b7ac935b93aa66c333dc3</td>\n",
       "      <td>9790</td>\n",
       "      <td>sao bernardo do campo</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>29150127e6685892b6eab3eec79f59c7</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-01-12 20:48:24</td>\n",
       "      <td>2018-01-12 20:58:32</td>\n",
       "      <td>2018-01-15 17:14:59</td>\n",
       "      <td>...</td>\n",
       "      <td>10150.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>housewares</td>\n",
       "      <td>335.48</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>20:48:24</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4e7b3e00288586ebd08712fdd0374a03</td>\n",
       "      <td>060e732b5b29e8181a18229c7b0b2b5e</td>\n",
       "      <td>1151</td>\n",
       "      <td>sao paulo</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>b2059ed67ce144a36e2aa97d2c9e9ad2</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-05-19 16:07:45</td>\n",
       "      <td>2018-05-20 16:19:10</td>\n",
       "      <td>2018-06-11 14:31:00</td>\n",
       "      <td>...</td>\n",
       "      <td>8267.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>157.73</td>\n",
       "      <td>2018-05-19</td>\n",
       "      <td>16:07:45</td>\n",
       "      <td>2018</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b2b6027bc5c5109e529d4dc6358b12c3</td>\n",
       "      <td>259dac757896d24d7702b9acbbff3f3c</td>\n",
       "      <td>8775</td>\n",
       "      <td>mogi das cruzes</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>951670f92359f4fe4a63112aa7306eba</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-03-13 16:06:38</td>\n",
       "      <td>2018-03-13 17:29:19</td>\n",
       "      <td>2018-03-27 23:22:42</td>\n",
       "      <td>...</td>\n",
       "      <td>12160.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>173.30</td>\n",
       "      <td>2018-03-13</td>\n",
       "      <td>16:06:38</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4f2d8ab171c80ec8364f7c12e35b23ad</td>\n",
       "      <td>345ecd01c38d18a9036ed96c73b8d066</td>\n",
       "      <td>13056</td>\n",
       "      <td>campinas</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>6b7d50bd145f6fc7f33cebabd7e49d0f</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-07-29 09:51:30</td>\n",
       "      <td>2018-07-29 10:10:09</td>\n",
       "      <td>2018-07-30 15:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>5200.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>home_confort</td>\n",
       "      <td>252.25</td>\n",
       "      <td>2018-07-29</td>\n",
       "      <td>09:51:30</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        customer_id                customer_unique_id  \\\n",
       "0  06b8999e2fba1a1fbc88172c00ba8bc7  861eff4711a542e4b93843c6dd7febb0   \n",
       "1  18955e83d337fd6b2def6b18a428ac77  290c77bc529b7ac935b93aa66c333dc3   \n",
       "2  4e7b3e00288586ebd08712fdd0374a03  060e732b5b29e8181a18229c7b0b2b5e   \n",
       "3  b2b6027bc5c5109e529d4dc6358b12c3  259dac757896d24d7702b9acbbff3f3c   \n",
       "4  4f2d8ab171c80ec8364f7c12e35b23ad  345ecd01c38d18a9036ed96c73b8d066   \n",
       "\n",
       "   customer_zip_code_prefix          customer_city customer_state  \\\n",
       "0                     14409                 franca      São Paulo   \n",
       "1                      9790  sao bernardo do campo      São Paulo   \n",
       "2                      1151              sao paulo      São Paulo   \n",
       "3                      8775        mogi das cruzes      São Paulo   \n",
       "4                     13056               campinas      São Paulo   \n",
       "\n",
       "                           order_id order_status order_purchase_timestamp  \\\n",
       "0  00e7ee1b050b8499577073aeb2a297a1    delivered      2017-05-16 15:05:35   \n",
       "1  29150127e6685892b6eab3eec79f59c7    delivered      2018-01-12 20:48:24   \n",
       "2  b2059ed67ce144a36e2aa97d2c9e9ad2    delivered      2018-05-19 16:07:45   \n",
       "3  951670f92359f4fe4a63112aa7306eba    delivered      2018-03-13 16:06:38   \n",
       "4  6b7d50bd145f6fc7f33cebabd7e49d0f    delivered      2018-07-29 09:51:30   \n",
       "\n",
       "     order_approved_at order_delivered_carrier_date  ... product_weight_g  \\\n",
       "0  2017-05-16 15:22:12          2017-05-23 10:47:57  ...           8683.0   \n",
       "1  2018-01-12 20:58:32          2018-01-15 17:14:59  ...          10150.0   \n",
       "2  2018-05-20 16:19:10          2018-06-11 14:31:00  ...           8267.0   \n",
       "3  2018-03-13 17:29:19          2018-03-27 23:22:42  ...          12160.0   \n",
       "4  2018-07-29 10:10:09          2018-07-30 15:16:00  ...           5200.0   \n",
       "\n",
       "  product_length_cm  product_height_cm product_width_cm  \\\n",
       "0              54.0               64.0             31.0   \n",
       "1              89.0               15.0             40.0   \n",
       "2              52.0               52.0             17.0   \n",
       "3              56.0               51.0             28.0   \n",
       "4              45.0               15.0             35.0   \n",
       "\n",
       "  product_category_name_english total_price        date      time  year  month  \n",
       "0              office_furniture      146.87  2017-05-16  15:05:35  2017      5  \n",
       "1                    housewares      335.48  2018-01-12  20:48:24  2018      1  \n",
       "2              office_furniture      157.73  2018-05-19  16:07:45  2018      5  \n",
       "3              office_furniture      173.30  2018-03-13  16:06:38  2018      3  \n",
       "4                  home_confort      252.25  2018-07-29  09:51:30  2018      7  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_order_df[\"order_purchase_timestamp\"] = pd.to_datetime(new_order_df[\"order_purchase_timestamp\"])\n",
    "\n",
    "new_order_df['date'] = new_order_df['order_purchase_timestamp'].dt.date\n",
    "new_order_df['time'] = new_order_df['order_purchase_timestamp'].dt.time\n",
    "new_order_df['year'] = new_order_df['order_purchase_timestamp'].dt.year\n",
    "new_order_df['month'] = new_order_df['order_purchase_timestamp'].dt.month\n",
    "\n",
    "new_order_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['delivered' 'invoiced' 'shipped' 'processing' 'canceled' 'unavailable'\n",
      " 'approved']\n"
     ]
    }
   ],
   "source": [
    "order_stat = new_order_df['order_status'].unique()\n",
    "print(order_stat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "keep_val = [\"delivered\"]\n",
    "new_order_df = new_order_df[new_order_df[\"order_status\"].isin(keep_val)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['delivered']\n"
     ]
    }
   ],
   "source": [
    "order_stat = new_order_df['order_status'].unique()\n",
    "print(order_stat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 108638 entries, 0 to 111022\n",
      "Data columns (total 32 columns):\n",
      " #   Column                         Non-Null Count   Dtype         \n",
      "---  ------                         --------------   -----         \n",
      " 0   customer_id                    108638 non-null  object        \n",
      " 1   customer_unique_id             108638 non-null  object        \n",
      " 2   customer_zip_code_prefix       108638 non-null  int64         \n",
      " 3   customer_city                  108638 non-null  object        \n",
      " 4   customer_state                 108638 non-null  object        \n",
      " 5   order_id                       108638 non-null  object        \n",
      " 6   order_status                   108638 non-null  object        \n",
      " 7   order_purchase_timestamp       108638 non-null  datetime64[ns]\n",
      " 8   order_approved_at              108624 non-null  object        \n",
      " 9   order_delivered_carrier_date   108636 non-null  object        \n",
      " 10  order_delivered_customer_date  108630 non-null  object        \n",
      " 11  order_estimated_delivery_date  108638 non-null  object        \n",
      " 12  order_item_id                  108638 non-null  int64         \n",
      " 13  product_id                     108638 non-null  object        \n",
      " 14  seller_id                      108638 non-null  object        \n",
      " 15  shipping_limit_date            108638 non-null  object        \n",
      " 16  price                          108638 non-null  float64       \n",
      " 17  freight_value                  108638 non-null  float64       \n",
      " 18  product_category_name          108638 non-null  object        \n",
      " 19  product_name_lenght            108638 non-null  float64       \n",
      " 20  product_description_lenght     108638 non-null  float64       \n",
      " 21  product_photos_qty             108638 non-null  float64       \n",
      " 22  product_weight_g               108637 non-null  float64       \n",
      " 23  product_length_cm              108637 non-null  float64       \n",
      " 24  product_height_cm              108637 non-null  float64       \n",
      " 25  product_width_cm               108637 non-null  float64       \n",
      " 26  product_category_name_english  108638 non-null  object        \n",
      " 27  total_price                    108638 non-null  float64       \n",
      " 28  date                           108638 non-null  object        \n",
      " 29  time                           108638 non-null  object        \n",
      " 30  year                           108638 non-null  int32         \n",
      " 31  month                          108638 non-null  int32         \n",
      "dtypes: datetime64[ns](1), float64(10), int32(2), int64(2), object(17)\n",
      "memory usage: 26.5+ MB\n"
     ]
    }
   ],
   "source": [
    "new_order_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 108638 entries, 0 to 111022\n",
      "Data columns (total 12 columns):\n",
      " #   Column                         Non-Null Count   Dtype         \n",
      "---  ------                         --------------   -----         \n",
      " 0   customer_id                    108638 non-null  object        \n",
      " 1   customer_unique_id             108638 non-null  object        \n",
      " 2   customer_city                  108638 non-null  object        \n",
      " 3   customer_state                 108638 non-null  object        \n",
      " 4   order_status                   108638 non-null  object        \n",
      " 5   order_purchase_timestamp       108638 non-null  datetime64[ns]\n",
      " 6   product_category_name_english  108638 non-null  object        \n",
      " 7   total_price                    108638 non-null  float64       \n",
      " 8   date                           108638 non-null  object        \n",
      " 9   time                           108638 non-null  object        \n",
      " 10  year                           108638 non-null  int32         \n",
      " 11  month                          108638 non-null  int32         \n",
      "dtypes: datetime64[ns](1), float64(1), int32(2), object(8)\n",
      "memory usage: 9.9+ MB\n"
     ]
    }
   ],
   "source": [
    "drop_col = [\"order_approved_at\", \"order_delivered_carrier_date\", \"order_delivered_customer_date\", \"shipping_limit_date\", \"product_category_name\", \"product_name_lenght\", \"product_description_lenght\", \"product_photos_qty\", \"product_weight_g\", \"product_length_cm\", \"product_height_cm\", \"product_width_cm\", \"seller_id\", \"order_estimated_delivery_date\", \"order_item_id\", \"price\", \"freight_value\", \"customer_zip_code_prefix\", \"order_id\", \"product_id\"]\n",
    "\n",
    "df_cleaned = new_order_df.drop(columns=drop_col)\n",
    "df_cleaned.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cleaned.to_csv(\"dashboard/e-commerce_cleaned.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis (EDA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_use = pd.read_csv(\"dashboard/e-commerce_cleaned.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>customer_id</th>\n",
       "      <th>customer_unique_id</th>\n",
       "      <th>customer_city</th>\n",
       "      <th>customer_state</th>\n",
       "      <th>order_status</th>\n",
       "      <th>order_purchase_timestamp</th>\n",
       "      <th>product_category_name_english</th>\n",
       "      <th>total_price</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06b8999e2fba1a1fbc88172c00ba8bc7</td>\n",
       "      <td>861eff4711a542e4b93843c6dd7febb0</td>\n",
       "      <td>franca</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2017-05-16 15:05:35</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>146.87</td>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>15:05:35</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18955e83d337fd6b2def6b18a428ac77</td>\n",
       "      <td>290c77bc529b7ac935b93aa66c333dc3</td>\n",
       "      <td>sao bernardo do campo</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-01-12 20:48:24</td>\n",
       "      <td>housewares</td>\n",
       "      <td>335.48</td>\n",
       "      <td>2018-01-12</td>\n",
       "      <td>20:48:24</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4e7b3e00288586ebd08712fdd0374a03</td>\n",
       "      <td>060e732b5b29e8181a18229c7b0b2b5e</td>\n",
       "      <td>sao paulo</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-05-19 16:07:45</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>157.73</td>\n",
       "      <td>2018-05-19</td>\n",
       "      <td>16:07:45</td>\n",
       "      <td>2018</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b2b6027bc5c5109e529d4dc6358b12c3</td>\n",
       "      <td>259dac757896d24d7702b9acbbff3f3c</td>\n",
       "      <td>mogi das cruzes</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-03-13 16:06:38</td>\n",
       "      <td>office_furniture</td>\n",
       "      <td>173.30</td>\n",
       "      <td>2018-03-13</td>\n",
       "      <td>16:06:38</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4f2d8ab171c80ec8364f7c12e35b23ad</td>\n",
       "      <td>345ecd01c38d18a9036ed96c73b8d066</td>\n",
       "      <td>campinas</td>\n",
       "      <td>São Paulo</td>\n",
       "      <td>delivered</td>\n",
       "      <td>2018-07-29 09:51:30</td>\n",
       "      <td>home_confort</td>\n",
       "      <td>252.25</td>\n",
       "      <td>2018-07-29</td>\n",
       "      <td>09:51:30</td>\n",
       "      <td>2018</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        customer_id                customer_unique_id  \\\n",
       "0  06b8999e2fba1a1fbc88172c00ba8bc7  861eff4711a542e4b93843c6dd7febb0   \n",
       "1  18955e83d337fd6b2def6b18a428ac77  290c77bc529b7ac935b93aa66c333dc3   \n",
       "2  4e7b3e00288586ebd08712fdd0374a03  060e732b5b29e8181a18229c7b0b2b5e   \n",
       "3  b2b6027bc5c5109e529d4dc6358b12c3  259dac757896d24d7702b9acbbff3f3c   \n",
       "4  4f2d8ab171c80ec8364f7c12e35b23ad  345ecd01c38d18a9036ed96c73b8d066   \n",
       "\n",
       "           customer_city customer_state order_status order_purchase_timestamp  \\\n",
       "0                 franca      São Paulo    delivered      2017-05-16 15:05:35   \n",
       "1  sao bernardo do campo      São Paulo    delivered      2018-01-12 20:48:24   \n",
       "2              sao paulo      São Paulo    delivered      2018-05-19 16:07:45   \n",
       "3        mogi das cruzes      São Paulo    delivered      2018-03-13 16:06:38   \n",
       "4               campinas      São Paulo    delivered      2018-07-29 09:51:30   \n",
       "\n",
       "  product_category_name_english  total_price        date      time  year  \\\n",
       "0              office_furniture       146.87  2017-05-16  15:05:35  2017   \n",
       "1                    housewares       335.48  2018-01-12  20:48:24  2018   \n",
       "2              office_furniture       157.73  2018-05-19  16:07:45  2018   \n",
       "3              office_furniture       173.30  2018-03-13  16:06:38  2018   \n",
       "4                  home_confort       252.25  2018-07-29  09:51:30  2018   \n",
       "\n",
       "   month  \n",
       "0      5  \n",
       "1      1  \n",
       "2      5  \n",
       "3      3  \n",
       "4      7  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_use.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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</th>\n",
       "      <th>jumlah</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>59646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>48677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  jumlah\n",
       "0  2018   59646\n",
       "1  2017   48677\n",
       "2  2016     315"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year = df_use.groupby(by='year').agg({\n",
    "    'year': 'count',\n",
    "}).rename(columns={\"year\":\"jumlah\"}).sort_values(by='jumlah',ascending= False)\n",
    "year.reset_index(inplace=True)\n",
    "year.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore kategori produk yang banyak dibeli pelanggan di platform e-commerce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product_category_name_english</th>\n",
       "      <th>jumlah</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bed_bath_table</td>\n",
       "      <td>10953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>health_beauty</td>\n",
       "      <td>9465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sports_leisure</td>\n",
       "      <td>8431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>furniture_decor</td>\n",
       "      <td>8160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>computers_accessories</td>\n",
       "      <td>7644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  product_category_name_english  jumlah\n",
       "0                bed_bath_table   10953\n",
       "1                 health_beauty    9465\n",
       "2                sports_leisure    8431\n",
       "3               furniture_decor    8160\n",
       "4         computers_accessories    7644"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_products = df_use.groupby(by='product_category_name_english').agg({\n",
    "    'product_category_name_english': 'count',\n",
    "}).rename(columns={\"product_category_name_english\":\"jumlah\"}).sort_values(by='jumlah',ascending= False)\n",
    "category_products.reset_index(inplace=True)\n",
    "category_products.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore pendapatan dari pelanggan di platform e-commerce berdasarkan daerah (state)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>customer_state</th>\n",
       "      <th colspan=\"4\" halign=\"left\">total_price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>nunique</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customer_state</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>Acre</th>\n",
       "      <td>1</td>\n",
       "      <td>1251.70</td>\n",
       "      <td>39.03</td>\n",
       "      <td>218.516742</td>\n",
       "      <td>215.691905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alagoas</th>\n",
       "      <td>1</td>\n",
       "      <td>1942.00</td>\n",
       "      <td>25.24</td>\n",
       "      <td>220.997754</td>\n",
       "      <td>258.259287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amapá</th>\n",
       "      <td>1</td>\n",
       "      <td>1482.42</td>\n",
       "      <td>34.80</td>\n",
       "      <td>199.281605</td>\n",
       "      <td>230.970672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amazonas</th>\n",
       "      <td>1</td>\n",
       "      <td>1853.75</td>\n",
       "      <td>29.65</td>\n",
       "      <td>167.371491</td>\n",
       "      <td>221.453047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahia</th>\n",
       "      <td>1</td>\n",
       "      <td>3048.27</td>\n",
       "      <td>21.99</td>\n",
       "      <td>161.035373</td>\n",
       "      <td>208.831994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ceará</th>\n",
       "      <td>1</td>\n",
       "      <td>2734.11</td>\n",
       "      <td>25.43</td>\n",
       "      <td>186.510482</td>\n",
       "      <td>222.130100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Distrito Federal</th>\n",
       "      <td>1</td>\n",
       "      <td>4194.76</td>\n",
       "      <td>20.04</td>\n",
       "      <td>147.655949</td>\n",
       "      <td>223.900240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Espírito Santo</th>\n",
       "      <td>1</td>\n",
       "      <td>6922.21</td>\n",
       "      <td>22.04</td>\n",
       "      <td>143.068962</td>\n",
       "      <td>220.511121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Goiás</th>\n",
       "      <td>1</td>\n",
       "      <td>2220.32</td>\n",
       "      <td>13.27</td>\n",
       "      <td>145.922004</td>\n",
       "      <td>167.462538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maranhão</th>\n",
       "      <td>1</td>\n",
       "      <td>2511.75</td>\n",
       "      <td>21.24</td>\n",
       "      <td>184.697585</td>\n",
       "      <td>217.657076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mato Grosso</th>\n",
       "      <td>1</td>\n",
       "      <td>2124.78</td>\n",
       "      <td>15.90</td>\n",
       "      <td>175.583776</td>\n",
       "      <td>211.376481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mato Grosso do Sul</th>\n",
       "      <td>1</td>\n",
       "      <td>6929.31</td>\n",
       "      <td>21.33</td>\n",
       "      <td>166.572993</td>\n",
       "      <td>337.192809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minas Gerais</th>\n",
       "      <td>1</td>\n",
       "      <td>4175.26</td>\n",
       "      <td>6.08</td>\n",
       "      <td>141.071587</td>\n",
       "      <td>185.188839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paraná</th>\n",
       "      <td>1</td>\n",
       "      <td>3126.50</td>\n",
       "      <td>10.33</td>\n",
       "      <td>138.563309</td>\n",
       "      <td>184.123612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paraíba</th>\n",
       "      <td>1</td>\n",
       "      <td>4681.78</td>\n",
       "      <td>29.74</td>\n",
       "      <td>233.567712</td>\n",
       "      <td>350.223583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pará</th>\n",
       "      <td>1</td>\n",
       "      <td>2252.66</td>\n",
       "      <td>26.13</td>\n",
       "      <td>194.864802</td>\n",
       "      <td>230.177466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pernambuco</th>\n",
       "      <td>1</td>\n",
       "      <td>3792.59</td>\n",
       "      <td>14.38</td>\n",
       "      <td>176.548868</td>\n",
       "      <td>215.089256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Piauí</th>\n",
       "      <td>1</td>\n",
       "      <td>1816.11</td>\n",
       "      <td>34.80</td>\n",
       "      <td>202.207364</td>\n",
       "      <td>211.315186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rio Grande do Norte</th>\n",
       "      <td>1</td>\n",
       "      <td>1821.82</td>\n",
       "      <td>34.84</td>\n",
       "      <td>194.082602</td>\n",
       "      <td>232.205421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rio Grande do Sul</th>\n",
       "      <td>1</td>\n",
       "      <td>3297.40</td>\n",
       "      <td>19.48</td>\n",
       "      <td>140.821365</td>\n",
       "      <td>173.335013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rio de Janeiro</th>\n",
       "      <td>1</td>\n",
       "      <td>4950.34</td>\n",
       "      <td>9.56</td>\n",
       "      <td>145.647034</td>\n",
       "      <td>194.256355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rondônia</th>\n",
       "      <td>1</td>\n",
       "      <td>2452.12</td>\n",
       "      <td>34.34</td>\n",
       "      <td>210.302397</td>\n",
       "      <td>288.780950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roraima</th>\n",
       "      <td>1</td>\n",
       "      <td>994.77</td>\n",
       "      <td>39.03</td>\n",
       "      <td>198.584091</td>\n",
       "      <td>184.711014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Santa Catarina</th>\n",
       "      <td>1</td>\n",
       "      <td>3209.72</td>\n",
       "      <td>14.24</td>\n",
       "      <td>145.427357</td>\n",
       "      <td>200.336724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sergipe</th>\n",
       "      <td>1</td>\n",
       "      <td>1729.98</td>\n",
       "      <td>30.97</td>\n",
       "      <td>187.844745</td>\n",
       "      <td>207.561963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>São Paulo</th>\n",
       "      <td>1</td>\n",
       "      <td>6726.66</td>\n",
       "      <td>7.28</td>\n",
       "      <td>124.355822</td>\n",
       "      <td>168.430807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tocantins</th>\n",
       "      <td>1</td>\n",
       "      <td>2784.16</td>\n",
       "      <td>26.13</td>\n",
       "      <td>194.386013</td>\n",
       "      <td>268.840434</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    customer_state total_price                               \n",
       "                           nunique         max    min        mean         std\n",
       "customer_state                                                               \n",
       "Acre                             1     1251.70  39.03  218.516742  215.691905\n",
       "Alagoas                          1     1942.00  25.24  220.997754  258.259287\n",
       "Amapá                            1     1482.42  34.80  199.281605  230.970672\n",
       "Amazonas                         1     1853.75  29.65  167.371491  221.453047\n",
       "Bahia                            1     3048.27  21.99  161.035373  208.831994\n",
       "Ceará                            1     2734.11  25.43  186.510482  222.130100\n",
       "Distrito Federal                 1     4194.76  20.04  147.655949  223.900240\n",
       "Espírito Santo                   1     6922.21  22.04  143.068962  220.511121\n",
       "Goiás                            1     2220.32  13.27  145.922004  167.462538\n",
       "Maranhão                         1     2511.75  21.24  184.697585  217.657076\n",
       "Mato Grosso                      1     2124.78  15.90  175.583776  211.376481\n",
       "Mato Grosso do Sul               1     6929.31  21.33  166.572993  337.192809\n",
       "Minas Gerais                     1     4175.26   6.08  141.071587  185.188839\n",
       "Paraná                           1     3126.50  10.33  138.563309  184.123612\n",
       "Paraíba                          1     4681.78  29.74  233.567712  350.223583\n",
       "Pará                             1     2252.66  26.13  194.864802  230.177466\n",
       "Pernambuco                       1     3792.59  14.38  176.548868  215.089256\n",
       "Piauí                            1     1816.11  34.80  202.207364  211.315186\n",
       "Rio Grande do Norte              1     1821.82  34.84  194.082602  232.205421\n",
       "Rio Grande do Sul                1     3297.40  19.48  140.821365  173.335013\n",
       "Rio de Janeiro                   1     4950.34   9.56  145.647034  194.256355\n",
       "Rondônia                         1     2452.12  34.34  210.302397  288.780950\n",
       "Roraima                          1      994.77  39.03  198.584091  184.711014\n",
       "Santa Catarina                   1     3209.72  14.24  145.427357  200.336724\n",
       "Sergipe                          1     1729.98  30.97  187.844745  207.561963\n",
       "São Paulo                        1     6726.66   7.28  124.355822  168.430807\n",
       "Tocantins                        1     2784.16  26.13  194.386013  268.840434"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_use.groupby(by=\"customer_state\").agg({\n",
    "    \"customer_state\": \"nunique\",\n",
    "    \"total_price\": [\"max\", \"min\", \"mean\", \"std\"]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customer_state\n",
       "São Paulo            5697113.29\n",
       "Rio de Janeiro       2028571.89\n",
       "Minas Gerais         1796405.59\n",
       "Rio Grande do Sul     850279.40\n",
       "Paraná                772074.76\n",
       "Name: total_price, dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_revenue_per_state = df_use.groupby('customer_state')['total_price'].sum()\n",
    "\n",
    "top_5_states = total_revenue_per_state.sort_values(ascending=False).head(5)\n",
    "\n",
    "top_5_states.head(5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore pendapatan dari pelanggan di platform e-commerce berdasarkan bulan dan tahun"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    year  month  total_price     period\n",
      "0   2016      9       143.46 2016-09-01\n",
      "1   2016     10     46394.74 2016-10-01\n",
      "2   2016     12        19.62 2016-12-01\n",
      "3   2017      1    125683.64 2017-01-01\n",
      "4   2017      2    261694.98 2017-02-01\n",
      "5   2017      3    406871.63 2017-03-01\n",
      "6   2017      4    380615.96 2017-04-01\n",
      "7   2017      5    554208.03 2017-05-01\n",
      "8   2017      6    484095.06 2017-06-01\n",
      "9   2017      7    562456.67 2017-07-01\n",
      "10  2017      8    639629.63 2017-08-01\n",
      "11  2017      9    694003.62 2017-09-01\n",
      "12  2017     10    733050.47 2017-10-01\n",
      "13  2017     11   1137526.60 2017-11-01\n",
      "14  2017     12    825707.25 2017-12-01\n",
      "15  2018      1   1053965.48 2018-01-01\n",
      "16  2018      2    951341.13 2018-02-01\n",
      "17  2018      3   1101474.76 2018-03-01\n",
      "18  2018      4   1123553.90 2018-04-01\n",
      "19  2018      5   1122746.04 2018-05-01\n",
      "20  2018      6   1009172.59 2018-06-01\n",
      "21  2018      7   1021408.04 2018-07-01\n",
      "22  2018      8    980656.61 2018-08-01\n"
     ]
    }
   ],
   "source": [
    "monthly_sales = df_cleaned.groupby(['year', 'month'])['total_price'].sum().reset_index()\n",
    "\n",
    "monthly_sales['period'] = pd.to_datetime(monthly_sales[['year', 'month']].assign(day=1))\n",
    "\n",
    "print(monthly_sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization & Explanatory Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pertanyaan 1: Apa saja 5 kategori produk yang paling sering di beli oleh pelanggan e-commerce?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "plt.bar(category_products['product_category_name_english'].head(5), category_products['jumlah'].head(5), color='skyblue')\n",
    "\n",
    "plt.xlabel('Nama Kategori Produk', fontsize=12)\n",
    "plt.ylabel('Jumlah', fontsize=12)\n",
    "plt.title(' 5 Kategori produk yang paling sering di beli oleh pelanggan e-commerce (Grafik 1)', fontsize=12)\n",
    "plt.xticks(rotation=45) \n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pertanyaan 2: Apa saja 5 daerah yang menjadi target pasar potensial di platform e-commerce?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_5_states.plot(kind='bar', color='skyblue', figsize=(8, 5))\n",
    "\n",
    "plt.title('5 Daerah dengan Volume Pendapatan Tertinggi di Platform E-Commerce (Grafik 2)', fontsize=14)\n",
    "plt.xlabel('Daerah (State)', fontsize=12)\n",
    "plt.ylabel('Total Pendapatan', fontsize=12)\n",
    "\n",
    "plt.xticks(rotation=45) \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pertanyaan 3: Di bulan dan tahun berapa e-commerce mencatatkan pendapatan tertinggi dan terendah?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(monthly_sales['period'], monthly_sales['total_price'], marker='o', linestyle='-', color='blue')\n",
    "\n",
    "plt.title('Pendapatan Bulanan (Grafik 3)', fontsize=16)\n",
    "plt.xlabel('Bulan', fontsize=12)\n",
    "plt.ylabel('Total Pendapatan', fontsize=12)\n",
    "\n",
    "plt.xticks(ticks=monthly_sales['period'], labels=monthly_sales['period'].dt.strftime('%Y-%m'), rotation=45)\n",
    "\n",
    "plt.grid(True)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analisis Lanjutan (Opsional)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RFM Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 108638 entries, 0 to 108637\n",
      "Data columns (total 12 columns):\n",
      " #   Column                         Non-Null Count   Dtype  \n",
      "---  ------                         --------------   -----  \n",
      " 0   customer_id                    108638 non-null  object \n",
      " 1   customer_unique_id             108638 non-null  object \n",
      " 2   customer_city                  108638 non-null  object \n",
      " 3   customer_state                 108638 non-null  object \n",
      " 4   order_status                   108638 non-null  object \n",
      " 5   order_purchase_timestamp       108638 non-null  object \n",
      " 6   product_category_name_english  108638 non-null  object \n",
      " 7   total_price                    108638 non-null  float64\n",
      " 8   date                           108638 non-null  object \n",
      " 9   time                           108638 non-null  object \n",
      " 10  year                           108638 non-null  int64  \n",
      " 11  month                          108638 non-null  int64  \n",
      "dtypes: float64(1), int64(2), object(9)\n",
      "memory usage: 9.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df_use.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     customer_unique_id  Recency  Frequency  Monetary\n",
      "0      0000366f3b9a7992bf8c76cfdf3221e2      111          1    141.90\n",
      "1      0000b849f77a49e4a4ce2b2a4ca5be3f      114          1     27.19\n",
      "2      0000f46a3911fa3c0805444483337064      536          1     86.22\n",
      "3      0000f6ccb0745a6a4b88665a16c9f078      320          1     43.62\n",
      "4      0004aac84e0df4da2b147fca70cf8255      287          1    196.89\n",
      "...                                 ...      ...        ...       ...\n",
      "92074  fffcf5a5ff07b0908bd4e2dbc735a684      446          2   2067.42\n",
      "92075  fffea47cd6d3cc0a88bd621562a9d061      261          1     84.58\n",
      "92076  ffff371b4d645b6ecea244b27531430a      567          1    112.46\n",
      "92077  ffff5962728ec6157033ef9805bacc48      118          1    133.69\n",
      "92078  ffffd2657e2aad2907e67c3e9daecbeb      483          1     71.56\n",
      "\n",
      "[92079 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "df = df_use\n",
    "\n",
    "df['order_purchase_timestamp'] = pd.to_datetime(df['order_purchase_timestamp'])\n",
    "\n",
    "reference_date = df['order_purchase_timestamp'].max()\n",
    "\n",
    "\n",
    "rfm = df.groupby('customer_unique_id').agg({\n",
    "    'order_purchase_timestamp': lambda x: (reference_date - x.max()).days,  # Recency\n",
    "    'customer_id': 'count',  # Frequency\n",
    "    'total_price': 'sum'  # Monetary\n",
    "}).reset_index()\n",
    "\n",
    "rfm.rename(columns={\n",
    "    'order_purchase_timestamp': 'Recency',\n",
    "    'customer_id': 'Frequency',\n",
    "    'total_price': 'Monetary'\n",
    "}, inplace=True)\n",
    "\n",
    "print(rfm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     customer_unique_id  Recency  Frequency  Monetary\n",
      "46102  7febafa06d9d8f232a900a2937f04338        0          1     61.29\n",
      "32128  58ffbb506c34ffb731c99595589a4ebe        0          1     38.37\n",
      "82668  e58697e3a253c253e1582f8c4f4c54ff        0          2    185.82\n",
      "12267  21dbe8eabd00b34492a939c540e2b1a7        0          1     14.29\n",
      "24805  44d111bdc55faca551ef91cb74a444d8        0          1    259.81\n",
      "...                                 ...      ...        ...       ...\n",
      "86923  f176923a0a4ab546c7287791ccb82193      694          2    101.44\n",
      "73166  cb1bc069e25d9c59773c85a2e2a46713      694          1    267.49\n",
      "80424  df2988ba3ed226b10521a0e4da849b61      694          1     86.88\n",
      "2976   0829f7df6577d5a4b65439bea701405f      694          1    267.49\n",
      "47229  830d5b7aaa3b6f1e9ad63703bec97d23      713          3    143.46\n",
      "\n",
      "[92079 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "rfm_sorted_R = rfm.sort_values(\"Recency\")\n",
    "print(rfm_sorted_R)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     customer_unique_id  Recency  Frequency  Monetary\n",
      "72147  c8460e4251689ba205045f3ea17884a1       21         24   4655.88\n",
      "24964  4546caea018ad8c692964e3382debd19      408         21    196.17\n",
      "70607  c402f431464c72e27330a67f7b94d4fb      187         20   2202.40\n",
      "38056  698e1cf81d01a3d389d96145f7fa6df8      371         20   2262.80\n",
      "5554   0f5ac8d5c31de21d2f25e24be15bbffb      275         18   1544.82\n",
      "...                                 ...      ...        ...       ...\n",
      "32650  5a6cda86d79e1ed11d38881398f56c59      522          1     84.16\n",
      "32649  5a6cd8797286a15f0bf2fb97f024781c      104          1     21.39\n",
      "32648  5a6bc06cb2b6634abf6db687a6523436      563          1    174.28\n",
      "32645  5a6a43b78f4354c6bf999401fba32452      468          1    233.68\n",
      "92078  ffffd2657e2aad2907e67c3e9daecbeb      483          1     71.56\n",
      "\n",
      "[92079 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "rfm_sorted_F = rfm.sort_values(\"Frequency\", ascending=False)\n",
    "print(rfm_sorted_F)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     customer_unique_id  Recency  Frequency  Monetary\n",
      "3676   0a0a92112bd4c708ca5fde585afaa872      333          8  13664.08\n",
      "78561  da122df9eeddfedc1dc1f5349a1a690c      514          2   7571.63\n",
      "42571  763c8b1c9c68a0229c42c9fc6f662b93       45          4   7274.88\n",
      "79376  dc4802a71eae9be1dd28f5d788ceb526      562          1   6929.31\n",
      "25089  459bef486812aa25204be022145caa62       34          1   6922.21\n",
      "...                                 ...      ...        ...       ...\n",
      "14600  2878e5b88167faab17d4fb83a986d38b      303          1     11.63\n",
      "40136  6f5b9d1cdccc4d28f0483a612edecacf      360          1     11.63\n",
      "64584  b33336f46234b24a613ad9064d13106d       68          1     10.89\n",
      "68101  bd06ce0e06ad77a7f681f1a4960a3cc6      349          1     10.07\n",
      "17854  317cfc692e3f86c45c95697c61c853a6        3          1      9.59\n",
      "\n",
      "[92079 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "rfm_sorted_M = rfm.sort_values(\"Monetary\", ascending=False)\n",
    "print(rfm_sorted_M)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "rfm['Recency_Category'] = pd.cut(rfm['Recency'], bins=[0, 30, 90, 180, 365, rfm['Recency'].max()],\n",
    "                                  labels=['<30 hari', '30-90 hari', '90-180 hari', '180-365 hari', '>365 hari'])\n",
    "rfm['Frequency_Category'] = pd.cut(rfm['Frequency'], bins=[0, 1, 3, 5, 10, rfm['Frequency'].max()],\n",
    "                                    labels=['1x', '2-3x', '4-5x', '6-10x', '>10x'])\n",
    "rfm['Monetary_Category'] = pd.cut(rfm['Monetary'], bins=[0, 100, 500, 1000, 5000, rfm['Monetary'].max()],\n",
    "                                   labels=['<100', '100-500', '500-1000', '1000-5000', '>5000'])\n",
    "\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.subplot(1, 3, 1)\n",
    "rfm['Recency_Category'].value_counts().sort_index().plot(kind='bar', color='blue')\n",
    "plt.title('Recency')\n",
    "plt.xlabel('Kategori Recency')\n",
    "plt.ylabel('Jumlah Pelanggan')\n",
    "\n",
    "plt.subplot(1, 3, 2)\n",
    "rfm['Frequency_Category'].value_counts().sort_index().plot(kind='bar', color='green')\n",
    "plt.title('Frequency')\n",
    "plt.xlabel('Kategori Frequency')\n",
    "plt.ylabel('Jumlah Pelanggan')\n",
    "\n",
    "plt.subplot(1, 3, 3)\n",
    "rfm['Monetary_Category'].value_counts().sort_index().plot(kind='bar', color='orange')\n",
    "plt.title('Monetary')\n",
    "plt.xlabel('Kategori Monetary')\n",
    "plt.ylabel('Jumlah Pelanggan')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "top_recency = rfm.sort_values(by=\"Recency\", ascending=True).head(10)\n",
    "\n",
    "top_frequency = rfm.sort_values(by=\"Frequency\", ascending=False).head(10)\n",
    "\n",
    "top_monetary = rfm.sort_values(by=\"Monetary\", ascending=False).head(10)\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(\n",
    "    x=\"Recency\", \n",
    "    y=\"customer_unique_id\", \n",
    "    data=top_recency, \n",
    "    hue=\"customer_unique_id\", \n",
    "    palette=\"Blues_r\", \n",
    "    legend=False\n",
    ")\n",
    "plt.title(\" 10 Customers terbaik berdasarkan Recency terendah\", fontsize=16)\n",
    "plt.xlabel(\"Recency (Hari Sejak Pembelian Terakhir)\", fontsize=12)\n",
    "plt.ylabel(\"Customer Unique ID\", fontsize=12)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(\n",
    "    x=\"Frequency\", \n",
    "    y=\"customer_unique_id\", \n",
    "    data=top_frequency, \n",
    "    hue=\"customer_unique_id\", \n",
    "    palette=\"Blues_r\", \n",
    "    legend=False\n",
    ")\n",
    "plt.title(\"10 Customers terbaik berdasarkan Frequency tertinggi\", fontsize=16)\n",
    "plt.xlabel(\"Frequency (Jumlah Transaksi)\", fontsize=12)\n",
    "plt.ylabel(\"Customer Unique ID\", fontsize=12)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(\n",
    "    x=\"Monetary\", \n",
    "    y=\"customer_unique_id\", \n",
    "    data=top_monetary, \n",
    "    hue=\"customer_unique_id\", \n",
    "    palette=\"Oranges_r\", \n",
    "    legend=False\n",
    ")\n",
    "plt.title(\"10 Customers terbaik berdasarkan Monetary tertinggi\", fontsize=16)\n",
    "plt.xlabel(\"Monetary (Jumlah Pengeluaran)\", fontsize=12)\n",
    "plt.ylabel(\"Customer Unique ID\", fontsize=12)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Apa saja 5 kategori produk yang paling sering di beli oleh pelanggan e-commerce?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Pada grafik 1 dapat dilihat 5 katergori yang paling sering dibeli oleh pelanggan e-commerce. Kategori **bed_bath_table** memiliki jumlah pembelian tertinggi, diikuti oleh **health_beauty**, **furniture_decor**, **sports_leisure**, dan terakhir **computers_accessories**. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Apa saja 5 daerah yang menjadi target pasar potensial di platform e-commerce?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Pada grafik 2 menunjukkan 5 daerah dengan volume pendapatan tertinggi di platform e-commerce. Daerah **SP (São Paulo)** mendominasi dengan pendapatan tertinggi, diikuti oleh **RJ (Rio de Janeiro)** dan **MG (Minas Gerais)**. Sementara itu, daerah **RS (Rio Grande do Sul)** dan **PR (Paraná)** memiliki volume pendapatan yang lebih rendah dibandingkan tiga daerah teratas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Di bulan dan tahun berapa e-commerce mencatatkan pendapatan tertinggi dan terendah?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Pada grafik 3 menunjukkan pendapatan terendah pada platform e-commerce didapatkan pada bulan ke **12 - 2016 (Desember 2016)** sedangkan pendapatan tertinggi pada platfrom e-commerce didapatkan pada bulan ke **11 - 2017 (November 2017)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Pelanggan mana yang menjadi pelanggan terbaik berdasarkan RFM Analysis?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- berdasarkan **Recency**, pelanggan dengan **customer_unique_id 7febafa06d9d8f232a900a2937f04338** menjadi salah satu pelanggan terbaik dengan 0 Hari sejak terakhir kali pelanggan melakukan pembelian pada platform e-commerce.\n",
    "- berdasarkan **Frequency**, pelanggan dengan **customer_unique_id c8460e4251689ba205045f3ea17884a1** menjadi pelanggan terbaik dengan jumlah total transaksi 24 kali  yang dilakukan pada platform e-commerce.\n",
    "- berdasarkan **Monetary**, pelanggan dengan **customer_unique_id 0a0a92112bd4c708ca5fde585afaa872** menjadi pelanggan terbaik dengan jumlah total pengeluaran pelanggan sebanyak 13664.08 pada platform e-commerce."
   ]
  }
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