E commerce data EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_6F6rxolVUph"
   },
   "source": [
    "* Dataset from : https://archive.ics.uci.edu/ml/datasets/Online+Retail#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "al7uPLI5VUpu"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 4226,
     "status": "ok",
     "timestamp": 1634789334125,
     "user": {
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      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "TZZCAq_CVUpz",
    "outputId": "803a6ac5-5de0-4186-88e1-78928981c948"
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   "outputs": [],
   "source": [
    "def get_font_family():\n",
    "    \"\"\"\n",
    "    시스템 환경에 따른 기본 폰트명을 반환하는 함수\n",
    "    \"\"\"\n",
    "    import platform\n",
    "    system_name = platform.system()\n",
    "\n",
    "    if system_name == \"Darwin\" :\n",
    "        font_family = \"AppleGothic\"\n",
    "    elif system_name == \"Windows\":\n",
    "        font_family = \"Malgun Gothic\"\n",
    "    else:\n",
    "        # Linux(Colab)\n",
    "        !apt-get install fonts-nanum -qq  > /dev/null\n",
    "        !fc-cache -fv\n",
    "\n",
    "        import matplotlib as mpl\n",
    "        mpl.font_manager._rebuild()\n",
    "        findfont = mpl.font_manager.fontManager.findfont\n",
    "        mpl.font_manager.findfont = findfont\n",
    "        mpl.backends.backend_agg.findfont = findfont\n",
    "        \n",
    "        font_family = \"NanumBarunGothic\"\n",
    "    return font_family\n",
    "\n",
    "plt.rc(\"font\", family=get_font_family())\n",
    "plt.rc(\"axes\", unicode_minus=False)"
   ]
  },
  {
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   "execution_count": 3,
   "metadata": {
    "colab": {
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     "status": "ok",
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     "user": {
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      "userId": "06348894780083418282"
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    "id": "aCg7NWdbVUp2",
    "outputId": "76f5f611-8b15-4a51-8a77-c905905703e8"
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   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541904</th>\n",
       "      <td>581587</td>\n",
       "      <td>22613</td>\n",
       "      <td>PACK OF 20 SPACEBOY NAPKINS</td>\n",
       "      <td>12</td>\n",
       "      <td>2011-12-09 12:50:00</td>\n",
       "      <td>0.85</td>\n",
       "      <td>12680.0</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541905</th>\n",
       "      <td>581587</td>\n",
       "      <td>22899</td>\n",
       "      <td>CHILDREN'S APRON DOLLY GIRL</td>\n",
       "      <td>6</td>\n",
       "      <td>2011-12-09 12:50:00</td>\n",
       "      <td>2.10</td>\n",
       "      <td>12680.0</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541906</th>\n",
       "      <td>581587</td>\n",
       "      <td>23254</td>\n",
       "      <td>CHILDRENS CUTLERY DOLLY GIRL</td>\n",
       "      <td>4</td>\n",
       "      <td>2011-12-09 12:50:00</td>\n",
       "      <td>4.15</td>\n",
       "      <td>12680.0</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541907</th>\n",
       "      <td>581587</td>\n",
       "      <td>23255</td>\n",
       "      <td>CHILDRENS CUTLERY CIRCUS PARADE</td>\n",
       "      <td>4</td>\n",
       "      <td>2011-12-09 12:50:00</td>\n",
       "      <td>4.15</td>\n",
       "      <td>12680.0</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541908</th>\n",
       "      <td>581587</td>\n",
       "      <td>22138</td>\n",
       "      <td>BAKING SET 9 PIECE RETROSPOT</td>\n",
       "      <td>3</td>\n",
       "      <td>2011-12-09 12:50:00</td>\n",
       "      <td>4.95</td>\n",
       "      <td>12680.0</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>541909 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0         536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1         536365     71053                  WHITE METAL LANTERN         6   \n",
       "2         536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3         536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4         536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "...          ...       ...                                  ...       ...   \n",
       "541904    581587     22613          PACK OF 20 SPACEBOY NAPKINS        12   \n",
       "541905    581587     22899         CHILDREN'S APRON DOLLY GIRL          6   \n",
       "541906    581587     23254        CHILDRENS CUTLERY DOLLY GIRL          4   \n",
       "541907    581587     23255      CHILDRENS CUTLERY CIRCUS PARADE         4   \n",
       "541908    581587     22138        BAKING SET 9 PIECE RETROSPOT          3   \n",
       "\n",
       "                InvoiceDate  UnitPrice  CustomerID         Country  \n",
       "0       2010-12-01 08:26:00       2.55     17850.0  United Kingdom  \n",
       "1       2010-12-01 08:26:00       3.39     17850.0  United Kingdom  \n",
       "2       2010-12-01 08:26:00       2.75     17850.0  United Kingdom  \n",
       "3       2010-12-01 08:26:00       3.39     17850.0  United Kingdom  \n",
       "4       2010-12-01 08:26:00       3.39     17850.0  United Kingdom  \n",
       "...                     ...        ...         ...             ...  \n",
       "541904  2011-12-09 12:50:00       0.85     12680.0          France  \n",
       "541905  2011-12-09 12:50:00       2.10     12680.0          France  \n",
       "541906  2011-12-09 12:50:00       4.15     12680.0          France  \n",
       "541907  2011-12-09 12:50:00       4.15     12680.0          France  \n",
       "541908  2011-12-09 12:50:00       4.95     12680.0          France  \n",
       "\n",
       "[541909 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data/online_retail.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
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     "status": "ok",
     "timestamp": 1634789335057,
     "user": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceNo       object\n",
       "StockCode       object\n",
       "Description     object\n",
       "Quantity         int64\n",
       "InvoiceDate     object\n",
       "UnitPrice      float64\n",
       "CustomerID     float64\n",
       "Country         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2HuBJz6q2tNw"
   },
   "source": [
    "Attribute Information:\n",
    "\n",
    "- InvoiceNo: 송장번호. 해당 거래에 할당된 6자리 정수\n",
    "  * 이 코드가 문자 'c'로 시작하면 취소를 나타냅니다.\n",
    "- StockCode: 제품 코드. 각 고유 제품에 고유하게 할당된 5자리 정수\n",
    "- Description: 제품 이름\n",
    "- Quantity: 거래당 각 제품의 수량 \n",
    "  * 이 코드가 ‘-’(마이너스)로 시작하면 취소를 나타냅니다.\n",
    "- InvoiceDate:  송장 날짜 및 시간. 숫자, 각 거래가 생성된 날짜 및 시간\n",
    "- UnitPrice: 단가. 숫자, 스털링(영국 화폐) 단위의 제품 가격\n",
    "- CustomerID: 고객 번호. 해당 고객에게 고유하게 할당된 5자리 정수\n",
    "- Country: 국가 이름. 해당 고객이 거주하는 국가의 이름"
   ]
  },
  {
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   "execution_count": 5,
   "metadata": {
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     "height": 300
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    "executionInfo": {
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     "status": "ok",
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    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quantity</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>541909.000000</td>\n",
       "      <td>541909.000000</td>\n",
       "      <td>406829.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9.552250</td>\n",
       "      <td>4.611114</td>\n",
       "      <td>15287.690570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>218.081158</td>\n",
       "      <td>96.759853</td>\n",
       "      <td>1713.600303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-80995.000000</td>\n",
       "      <td>-11062.060000</td>\n",
       "      <td>12346.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>13953.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.080000</td>\n",
       "      <td>15152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>4.130000</td>\n",
       "      <td>16791.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>80995.000000</td>\n",
       "      <td>38970.000000</td>\n",
       "      <td>18287.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Quantity      UnitPrice     CustomerID\n",
       "count  541909.000000  541909.000000  406829.000000\n",
       "mean        9.552250       4.611114   15287.690570\n",
       "std       218.081158      96.759853    1713.600303\n",
       "min    -80995.000000  -11062.060000   12346.000000\n",
       "25%         1.000000       1.250000   13953.000000\n",
       "50%         3.000000       2.080000   15152.000000\n",
       "75%        10.000000       4.130000   16791.000000\n",
       "max     80995.000000   38970.000000   18287.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
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    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>541909</td>\n",
       "      <td>541909</td>\n",
       "      <td>540455</td>\n",
       "      <td>541909</td>\n",
       "      <td>541909</td>\n",
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       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>25900</td>\n",
       "      <td>4070</td>\n",
       "      <td>4223</td>\n",
       "      <td>23260</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>573585</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>2011-10-31 14:41:00</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1114</td>\n",
       "      <td>2313</td>\n",
       "      <td>2369</td>\n",
       "      <td>1114</td>\n",
       "      <td>495478</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       InvoiceNo StockCode                         Description  \\\n",
       "count     541909    541909                              540455   \n",
       "unique     25900      4070                                4223   \n",
       "top       573585    85123A  WHITE HANGING HEART T-LIGHT HOLDER   \n",
       "freq        1114      2313                                2369   \n",
       "\n",
       "                InvoiceDate         Country  \n",
       "count                541909          541909  \n",
       "unique                23260              38  \n",
       "top     2011-10-31 14:41:00  United Kingdom  \n",
       "freq                   1114          495478  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include=[\"object\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 11,
     "status": "ok",
     "timestamp": 1634789335878,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "eaER7TiDVUp_",
    "outputId": "a890869c-56ea-4a3e-c80b-235eb9346405"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceNo           0\n",
       "StockCode           0\n",
       "Description      1454\n",
       "Quantity            0\n",
       "InvoiceDate         0\n",
       "UnitPrice           0\n",
       "CustomerID     135080\n",
       "Country             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 7,
     "status": "ok",
     "timestamp": 1634789335878,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "5e9vOOm5VUqA",
    "outputId": "27e9dc38-81dc-4e92-aa0e-d47d6e81f253"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceNo       0.000000\n",
       "StockCode       0.000000\n",
       "Description     0.268311\n",
       "Quantity        0.000000\n",
       "InvoiceDate     0.000000\n",
       "UnitPrice       0.000000\n",
       "CustomerID     24.926694\n",
       "Country         0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum() / df.shape[0] * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 607
    },
    "executionInfo": {
     "elapsed": 902,
     "status": "ok",
     "timestamp": 1634789342808,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "R84kQu4mVUqC",
    "outputId": "54f51d78-f5f4-49e1-b403-516d4039b00b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'Quantity'}>,\n",
       "        <AxesSubplot:title={'center':'UnitPrice'}>],\n",
       "       [<AxesSubplot:title={'center':'CustomerID'}>, <AxesSubplot:>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "wlEz7o0CVUqC"
   },
   "outputs": [],
   "source": [
    "df[\"TotalPrice\"] = df[\"UnitPrice\"] * df[\"Quantity\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "B7YCaej9VUqD"
   },
   "source": [
    "## 회원 vs 비회원 구매"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 19,
     "status": "ok",
     "timestamp": 1634789342809,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "IMfr249QVUqD",
    "outputId": "1558140c-5967-41e5-a2bc-acb36af049d8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "United Kingdom    133600\n",
       "EIRE                 711\n",
       "Hong Kong            288\n",
       "Unspecified          202\n",
       "Switzerland          125\n",
       "France                66\n",
       "Israel                47\n",
       "Portugal              39\n",
       "Bahrain                2\n",
       "Name: Country, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[\"CustomerID\"].isnull(), \"Country\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 16,
     "status": "ok",
     "timestamp": 1634789342810,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "ZNHLL-0sVUqD",
    "outputId": "1011f6f6-1bc2-468d-f831-c4343de19e3c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "United Kingdom          361878\n",
       "Germany                   9495\n",
       "France                    8491\n",
       "EIRE                      7485\n",
       "Spain                     2533\n",
       "Netherlands               2371\n",
       "Belgium                   2069\n",
       "Switzerland               1877\n",
       "Portugal                  1480\n",
       "Australia                 1259\n",
       "Norway                    1086\n",
       "Italy                      803\n",
       "Channel Islands            758\n",
       "Finland                    695\n",
       "Cyprus                     622\n",
       "Sweden                     462\n",
       "Austria                    401\n",
       "Denmark                    389\n",
       "Japan                      358\n",
       "Poland                     341\n",
       "USA                        291\n",
       "Israel                     250\n",
       "Unspecified                244\n",
       "Singapore                  229\n",
       "Iceland                    182\n",
       "Canada                     151\n",
       "Greece                     146\n",
       "Malta                      127\n",
       "United Arab Emirates        68\n",
       "European Community          61\n",
       "RSA                         58\n",
       "Lebanon                     45\n",
       "Lithuania                   35\n",
       "Brazil                      32\n",
       "Czech Republic              30\n",
       "Bahrain                     17\n",
       "Saudi Arabia                10\n",
       "Name: Country, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[~df[\"CustomerID\"].isnull(), \"Country\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "82lJFz5oVUqF"
   },
   "source": [
    "## 매출액 상위 국가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 275
    },
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1634789342811,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "7MBnsUThVUqF",
    "outputId": "b2a3f354-a1e8-46a0-b3b1-8525c4682a64"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "average_total_price by country top 10: \n",
      "Country\n",
      "Netherlands    120.059696\n",
      "Australia      108.877895\n",
      "Japan           98.716816\n",
      "Sweden          79.211926\n",
      "Denmark         48.247147\n",
      "Lithuania       47.458857\n",
      "Singapore       39.827031\n",
      "Lebanon         37.641778\n",
      "Brazil          35.737500\n",
      "Hong Kong       35.128611\n",
      "Name: TotalPrice, dtype: float64\n",
      "------------------------------\n",
      "sum_total_price by country top 10: \n",
      "Country\n",
      "United Kingdom    8187806.364\n",
      "Netherlands        284661.540\n",
      "EIRE               263276.820\n",
      "Germany            221698.210\n",
      "France             197403.900\n",
      "Australia          137077.270\n",
      "Switzerland         56385.350\n",
      "Spain               54774.580\n",
      "Belgium             40910.960\n",
      "Sweden              36595.910\n",
      "Name: TotalPrice, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "average_total_price = df.groupby(\"Country\")[\"TotalPrice\"].mean().sort_values(ascending=False).head(10)\n",
    "sum_total_price = df.groupby(\"Country\")[\"TotalPrice\"].sum().sort_values(ascending=False).head(10)\n",
    "\n",
    "print(f\"average_total_price by country top 10: \\n{average_total_price}\")\n",
    "print(\"-\"*30)\n",
    "print(f\"sum_total_price by country top 10: \\n{sum_total_price}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 상품\n",
    "* 판매 빈도가 높은 상품"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/ML/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  \n"
     ]
    },
    {
     "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>InvoiceNo</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>TotalPrice</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StockCode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>85123A</th>\n",
       "      <td>2313</td>\n",
       "      <td>38830</td>\n",
       "      <td>97894.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22423</th>\n",
       "      <td>2203</td>\n",
       "      <td>12980</td>\n",
       "      <td>164762.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85099B</th>\n",
       "      <td>2159</td>\n",
       "      <td>47363</td>\n",
       "      <td>92356.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47566</th>\n",
       "      <td>1727</td>\n",
       "      <td>18022</td>\n",
       "      <td>98302.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20725</th>\n",
       "      <td>1639</td>\n",
       "      <td>18979</td>\n",
       "      <td>35187.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84879</th>\n",
       "      <td>1502</td>\n",
       "      <td>36221</td>\n",
       "      <td>58959.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22720</th>\n",
       "      <td>1477</td>\n",
       "      <td>7286</td>\n",
       "      <td>37413.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22197</th>\n",
       "      <td>1476</td>\n",
       "      <td>56450</td>\n",
       "      <td>50987.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21212</th>\n",
       "      <td>1385</td>\n",
       "      <td>36039</td>\n",
       "      <td>21059.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20727</th>\n",
       "      <td>1350</td>\n",
       "      <td>12112</td>\n",
       "      <td>22219.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           InvoiceNo  Quantity  TotalPrice\n",
       "StockCode                                 \n",
       "85123A          2313     38830    97894.50\n",
       "22423           2203     12980   164762.19\n",
       "85099B          2159     47363    92356.03\n",
       "47566           1727     18022    98302.98\n",
       "20725           1639     18979    35187.31\n",
       "84879           1502     36221    58959.73\n",
       "22720           1477      7286    37413.44\n",
       "22197           1476     56450    50987.47\n",
       "21212           1385     36039    21059.72\n",
       "20727           1350     12112    22219.01"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 상품 판매 빈도가 높은 상품\n",
    "stock_sale_frequency_top10 = df.groupby([\"StockCode\"])['InvoiceNo', \"Quantity\", \"TotalPrice\"].aggregate(\n",
    "                    {\"InvoiceNo\": \"count\", \"Quantity\": \"sum\", \"TotalPrice\": \"sum\"},\n",
    "                    ascending=False\n",
    "                ).sort_values(by=[\"InvoiceNo\"], ascending=False).head(10)\n",
    "                #.nlargest(10, \"InvoiceNo\")\n",
    "stock_sale_frequency_top10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StockCode</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>85123A</th>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22423</th>\n",
       "      <td>REGENCY CAKESTAND 3 TIER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85099B</th>\n",
       "      <td>JUMBO BAG RED RETROSPOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47566</th>\n",
       "      <td>PARTY BUNTING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20725</th>\n",
       "      <td>LUNCH BAG RED RETROSPOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84879</th>\n",
       "      <td>ASSORTED COLOUR BIRD ORNAMENT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22720</th>\n",
       "      <td>SET OF 3 CAKE TINS PANTRY DESIGN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22197</th>\n",
       "      <td>SMALL POPCORN HOLDER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21212</th>\n",
       "      <td>PACK OF 72 RETROSPOT CAKE CASES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20727</th>\n",
       "      <td>LUNCH BAG  BLACK SKULL.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Description\n",
       "StockCode                                    \n",
       "85123A     WHITE HANGING HEART T-LIGHT HOLDER\n",
       "22423                REGENCY CAKESTAND 3 TIER\n",
       "85099B                JUMBO BAG RED RETROSPOT\n",
       "47566                           PARTY BUNTING\n",
       "20725                 LUNCH BAG RED RETROSPOT\n",
       "84879           ASSORTED COLOUR BIRD ORNAMENT\n",
       "22720       SET OF 3 CAKE TINS PANTRY DESIGN \n",
       "22197                    SMALL POPCORN HOLDER\n",
       "21212         PACK OF 72 RETROSPOT CAKE CASES\n",
       "20727                 LUNCH BAG  BLACK SKULL."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_description = df.loc[df['StockCode'].isin(stock_sale_frequency_top10.index), ['StockCode', 'Description']] \\\n",
    "    .drop_duplicates(\"StockCode\").set_index(\"StockCode\")\n",
    "\n",
    "stock_description.loc[stock_sale_frequency_top10.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\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>InvoiceNo</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>TotalPrice</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StockCode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>85123A</th>\n",
       "      <td>2313</td>\n",
       "      <td>38830</td>\n",
       "      <td>97894.50</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22423</th>\n",
       "      <td>2203</td>\n",
       "      <td>12980</td>\n",
       "      <td>164762.19</td>\n",
       "      <td>REGENCY CAKESTAND 3 TIER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85099B</th>\n",
       "      <td>2159</td>\n",
       "      <td>47363</td>\n",
       "      <td>92356.03</td>\n",
       "      <td>JUMBO BAG RED RETROSPOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47566</th>\n",
       "      <td>1727</td>\n",
       "      <td>18022</td>\n",
       "      <td>98302.98</td>\n",
       "      <td>PARTY BUNTING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20725</th>\n",
       "      <td>1639</td>\n",
       "      <td>18979</td>\n",
       "      <td>35187.31</td>\n",
       "      <td>LUNCH BAG RED RETROSPOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84879</th>\n",
       "      <td>1502</td>\n",
       "      <td>36221</td>\n",
       "      <td>58959.73</td>\n",
       "      <td>ASSORTED COLOUR BIRD ORNAMENT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22720</th>\n",
       "      <td>1477</td>\n",
       "      <td>7286</td>\n",
       "      <td>37413.44</td>\n",
       "      <td>SET OF 3 CAKE TINS PANTRY DESIGN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22197</th>\n",
       "      <td>1476</td>\n",
       "      <td>56450</td>\n",
       "      <td>50987.47</td>\n",
       "      <td>SMALL POPCORN HOLDER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21212</th>\n",
       "      <td>1385</td>\n",
       "      <td>36039</td>\n",
       "      <td>21059.72</td>\n",
       "      <td>PACK OF 72 RETROSPOT CAKE CASES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20727</th>\n",
       "      <td>1350</td>\n",
       "      <td>12112</td>\n",
       "      <td>22219.01</td>\n",
       "      <td>LUNCH BAG  BLACK SKULL.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           InvoiceNo  Quantity  TotalPrice                         Description\n",
       "StockCode                                                                     \n",
       "85123A          2313     38830    97894.50  WHITE HANGING HEART T-LIGHT HOLDER\n",
       "22423           2203     12980   164762.19            REGENCY CAKESTAND 3 TIER\n",
       "85099B          2159     47363    92356.03             JUMBO BAG RED RETROSPOT\n",
       "47566           1727     18022    98302.98                       PARTY BUNTING\n",
       "20725           1639     18979    35187.31             LUNCH BAG RED RETROSPOT\n",
       "84879           1502     36221    58959.73       ASSORTED COLOUR BIRD ORNAMENT\n",
       "22720           1477      7286    37413.44   SET OF 3 CAKE TINS PANTRY DESIGN \n",
       "22197           1476     56450    50987.47                SMALL POPCORN HOLDER\n",
       "21212           1385     36039    21059.72     PACK OF 72 RETROSPOT CAKE CASES\n",
       "20727           1350     12112    22219.01             LUNCH BAG  BLACK SKULL."
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_sale_frequency_top10['Description'] = stock_description.loc[stock_sale_frequency_top10.index]\n",
    "stock_sale_frequency_top10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "u4-hkkCTVUqH"
   },
   "source": [
    "## 구매 취소 비율"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "aUI6c0IeVUqH"
   },
   "outputs": [],
   "source": [
    "df[\"Cancel\"] = df[\"Quantity\"] < 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 394
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1634789343914,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "P7xYrPbLVUqH",
    "outputId": "66248cb6-4ad0-4e3f-b102-1213fa7aefec",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Cancel</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.0</th>\n",
       "      <td>182.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.0</th>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349.0</th>\n",
       "      <td>73.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.0</th>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18280.0</th>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18281.0</th>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18282.0</th>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18283.0</th>\n",
       "      <td>756.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18287.0</th>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4372 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Cancel      False  True\n",
       "CustomerID             \n",
       "12346.0       1.0   1.0\n",
       "12347.0     182.0   NaN\n",
       "12348.0      31.0   NaN\n",
       "12349.0      73.0   NaN\n",
       "12350.0      17.0   NaN\n",
       "...           ...   ...\n",
       "18280.0      10.0   NaN\n",
       "18281.0       7.0   NaN\n",
       "18282.0      12.0   1.0\n",
       "18283.0     756.0   NaN\n",
       "18287.0      70.0   NaN\n",
       "\n",
       "[4372 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 고객별 구매취소 비율\n",
    "df.groupby(\"CustomerID\")[\"Cancel\"].value_counts().unstack()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YyAUqbnzVUqH"
   },
   "source": [
    "### 특정 고객의 구매 건 조회"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1634789343914,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "alPR3Eb0VUqI",
    "outputId": "cfde4183-1c0c-4c3d-de77-e27fff07a49a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>Cancel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16061.0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16262.0</th>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12503.0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12505.0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17547.0</th>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15494.0</th>\n",
       "      <td>125</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13325.0</th>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13323.0</th>\n",
       "      <td>21</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15500.0</th>\n",
       "      <td>68</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18287.0</th>\n",
       "      <td>70</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4372 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            InvoiceNo  Cancel\n",
       "CustomerID                   \n",
       "16061.0             1     1.0\n",
       "16262.0             3     1.0\n",
       "12503.0             1     1.0\n",
       "12505.0             1     1.0\n",
       "17547.0             2     1.0\n",
       "...               ...     ...\n",
       "15494.0           125     0.0\n",
       "13325.0            12     0.0\n",
       "13323.0            21     0.0\n",
       "15500.0            68     0.0\n",
       "18287.0            70     0.0\n",
       "\n",
       "[4372 rows x 2 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# InvoiceNo : 구매한 상품 개수\n",
    "# Cancel : 구매한 상품 대비 취소 건수\n",
    "\n",
    "cancel_customer_proportion = df.groupby(\"CustomerID\").aggregate(\n",
    "    {\"InvoiceNo\": \"count\", \"Cancel\": \"mean\"}\n",
    ").sort_values(by=[\"Cancel\"], ascending=False)\n",
    "\n",
    "cancel_customer_proportion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xSJJO4XrVUqJ"
   },
   "source": [
    "### 국가별 구매 취소 비율"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 394
    },
    "executionInfo": {
     "elapsed": 15,
     "status": "ok",
     "timestamp": 1634789344442,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "rZIX9ubCVUqJ",
    "outputId": "4f3acf32-35d4-43a2-fded-3e2a0b15b261"
   },
   "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>InvoiceNo</th>\n",
       "      <th>Cancel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>USA</th>\n",
       "      <td>291</td>\n",
       "      <td>0.384880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Czech Republic</th>\n",
       "      <td>30</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malta</th>\n",
       "      <td>127</td>\n",
       "      <td>0.118110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>358</td>\n",
       "      <td>0.103352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>10</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>1259</td>\n",
       "      <td>0.058777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>803</td>\n",
       "      <td>0.056040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahrain</th>\n",
       "      <td>19</td>\n",
       "      <td>0.052632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>9495</td>\n",
       "      <td>0.047709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EIRE</th>\n",
       "      <td>8196</td>\n",
       "      <td>0.036847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <td>341</td>\n",
       "      <td>0.032258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>229</td>\n",
       "      <td>0.030568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sweden</th>\n",
       "      <td>462</td>\n",
       "      <td>0.023810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Denmark</th>\n",
       "      <td>389</td>\n",
       "      <td>0.023136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>2533</td>\n",
       "      <td>0.018950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Kingdom</th>\n",
       "      <td>495478</td>\n",
       "      <td>0.018552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>2069</td>\n",
       "      <td>0.018366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Switzerland</th>\n",
       "      <td>2002</td>\n",
       "      <td>0.017483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>8557</td>\n",
       "      <td>0.017413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>European Community</th>\n",
       "      <td>61</td>\n",
       "      <td>0.016393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finland</th>\n",
       "      <td>695</td>\n",
       "      <td>0.014388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>288</td>\n",
       "      <td>0.013889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Channel Islands</th>\n",
       "      <td>758</td>\n",
       "      <td>0.013193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norway</th>\n",
       "      <td>1086</td>\n",
       "      <td>0.012891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cyprus</th>\n",
       "      <td>622</td>\n",
       "      <td>0.012862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>1519</td>\n",
       "      <td>0.011850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>401</td>\n",
       "      <td>0.007481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>146</td>\n",
       "      <td>0.006849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>297</td>\n",
       "      <td>0.006734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netherlands</th>\n",
       "      <td>2371</td>\n",
       "      <td>0.003374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>68</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lithuania</th>\n",
       "      <td>35</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RSA</th>\n",
       "      <td>58</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>32</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lebanon</th>\n",
       "      <td>45</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>151</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iceland</th>\n",
       "      <td>182</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unspecified</th>\n",
       "      <td>446</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      InvoiceNo    Cancel\n",
       "Country                                  \n",
       "USA                         291  0.384880\n",
       "Czech Republic               30  0.166667\n",
       "Malta                       127  0.118110\n",
       "Japan                       358  0.103352\n",
       "Saudi Arabia                 10  0.100000\n",
       "Australia                  1259  0.058777\n",
       "Italy                       803  0.056040\n",
       "Bahrain                      19  0.052632\n",
       "Germany                    9495  0.047709\n",
       "EIRE                       8196  0.036847\n",
       "Poland                      341  0.032258\n",
       "Singapore                   229  0.030568\n",
       "Sweden                      462  0.023810\n",
       "Denmark                     389  0.023136\n",
       "Spain                      2533  0.018950\n",
       "United Kingdom           495478  0.018552\n",
       "Belgium                    2069  0.018366\n",
       "Switzerland                2002  0.017483\n",
       "France                     8557  0.017413\n",
       "European Community           61  0.016393\n",
       "Finland                     695  0.014388\n",
       "Hong Kong                   288  0.013889\n",
       "Channel Islands             758  0.013193\n",
       "Norway                     1086  0.012891\n",
       "Cyprus                      622  0.012862\n",
       "Portugal                   1519  0.011850\n",
       "Austria                     401  0.007481\n",
       "Greece                      146  0.006849\n",
       "Israel                      297  0.006734\n",
       "Netherlands                2371  0.003374\n",
       "United Arab Emirates         68  0.000000\n",
       "Lithuania                    35  0.000000\n",
       "RSA                          58  0.000000\n",
       "Brazil                       32  0.000000\n",
       "Lebanon                      45  0.000000\n",
       "Canada                      151  0.000000\n",
       "Iceland                     182  0.000000\n",
       "Unspecified                 446  0.000000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancel_country_proportion = df.groupby([\"Country\"]).aggregate(\n",
    "                                                    {\"InvoiceNo\": \"count\", \"Cancel\": \"mean\"},\n",
    "                                                    ).sort_values(by=[\"Cancel\"], ascending=False)\n",
    "\n",
    "cancel_country_proportion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OAeweOlzVUqJ"
   },
   "source": [
    "## 날짜와 시간"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 14,
     "status": "ok",
     "timestamp": 1634789344443,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "7stfxt2XVUqJ",
    "outputId": "30e13872-d61a-4166-d760-b4236bd95915"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        2010-12-01 08:26:00\n",
       "1        2010-12-01 08:26:00\n",
       "2        2010-12-01 08:26:00\n",
       "3        2010-12-01 08:26:00\n",
       "4        2010-12-01 08:26:00\n",
       "                 ...        \n",
       "541904   2011-12-09 12:50:00\n",
       "541905   2011-12-09 12:50:00\n",
       "541906   2011-12-09 12:50:00\n",
       "541907   2011-12-09 12:50:00\n",
       "541908   2011-12-09 12:50:00\n",
       "Name: InvoiceDate, Length: 541909, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InvoiceDate\"] = pd.to_datetime(df[\"InvoiceDate\"])\n",
    "df[\"InvoiceDate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 170
    },
    "executionInfo": {
     "elapsed": 328,
     "status": "ok",
     "timestamp": 1634789344762,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "sVkvqHweVUqK",
    "outputId": "74ebfa68-6106-451a-8e0e-88307f3307d5"
   },
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPrice</th>\n",
       "      <th>Cancel</th>\n",
       "      <th>InvoiceYear</th>\n",
       "      <th>InvoiceMonth</th>\n",
       "      <th>InvoiceDay</th>\n",
       "      <th>InvoiceDow</th>\n",
       "      <th>InvoiceTime</th>\n",
       "      <th>InvoiceHour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.3</td>\n",
       "      <td>False</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>08:26:00</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                         Description  Quantity  \\\n",
       "0    536365    85123A  WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "\n",
       "          InvoiceDate  UnitPrice  CustomerID         Country  TotalPrice  \\\n",
       "0 2010-12-01 08:26:00       2.55     17850.0  United Kingdom        15.3   \n",
       "\n",
       "   Cancel  InvoiceYear  InvoiceMonth  InvoiceDay InvoiceDow InvoiceTime  \\\n",
       "0   False         2010            12           1  Wednesday    08:26:00   \n",
       "\n",
       "   InvoiceHour  \n",
       "0            8  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InvoiceYear\"] = df[\"InvoiceDate\"].dt.year\n",
    "df[\"InvoiceMonth\"] = df[\"InvoiceDate\"].dt.month\n",
    "df[\"InvoiceDay\"] = df[\"InvoiceDate\"].dt.day\n",
    "df[\"InvoiceDow\"] = df[\"InvoiceDate\"].dt.strftime(\"%A\")\n",
    "# df[\"InvoiceDow\"] = df[\"InvoiceDate\"].dt.dayofweek\n",
    "df[\"InvoiceTime\"] = df[\"InvoiceDate\"].dt.time\n",
    "df[\"InvoiceHour\"] = df[\"InvoiceDate\"].dt.hour\n",
    "df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 170
    },
    "executionInfo": {
     "elapsed": 1120,
     "status": "ok",
     "timestamp": 1634789346201,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "p4Gr-7GiVUqK",
    "outputId": "9b0c9bd6-a26f-42d3-b9b2-8ccbcbe3b19f"
   },
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPrice</th>\n",
       "      <th>Cancel</th>\n",
       "      <th>InvoiceYear</th>\n",
       "      <th>InvoiceMonth</th>\n",
       "      <th>InvoiceDay</th>\n",
       "      <th>InvoiceDow</th>\n",
       "      <th>InvoiceTime</th>\n",
       "      <th>InvoiceHour</th>\n",
       "      <th>InvoiceYM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.3</td>\n",
       "      <td>False</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>08:26:00</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                         Description  Quantity  \\\n",
       "0    536365    85123A  WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "\n",
       "          InvoiceDate  UnitPrice  CustomerID         Country  TotalPrice  \\\n",
       "0 2010-12-01 08:26:00       2.55     17850.0  United Kingdom        15.3   \n",
       "\n",
       "   Cancel  InvoiceYear  InvoiceMonth  InvoiceDay InvoiceDow InvoiceTime  \\\n",
       "0   False         2010            12           1  Wednesday    08:26:00   \n",
       "\n",
       "   InvoiceHour InvoiceYM  \n",
       "0            8   2010-12  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"InvoiceYM\"] = df[\"InvoiceDate\"].dt.strftime(\"%Y-%m\")\n",
    "df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 13,
     "status": "ok",
     "timestamp": 1634789346545,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "UiLRfNfRVUqK",
    "outputId": "f6da291f-7e90-4575-b202-a0fe29008926"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceYear', ylabel='count'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"InvoiceYear\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 437,
     "status": "ok",
     "timestamp": 1634789346976,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "XzJ5efozVUqL",
    "outputId": "74f9ec47-31a1-4046-b95d-d2396cd6487a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceMonth', ylabel='count'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"InvoiceMonth\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 620,
     "status": "ok",
     "timestamp": 1634789347592,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "t8GRdWq_VUqL",
    "outputId": "a160294e-85f8-4234-9532-f9532b9ffb17"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vqm4CbgJYunTpzsaVJI2ZMz5xR9dTmNWnz3xL11OQtIAMu03l7iTXJjmsvX4LuGuIfj8OHJ1kbZK1wDHtnwGOnrqofcPn1BaWzf2xdjy16l0D3wY6FXuc7avnU45s7ZIkSdJYGqoYr6qrgfuB/9xeX6mq9w7Rb2VVLauqk6vqZODh9s8bgDOSHNwuPRe4rR3fClyaBrgIWN1it7P9Qc8DgFOAu9v+8eeSHN9ixwFPVtUzw+QnSZIkdWHYbSpU1W1sL5jnpKqeT3IFsCbJNuBBep+2QlVtTHIvveL/JWB1VT3cul4PrEpyX4td1veRi5cAtyTZH3iW7Q99SpIkSWNp6GJ8T6iq7+87Xgssm+G6lcDKadq3AufP0OcJeh93KEmSJC0Iw+4ZlyRJkrSHzevKuCQtBKd/6pe7nsKs7vzxX+t6CpKkPcBiXOrIBz/0pq6nMKuz3/EHXU9Bc/TmT97c9RRm9Zmf/HddT0GSOuM2FUmSJKkjFuOSJElSRyzGJUmSpI64Z3zCPXH9uV1PYVbfftHq2S+SpAnzk5+8v+spzOqTP/l9XU9BmniujEuSJEkdsRiXJEmSOmIxLkmSJHXEYlySJEnqiMW4JEmS1BGLcUmSJKkjFuOSJElSRyzGJUmSpI5YjEuSJEkdGWkxnuQVSf5Lkt9Pcm+STyY5oMVOTLIuyfokNydZ3NdvRZIHkmxMcmFf+6IkN7Y+65Oc1Bc7NMldbcx7khw2ytwkSZKkuRr1yvjLgA9U1Y9U1UnA54AVSfYFrgZOr6rXAQ8BFwAkOQY4DVgKnACcnOTYNt4KYFPrcypwVRsL4DrgyqpaBlwOXDvi3CRJkqQ5GWkxXlVPVdWDAK1oPhJ4BFgOrKmqp9qlq4Az2/F5wDXV0Cuyz2mxs4Ab2thPA3cCy5McBBxSVetabANwYGvfQVt135Bkw5YtW/Z0ypIkSdLQFs9+ydwkeQtwCXAE8KfAr9Irrh+duqaqXuxb4T6qPwY81toAFlXVC9PEngA2Ddx6c7vnH/c3VtVNwE0AS5curd3NS9J2V/y35V1PYVZX/Zs1XU9BkqRvMPIHOKvqjqp6Q1W9BlgN/DYQYLAQnjrfWWzaW8zQZ7Z+kiRJUqfm9dNUqup24HB6q9ZHT7Un2Q/Y1k53iLXjqVXvatcOxh5n++r5lCNbuyRJkjSWRv1pKockOaXv/O3Al4E1wBlJDm6hc4Hb2vGtwKVpgIvoragD3M72Bz0PAE4B7m77x59LcnyLHQc8WVXPjDI/SZIkaS5GvWf8OeCnkvwa8A/09oK/u6qeT3IFsCbJNuBB4GKAqtqY5F7gfuAlYHVVPdzGux5YleS+Frusqra22CXALUn2B55l+0OfkiRJ0lgaaTFeVf9I7+MIp4utBZbNEFsJrJymfStw/gx9nqD3cYeaUJ9//5u7nsKsfvD8z3Q9BUmStID4DZySJElSRyzGJUmSpI5YjEuSJEkdsRiXJEmSOjLyb+CUJEmS9oS/Xvmlrqcwq0N//gd26XpXxiVJkqSOWIxLkiRJHbEYlyRJkjpiMS5JkiR1xGJckiRJ6ojFuCRJktQRi3FJkiSpIxbjkiRJUkcsxiVJkqSOWIxLkiRJHRlpMZ7k9Uk+neTzSf4oyamt/cQk65KsT3JzksV9fVYkeSDJxiQX9rUvSnJj67M+yUl9sUOT3NXGvCfJYaPMS5IkSdoTRr0yvgh4a1X9IPBm4Jok+wJXA6dX1euAh4ALAJIcA5wGLAVOAE5OcmwbawWwqfU5FbiqjQVwHXBlVS0DLgeuHXFekiRJ0pyNtBivqnur6u/a6TPAPwLLgTVV9VRrXwWc2Y7PA66phl6RfU6LnQXc0MZ9GrgTWJ7kIOCQqlrXYhuAA1u7JEmSNLbmZc94kn3orVbfAhwFPDoVq6oXgakV7h1iwGOtDWBRVb0wTewIYNPALTe39unmsiLJhiQbtmzZsnsJSZIkSXvAyIvxJN8K/C7wxaq6CQhQA5dNne8sNp2aoc+M/arqpqpaWlVLlyxZMtv0JUmSpJEZ9QOcrwU+APxCVf1ea94MHN13zX7Atuli7Xhq1bvatYOxx9m+ej7lyNYuSZIkja1Rr4xfCZxbVU/0ta0BzkhycDs/F7itHd8KXJoGuAhY3WK3s/1BzwOAU4C72/7x55Ic32LHAU9W1TMjy0qSJEnaAxbPfsmcvB74eK+u/rrzgSuANUm2AQ8CFwNU1cYk9wL3Ay8Bq6vq4dbvemBVkvta7LKq2tpilwC3JNkfeJbtD31KkiRJY2ukxXhVDW4fmbIJWDZDn5XAymnat9Ir5Kfr8wS9jzuUJEmSFgy/gVOSJEnqiMW4JEmS1BGLcUmSJKkjFuOSJElSRyzGJUmSpI5YjEuSJEkdsRiXJEmSOmIxLkmSJHXEYlySJEnqiMW4JEmS1BGLcUmSJKkjFuOSJElSRyzGJUmSpI5YjEuSJEkdsRiXJEmSOmIxLkmSJHVk3orxJJcneWff+YlJ1iVZn+TmJIv7YiuSPJBkY5IL+9oXJbmx9Vmf5KS+2KFJ7mpj3pPksPnKTZIkSdodIy/Gk7w6yX3Au/va9gWuBk6vqtcBDwEXtNgxwGnAUuAE4OQkx7auK4BNrc+pwFVtLIDrgCurahlwOXDtqHOTJEmS5mLkxXhV/XlVfT/wC33Ny4E1VfVUO18FnNmOzwOuqYZekX1Oi50F3NDGfRq4E1ie5CDgkKpa12IbgANb+w7aqvuGJBu2bNmyBzOVJEmSdk1Xe8aPAh6dOqmqF4F9p4sBj7U2gEVV9cI0sSOATQP32Nzad1BVN1XV0qpaumTJkjklIUmSJM1FV8V4gBpoqyFi06kZ+szWT5IkSepUV8X4ZuDoqZMk+wHbpou146lV72rXDsYeZ/vq+ZQjW7skSZI0lroqxtcAZyQ5uJ2fC9zWjm8FLk0DXASsbrHb2f6g5wHAKcDdbf/4c0mOb7HjgCer6pn5SEaSJEnaHYtnv2TPq6rnk1wBrEmyDXgQuLjFNia5F7gfeAlYXVUPt67XA6vap7O8BFxWVVtb7BLgliT7A8+y/aFPSZIkaSzNWzFeVR8cOF8LLJvh2pXAymnatwLnz9DnCXofdyhJkiQtCH4DpyRJktQRi3FJkiSpIxbjkiRJUkcsxiVJkqSOWIxLkiRJHbEYlyRJkjpiMS5JkiR1xGJckiRJ6ojFuCRJktQRi3FJkiSpIxbjkiRJUkcsxiVJkqSOWIxLkiRJHbEYlyRJkjpiMS5JkiR1ZKKK8SSHJrkrybok9yQ5rOs5SZIkSTOZqGIcuA64sqqWAZcD13Y8H0mSJGlGE1OMJzkIOKSq1gFU1QbgwNYuSZIkjZ1UVddz2COS/Evg3Kq6uK/tfcDqqvrjvrYVwIp2+l3Ao/MwvVcBT87DfebDJOUCk5XPJOUCk5XPJOUCk5XPJOUCk5XPJOUCk5XPJOUC85fPd1TVksHGxfNw4/kSYLqfLHZoq6qbgJvmZUZNkg1VtXQ+7zkqk5QLTFY+k5QLTFY+k5QLTFY+k5QLTFY+k5QLTFY+k5QLdJ/PxGxTAR4HjhpoO7K1S5IkSWNnYorxqnoaeC7J8QBJjgOerKpnOp2YJEmSNINJ2qYCcAlwS5L9gWeBc7qdztfN67aYEZukXGCy8pmkXGCy8pmkXGCy8pmkXGCy8pmkXGCy8pmkXKDjfCbmAU5JkiRpoZmYbSqSJEnSQmMxLkmSJHXEYlySJEnqiMV4nySvT/LpJJ9P8kdJTm3tJyZZl2R9kpuTLB7od0CSPx1oW5TkxtZnfZKThpzD5UneOdB2dpI/TLI2yR8kee1859MXOzHJx4a496FJ7mr3uSfJYQPxfVr8uxdyLpP03iQ5MslHk3wmyf1JrlqouQxcc8UwY41zPkm+P8mD7c/Z1OufL8RcWuxVSW5reXwxyZtmG29c80lywsD78sUkH1mIubTYG1sOX2ivY2Ybb8zz+ekkX2rzujHJN49zLn3XT1cL7PT+Cy2f1r5gaoGd5ZLdrAW+rqp8tRdwEvAt7fhg4E+BfYEvAoe09ncBF/b1uQJ4BHhiYKyfBd7djl/Zxth3J/d+NXAfsAV450DsVGBRO349cNt859Nit9P73PaPDXHvjwDL2vFS4KN9sTcDfwL8PfDdCzyXiXlvgGOAQ/uuuw1YuhBz6YsvBT4+zFjjnA9wMvDrw+Ywzrm08/8OnNyOFwGvWcj5DFx3Vv/9F1ou9P7b/Mp2/K+ATy/U94bed43cA+zXzv8t8N4xz2XaWmC2+y+0fFpsodUCe7xO+3r/Xbl4b3rR+0bPdcAZwC/3te8HfH6a6+8bOP8C8E19578EnDHEfc8efJOn+cPwqfnOp6/98Nn+0AIHAXcNtH0GOGig7YPD/gUc91wm8L05GLgT+CcLNRfgFcAnge+abaxxz4fdLMbHNJfvA26ZSy7jlM80194NvGKh5gL8EduLiu8GVi3U9wY4E7h0IPbFcc1l4Pqz2bEYH+r+CyWfgdgHGfNaYNhcWnyXawG3qUwjyT7AtcAt9L7V89GpWFW9SO+nsNksqqoX+s4f4xu/IXRX53Ug8DvAr+5ivz2Rz644Atg00La5tc/JuOYyKe9Nkvck+RLwZ8ADwNeGHXjccgF+HXgP8AK7YQzzWZrk423rwG8lefmwA49ZLv8S2NByWJvkjl39le6Y5dM/r38NPFBV/zDswGOYy3uAjyV5N3AVcNmuDD5m+fxP4Iwkr0jP2cA/S/KqYQbuIJedmfP9xyyfORnXXHa3FrAYH5DkW4HfpffT8030fvKqgcsGz4e1u/1IcgK9nx5/sao27kK/UeYz421nGHNO9xnXXCbpvamqX6mqHwC+FXg5sGKoQccslyQ/BjxeVdPuEZx14DHLB/hfwI3A26rqDfR+rXrFUIOOXy7701tZ+kBVnQxcDbx/6IHHL59+FwPXDz3omOXSfsD7MXoFzkp62z/en2TRUAOPWT5V9Qi9L3O5E7gL2AZsBP521kG7yWWnU5rL/ccwn902rrnsbi0Ak/cNnHPSVmfeB1xQVU+05s30flU3dc1+9P5Cz6aS7Nd+QgM4GvgfbbXhR1vbF6rqV4aY14/R+zXMz1TV88Nls8fzmeke0+XzON/4W4AjW/vu3mcsc5nU96aqtiX5OPC2Ie4zjrn8IvDqJGcALwNem2Qt8ENV9dJCy6eqnqG3t3HKR+gVTLPdZ+xyobeK+XtV9ScAVXXfsKv8Y5rPVL+jgb+vqr8Y8j7jmMs76P0qf01rvyPJcuBY4MEFmA9V9VHgo63/K4Gf7/v/8rjlsjO7ff8xzWd37zOWuexuLfB1u7KnZdJfwK30PcDW2l4GfBk4uJ2/E/jZafoO7hn/98DF7fgA4LPs5AHOvn5n840Pbfx3YJ8u8+lrP5zhHnT4BHB8Oz4OuHWaaz7I8A9tjF0uk/beACcAR7XjfYCbGe45h7HLZXfGGud8gMPoe8gR+GXgXQs0l28C7gW+o50fA3xmob43ffFVwL9Y4H/Ofore3/t92vm30VtJPnAh5tPOp/6bthj4EPAT45xL3/Vns2MtMNT9F0o+A7EPsgBqgZ28N7tdC0y9XBnf0euBjyfpbzuf3q+D1yTZRm914OIhxroeWJXkPuAl4LKq2robc/pO4HuBz/XN6++r6keG6Lsn89lVlwC3JNkfeBY4Z47jjWMuk/bePAtcl+RQYCvwiar69BDjjWMuczGO+RRwTZKDgG8GPk9vT/xsxi6XqnohyQXATW0F6++AnxtyzLHLB6DtQf72qtrp6vGAsculqm5L7yPmvpzkeXrPW7yzqp4dYsyxy6d5Z5Jl9B7o/kBV3T5N/0Fd5jKtqno+ye7ef+zymYNxzGUutQAAaVW9JEmSpHnmA5ySJElSRyzGJUmSpI5YjEuSJEkdsRiXJEmSOmIxLkmSJHXEYlySJlCSs5O8s4P7np/k6oG2U5Lc3ub0F0m+4WN1k7w1yV/N30wlaTxYjEuSZpTkPe3zwId1C/D6JN/Z+i8CrqL3RWgA/0jvK9cHvR342lzmKkkLkcW4JGlGVfUrNcvXhw9cX8C7gWtb0wrg01X11Xb+IQa+nCnJ9wJ/Bjw35wlL0gJjMS5JEyzJuUnuTrI+yX9Ksk+S+9K+Ki7Jy5Pc1o4vTnJvki8neWtrW5vkZUm+M8nvJ/nDJHcmOTzJq5PckeSzSf5rkpcDVNV64GtJzgL+LXBN35S+BvxtkiP72i4Cfnse/nVI0tj5hn17kqSJ8nbgzfS2h3wG+G7gXuBE4I+AHwE+leQNwA8Ab6D3/4ZPJ/mTNsYiettP3l5VX03y7cCB9Fa/f6mqHkzyduDngV9vfS4HHgHOrqoXBuZ0E70V8/+Q5GDg1VX10MBXXEvSXsGVcUmabKuq6rm2feR+4J8Cvwv8mxY/Hfg94AzgfVX1/9q2lJuB09o13wH876mtJlX1BPBV4PuA30qyll5x/fXV7qp6EvifwGcHJ1RVa4Hvb3vRz6W3dUWS9kqujEvSZBt8KDJV9SdJ3pvkW4AXquofkhRQfdf1n8+0ZL2xqn54N+d1B3Am8BPAD+7mGJK04LkyLkl7py/S+5STO9r5p4CfS89+wL8D7mqxx4FjkrwWIMlrgMOBF9rDlyQ5cGqf+ZA+BLwXWLsrD4hK0qRxZVyS9k4fBb5C75NPqKovJ/ke4PPAy4CVVfVI28f9EnA2cEOSVwB/C1xIr2C/IckrgX8Arhj25lX1N0n+kN7+cUnaa6W3jVCSJEnSfHObiiRJktQRi3FJkiSpIxbjkiRJUkcsxiVJkqSOWIxLkiRJHbEYlyRJkjpiMS5JkiR15P8DifgL/eFeWo0AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.countplot(x=\"InvoiceYM\", data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PsbAaCqsVUqL"
   },
   "source": [
    "### 요일별 빈도수"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 823,
     "status": "ok",
     "timestamp": 1634789348410,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "4JKPmUJrVUqL",
    "outputId": "ddca263f-7ebf-48bf-a786-fb3246df16ce"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceDow', ylabel='count'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"InvoiceDow\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 1002,
     "status": "ok",
     "timestamp": 1634789349408,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "H9Z3y8t7VUqL",
    "outputId": "acb32dbc-c985-4dfa-c778-5cff558edf1f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceDow', ylabel='count'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"InvoiceDow\", data=df, hue=\"Cancel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 313
    },
    "executionInfo": {
     "elapsed": 649,
     "status": "ok",
     "timestamp": 1634789350049,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "MotdJ6kyVUqM",
    "outputId": "48517aa5-8d36-4157-d967-fe4bf652cf5b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'요일 별 구매 취소'}, xlabel='InvoiceDow', ylabel='count'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"요일 별 구매 취소\")\n",
    "sns.countplot(x=\"InvoiceDow\", data=df[df[\"Cancel\"] == True])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 14,
     "status": "ok",
     "timestamp": 1634789350052,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "pXzpmaMEVUqM",
    "outputId": "54f2f4a4-07f0-4534-94b3-0704a5e3eed7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Thursday     103857\n",
       "Tuesday      101808\n",
       "Monday        95111\n",
       "Wednesday     94565\n",
       "Friday        82193\n",
       "Sunday        64375\n",
       "Name: InvoiceDow, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['InvoiceDow'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 678,
     "status": "ok",
     "timestamp": 1634789354142,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "yXpnGPBEVUqR",
    "outputId": "8cf7ae41-0dcf-4f32-9b9e-83f1103244dd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceHour', ylabel='count'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.countplot(x=\"InvoiceHour\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 284
    },
    "executionInfo": {
     "elapsed": 16,
     "status": "ok",
     "timestamp": 1634789354143,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "wFghJwAdVUqS",
    "outputId": "367c401c-9608-43c0-d539-30e58c549640"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceHour', ylabel='TotalPrice'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.pointplot(x=\"InvoiceHour\", y=\"TotalPrice\", data=df, estimator=len, ci=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 시간-요일별 빈도수"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 13,
     "status": "ok",
     "timestamp": 1634789350818,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "YU1ofas-VUqP",
    "outputId": "83656899-4ae7-442e-a92d-03a99b4dc67e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.pointplot(x=\"InvoiceHour\", y=\"TotalPrice\", data=df, estimator=len, ci=None, hue=\"InvoiceDow\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 551
    },
    "executionInfo": {
     "elapsed": 773,
     "status": "ok",
     "timestamp": 1634789350817,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "T_DEDaZSVUqO",
    "outputId": "a0affbfe-c48d-4ddb-8c63-ba52a86b3641"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='InvoiceDow', ylabel='InvoiceHour'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(pd.crosstab(df[\"InvoiceHour\"], df[\"InvoiceDow\"]), cmap=\"Purples\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YdPRyVg9VUqS"
   },
   "source": [
    "## 고객ID가 없는 주문과 취소 주문은 전체 데이터에서 제외"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "x2fmqp02VUqS"
   },
   "source": [
    "* 취소와 취소에 대한 본 주문건 제거\n",
    "* 고객ID가 없는 건도 제거"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 911
    },
    "executionInfo": {
     "elapsed": 334,
     "status": "ok",
     "timestamp": 1634789354905,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "UkxMnfspVUqc",
    "outputId": "fdba401d-fae8-4b2f-aa31-84cbbf5f550d"
   },
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPrice</th>\n",
       "      <th>Cancel</th>\n",
       "      <th>InvoiceYear</th>\n",
       "      <th>InvoiceMonth</th>\n",
       "      <th>InvoiceDay</th>\n",
       "      <th>InvoiceDow</th>\n",
       "      <th>InvoiceTime</th>\n",
       "      <th>InvoiceHour</th>\n",
       "      <th>InvoiceYM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.3</td>\n",
       "      <td>False</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>08:26:00</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                         Description  Quantity  \\\n",
       "0    536365    85123A  WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "\n",
       "          InvoiceDate  UnitPrice  CustomerID         Country  TotalPrice  \\\n",
       "0 2010-12-01 08:26:00       2.55     17850.0  United Kingdom        15.3   \n",
       "\n",
       "   Cancel  InvoiceYear  InvoiceMonth  InvoiceDay InvoiceDow InvoiceTime  \\\n",
       "0   False         2010            12           1  Wednesday    08:26:00   \n",
       "\n",
       "   InvoiceHour InvoiceYM  \n",
       "0            8   2010-12  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_valid = df[(df[\"CustomerID\"].notnull()) & (df[\"Quantity\"] > 0) & (df[\"UnitPrice\"] > 0)].copy()\n",
    "df_valid.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 911
    },
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1634789354906,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "dUSmXEq_1BXf",
    "outputId": "1a4f35cb-c23a-485b-9c4f-8c0ef6f071cc"
   },
   "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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPrice</th>\n",
       "      <th>Cancel</th>\n",
       "      <th>InvoiceYear</th>\n",
       "      <th>InvoiceMonth</th>\n",
       "      <th>InvoiceDay</th>\n",
       "      <th>InvoiceDow</th>\n",
       "      <th>InvoiceTime</th>\n",
       "      <th>InvoiceHour</th>\n",
       "      <th>InvoiceYM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.3</td>\n",
       "      <td>False</td>\n",
       "      <td>2010</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>08:26:00</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                         Description  Quantity  \\\n",
       "0    536365    85123A  WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "\n",
       "          InvoiceDate  UnitPrice  CustomerID         Country  TotalPrice  \\\n",
       "0 2010-12-01 08:26:00       2.55     17850.0  United Kingdom        15.3   \n",
       "\n",
       "   Cancel  InvoiceYear  InvoiceMonth  InvoiceDay InvoiceDow InvoiceTime  \\\n",
       "0   False         2010            12           1  Wednesday    08:26:00   \n",
       "\n",
       "   InvoiceHour InvoiceYM  \n",
       "0            8   2010-12  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_valid.drop_duplicates(inplace=True)\n",
    "df_valid.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tZRUYNdmVUqc"
   },
   "source": [
    "## 고객\n",
    "* ARPU(Average Revenue Per User) : \n",
    "    * 가입한 서비스에 대해 가입자 1명이 특정 기간 동안 지출한 평균 금액\n",
    "    * ARPU = 매출 / 중복을 제외한 순수 활동 사용자 수\n",
    "* ARPPU(Average Revenue Per Paying User):\n",
    "    * 지불 유저 1명 당 한 달에 결제하는 평균 금액을 산정한 수치\n",
    "    \n",
    "\n",
    "* [ARPU - 위키백과, 우리 모두의 백과사전](https://ko.wikipedia.org/wiki/ARPU)\n",
    "* [ARPPU](https://terms.naver.com/entry.naver?docId=2028542&cid=42914&categoryId=42915)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
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       "        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>TotalPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>ARPPU</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InvoiceYM</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-12</th>\n",
       "      <td>748957.020</td>\n",
       "      <td>948</td>\n",
       "      <td>790.039051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01</th>\n",
       "      <td>560000.260</td>\n",
       "      <td>783</td>\n",
       "      <td>715.198289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02</th>\n",
       "      <td>498062.650</td>\n",
       "      <td>798</td>\n",
       "      <td>624.138659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-03</th>\n",
       "      <td>683267.080</td>\n",
       "      <td>1020</td>\n",
       "      <td>669.869686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04</th>\n",
       "      <td>493207.121</td>\n",
       "      <td>899</td>\n",
       "      <td>548.617487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-05</th>\n",
       "      <td>723333.510</td>\n",
       "      <td>1079</td>\n",
       "      <td>670.373967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06</th>\n",
       "      <td>691123.120</td>\n",
       "      <td>1051</td>\n",
       "      <td>657.586223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07</th>\n",
       "      <td>681300.111</td>\n",
       "      <td>993</td>\n",
       "      <td>686.102831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08</th>\n",
       "      <td>682680.510</td>\n",
       "      <td>980</td>\n",
       "      <td>696.612765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-09</th>\n",
       "      <td>1019687.622</td>\n",
       "      <td>1302</td>\n",
       "      <td>783.170217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10</th>\n",
       "      <td>1070704.670</td>\n",
       "      <td>1425</td>\n",
       "      <td>751.371698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11</th>\n",
       "      <td>1461756.250</td>\n",
       "      <td>1711</td>\n",
       "      <td>854.328609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12</th>\n",
       "      <td>433668.010</td>\n",
       "      <td>686</td>\n",
       "      <td>632.169111</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            TotalPrice  CustomerID       ARPPU\n",
       "InvoiceYM                                     \n",
       "2010-12     748957.020         948  790.039051\n",
       "2011-01     560000.260         783  715.198289\n",
       "2011-02     498062.650         798  624.138659\n",
       "2011-03     683267.080        1020  669.869686\n",
       "2011-04     493207.121         899  548.617487\n",
       "2011-05     723333.510        1079  670.373967\n",
       "2011-06     691123.120        1051  657.586223\n",
       "2011-07     681300.111         993  686.102831\n",
       "2011-08     682680.510         980  696.612765\n",
       "2011-09    1019687.622        1302  783.170217\n",
       "2011-10    1070704.670        1425  751.371698\n",
       "2011-11    1461756.250        1711  854.328609\n",
       "2011-12     433668.010         686  632.169111"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arppu = df.groupby(\"InvoiceYM\").agg(\n",
    "    {\"TotalPrice\": \"sum\", \"CustomerID\" : \"nunique\"},\n",
    "    )\n",
    "arppu[\"ARPPU\"] = arppu[\"TotalPrice\"] / arppu[\"CustomerID\"]\n",
    "\n",
    "arppu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 319,
     "status": "ok",
     "timestamp": 1634789355218,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "2LqFRCJKVUqd",
    "outputId": "9a3bd4d8-8ab9-4372-ba84-0ce1ce905c01"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "\n",
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       "\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 colspan=\"2\" halign=\"left\">TotalPrice</th>\n",
       "      <th>InvoiceNo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sum</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.0</th>\n",
       "      <td>77183.600000</td>\n",
       "      <td>77183.60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.0</th>\n",
       "      <td>23.681319</td>\n",
       "      <td>4310.00</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.0</th>\n",
       "      <td>57.975484</td>\n",
       "      <td>1797.24</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349.0</th>\n",
       "      <td>24.076027</td>\n",
       "      <td>1757.55</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.0</th>\n",
       "      <td>19.670588</td>\n",
       "      <td>334.40</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18280.0</th>\n",
       "      <td>18.060000</td>\n",
       "      <td>180.60</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18281.0</th>\n",
       "      <td>11.545714</td>\n",
       "      <td>80.82</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18282.0</th>\n",
       "      <td>14.837500</td>\n",
       "      <td>178.05</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18283.0</th>\n",
       "      <td>2.837074</td>\n",
       "      <td>2045.53</td>\n",
       "      <td>721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18287.0</th>\n",
       "      <td>26.246857</td>\n",
       "      <td>1837.28</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4338 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              TotalPrice           InvoiceNo\n",
       "                    mean       sum     count\n",
       "CustomerID                                  \n",
       "12346.0     77183.600000  77183.60         1\n",
       "12347.0        23.681319   4310.00       182\n",
       "12348.0        57.975484   1797.24        31\n",
       "12349.0        24.076027   1757.55        73\n",
       "12350.0        19.670588    334.40        17\n",
       "...                  ...       ...       ...\n",
       "18280.0        18.060000    180.60        10\n",
       "18281.0        11.545714     80.82         7\n",
       "18282.0        14.837500    178.05        12\n",
       "18283.0         2.837074   2045.53       721\n",
       "18287.0        26.246857   1837.28        70\n",
       "\n",
       "[4338 rows x 3 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer_aggregation = df_valid.groupby(\"CustomerID\").agg({\n",
    "    \"TotalPrice\": [\"mean\", \"sum\"], \"InvoiceNo\": \"count\"}\n",
    ")\n",
    "\n",
    "customer_aggregation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MAU(Monthly Active User)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\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>CustomerID</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InvoiceYM</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-12</th>\n",
       "      <td>885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01</th>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02</th>\n",
       "      <td>758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-03</th>\n",
       "      <td>974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04</th>\n",
       "      <td>856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-05</th>\n",
       "      <td>1056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06</th>\n",
       "      <td>991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07</th>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08</th>\n",
       "      <td>935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-09</th>\n",
       "      <td>1266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10</th>\n",
       "      <td>1364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11</th>\n",
       "      <td>1664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12</th>\n",
       "      <td>615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           CustomerID\n",
       "InvoiceYM            \n",
       "2010-12           885\n",
       "2011-01           741\n",
       "2011-02           758\n",
       "2011-03           974\n",
       "2011-04           856\n",
       "2011-05          1056\n",
       "2011-06           991\n",
       "2011-07           949\n",
       "2011-08           935\n",
       "2011-09          1266\n",
       "2011-10          1364\n",
       "2011-11          1664\n",
       "2011-12           615"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_valid.groupby(\"InvoiceYM\").agg({\"CustomerID\": \"nunique\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pttmLPouVUqk"
   },
   "source": [
    "## 월별, 주문건, 중복을 제외한 주문제품 종류 수, 고객 수, 총 주문금액"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 318
    },
    "executionInfo": {
     "elapsed": 318,
     "status": "ok",
     "timestamp": 1634789358304,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "kaoFCIYHVUqk",
    "outputId": "644076c3-3d1b-4ebc-9cc2-d37af490dab9"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\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>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>TotalPrice</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InvoiceYM</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-12</th>\n",
       "      <td>25670</td>\n",
       "      <td>2411</td>\n",
       "      <td>885</td>\n",
       "      <td>80679.600</td>\n",
       "      <td>311048</td>\n",
       "      <td>570422.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01</th>\n",
       "      <td>20988</td>\n",
       "      <td>2121</td>\n",
       "      <td>741</td>\n",
       "      <td>66234.650</td>\n",
       "      <td>348473</td>\n",
       "      <td>568101.310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02</th>\n",
       "      <td>19706</td>\n",
       "      <td>2124</td>\n",
       "      <td>758</td>\n",
       "      <td>62619.480</td>\n",
       "      <td>265027</td>\n",
       "      <td>446084.920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-03</th>\n",
       "      <td>26870</td>\n",
       "      <td>2234</td>\n",
       "      <td>974</td>\n",
       "      <td>87864.790</td>\n",
       "      <td>347582</td>\n",
       "      <td>594081.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04</th>\n",
       "      <td>22433</td>\n",
       "      <td>2217</td>\n",
       "      <td>856</td>\n",
       "      <td>78543.481</td>\n",
       "      <td>291366</td>\n",
       "      <td>468374.331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-05</th>\n",
       "      <td>28073</td>\n",
       "      <td>2219</td>\n",
       "      <td>1056</td>\n",
       "      <td>101500.910</td>\n",
       "      <td>372864</td>\n",
       "      <td>677355.150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06</th>\n",
       "      <td>26926</td>\n",
       "      <td>2339</td>\n",
       "      <td>991</td>\n",
       "      <td>84602.660</td>\n",
       "      <td>363014</td>\n",
       "      <td>660046.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07</th>\n",
       "      <td>26580</td>\n",
       "      <td>2351</td>\n",
       "      <td>949</td>\n",
       "      <td>75454.521</td>\n",
       "      <td>367360</td>\n",
       "      <td>598962.901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08</th>\n",
       "      <td>26790</td>\n",
       "      <td>2356</td>\n",
       "      <td>935</td>\n",
       "      <td>78877.090</td>\n",
       "      <td>397373</td>\n",
       "      <td>644051.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-09</th>\n",
       "      <td>39669</td>\n",
       "      <td>2545</td>\n",
       "      <td>1266</td>\n",
       "      <td>118160.322</td>\n",
       "      <td>543652</td>\n",
       "      <td>950690.202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10</th>\n",
       "      <td>48793</td>\n",
       "      <td>2622</td>\n",
       "      <td>1364</td>\n",
       "      <td>164084.090</td>\n",
       "      <td>591543</td>\n",
       "      <td>1035642.450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11</th>\n",
       "      <td>63168</td>\n",
       "      <td>2695</td>\n",
       "      <td>1664</td>\n",
       "      <td>182340.090</td>\n",
       "      <td>665923</td>\n",
       "      <td>1156205.610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12</th>\n",
       "      <td>17026</td>\n",
       "      <td>2173</td>\n",
       "      <td>615</td>\n",
       "      <td>46559.700</td>\n",
       "      <td>286777</td>\n",
       "      <td>517190.440</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           InvoiceNo  StockCode  CustomerID   UnitPrice  Quantity   TotalPrice\n",
       "InvoiceYM                                                                     \n",
       "2010-12        25670       2411         885   80679.600    311048   570422.730\n",
       "2011-01        20988       2121         741   66234.650    348473   568101.310\n",
       "2011-02        19706       2124         758   62619.480    265027   446084.920\n",
       "2011-03        26870       2234         974   87864.790    347582   594081.760\n",
       "2011-04        22433       2217         856   78543.481    291366   468374.331\n",
       "2011-05        28073       2219        1056  101500.910    372864   677355.150\n",
       "2011-06        26926       2339         991   84602.660    363014   660046.050\n",
       "2011-07        26580       2351         949   75454.521    367360   598962.901\n",
       "2011-08        26790       2356         935   78877.090    397373   644051.040\n",
       "2011-09        39669       2545        1266  118160.322    543652   950690.202\n",
       "2011-10        48793       2622        1364  164084.090    591543  1035642.450\n",
       "2011-11        63168       2695        1664  182340.090    665923  1156205.610\n",
       "2011-12        17026       2173         615   46559.700    286777   517190.440"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "InvoiceYM_aggregation = df_valid.groupby(\"InvoiceYM\").agg({\n",
    "    \"InvoiceNo\": \"count\",\n",
    "    \"StockCode\": \"nunique\",\n",
    "    \"CustomerID\": \"nunique\",\n",
    "    \"UnitPrice\": \"sum\",\n",
    "    \"Quantity\": \"sum\",\n",
    "    \"TotalPrice\": \"sum\"\n",
    "})\n",
    "\n",
    "InvoiceYM_aggregation\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_fBp-TimVUqf"
   },
   "source": [
    "## 월단위 데이터 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "id": "NiKg56-UVUqg"
   },
   "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>InvoiceDate</th>\n",
       "      <th>InvoiceDate1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>61796</th>\n",
       "      <td>2011-01-18 13:05:00</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305178</th>\n",
       "      <td>2011-08-18 10:36:00</td>\n",
       "      <td>2011-08-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259785</th>\n",
       "      <td>2011-07-12 10:47:00</td>\n",
       "      <td>2011-07-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               InvoiceDate InvoiceDate1\n",
       "61796  2011-01-18 13:05:00   2011-01-01\n",
       "305178 2011-08-18 10:36:00   2011-08-01\n",
       "259785 2011-07-12 10:47:00   2011-07-01"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_valid['InvoiceDate1'] = pd.to_datetime(df_valid['InvoiceYM'])\n",
    "df_valid[['InvoiceDate', 'InvoiceDate1']].sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "id": "87EjZ0a5VUqh"
   },
   "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>InvoiceDateMin</th>\n",
       "      <th>InvoiceDate1</th>\n",
       "      <th>InvoiceDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>439435</th>\n",
       "      <td>2011-03-01</td>\n",
       "      <td>2011-11-01</td>\n",
       "      <td>2011-11-04 12:05:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503351</th>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>2011-11-01</td>\n",
       "      <td>2011-11-27 12:10:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378556</th>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-10-01</td>\n",
       "      <td>2011-10-05 12:52:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       InvoiceDateMin InvoiceDate1         InvoiceDate\n",
       "439435     2011-03-01   2011-11-01 2011-11-04 12:05:00\n",
       "503351     2010-12-01   2011-11-01 2011-11-27 12:10:00\n",
       "378556     2011-01-01   2011-10-01 2011-10-05 12:52:00"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_valid[\"InvoiceDateMin\"] = df_valid.groupby([\"CustomerID\"])[\"InvoiceDate1\"].transform(min)\n",
    "df_valid[[\"InvoiceDateMin\", \"InvoiceDate1\", \"InvoiceDate\"]].sample(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 첫 구매일로 부터 몇 달째 구매인가?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "id": "QpDiUiQKVUqh"
   },
   "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>InvoiceDate1</th>\n",
       "      <th>InvoiceDateMin</th>\n",
       "      <th>CohortIndex</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>335297</th>\n",
       "      <td>2011-09-01</td>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361376</th>\n",
       "      <td>2011-09-01</td>\n",
       "      <td>2011-08-01</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249980</th>\n",
       "      <td>2011-07-01</td>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       InvoiceDate1 InvoiceDateMin  CohortIndex\n",
       "335297   2011-09-01     2010-12-01           10\n",
       "361376   2011-09-01     2011-08-01            2\n",
       "249980   2011-07-01     2010-12-01            8"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_diff = df_valid[\"InvoiceDate1\"].dt.year - df_valid[\"InvoiceDateMin\"].dt.year\n",
    "month_diff = df_valid[\"InvoiceDate1\"].dt.month - df_valid[\"InvoiceDateMin\"].dt.month\n",
    "\n",
    "df_valid[\"CohortIndex\"] = year_diff * 12 + month_diff + 1\n",
    "df_valid[[\"InvoiceDate1\", \"InvoiceDateMin\", \"CohortIndex\"]].sample(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Dzrk-uO5VUqi"
   },
   "source": [
    "### 코호트 월별 빈도수"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "executionInfo": {
     "elapsed": 12,
     "status": "ok",
     "timestamp": 1634789357991,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "O3yTHc5EVUqi",
    "outputId": "3d00b9d7-f686-4791-fe56-8ad23e8de469"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='CohortIndex', ylabel='count'>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.countplot(x=\"CohortIndex\", data=df_valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iGfd7BtbVUqk"
   },
   "source": [
    "## 잔존 빈도 구하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1634789358305,
     "user": {
      "displayName": "JINY ROH",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>CohortIndex</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InvoiceDateMin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>2010-12-01</th>\n",
       "      <td>885.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>286.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>321.0</td>\n",
       "      <td>352.0</td>\n",
       "      <td>321.0</td>\n",
       "      <td>309.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>331.0</td>\n",
       "      <td>445.0</td>\n",
       "      <td>235.0</td>\n",
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       "      <th>2011-01-01</th>\n",
       "      <td>417.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>49.0</td>\n",
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       "      <th>2011-02-01</th>\n",
       "      <td>380.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>26.0</td>\n",
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       "      <th>2011-03-01</th>\n",
       "      <td>452.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>300.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2011-05-01</th>\n",
       "      <td>284.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-06-01</th>\n",
       "      <td>242.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>188.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>21.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-08-01</th>\n",
       "      <td>169.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-09-01</th>\n",
       "      <td>299.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>34.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-10-01</th>\n",
       "      <td>358.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-11-01</th>\n",
       "      <td>323.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2011-12-01</th>\n",
       "      <td>41.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      ],
      "text/plain": [
       "CohortIndex        1      2      3      4      5      6      7      8      9   \\\n",
       "InvoiceDateMin                                                                  \n",
       "2010-12-01      885.0  324.0  286.0  340.0  321.0  352.0  321.0  309.0  313.0   \n",
       "2011-01-01      417.0   92.0  111.0   96.0  134.0  120.0  103.0  101.0  125.0   \n",
       "2011-02-01      380.0   71.0   71.0  108.0  103.0   94.0   96.0  106.0   94.0   \n",
       "2011-03-01      452.0   68.0  114.0   90.0  101.0   76.0  121.0  104.0  126.0   \n",
       "2011-04-01      300.0   64.0   61.0   63.0   59.0   68.0   65.0   78.0   22.0   \n",
       "2011-05-01      284.0   54.0   49.0   49.0   59.0   66.0   75.0   27.0    NaN   \n",
       "2011-06-01      242.0   42.0   38.0   64.0   56.0   81.0   23.0    NaN    NaN   \n",
       "2011-07-01      188.0   34.0   39.0   42.0   51.0   21.0    NaN    NaN    NaN   \n",
       "2011-08-01      169.0   35.0   42.0   41.0   21.0    NaN    NaN    NaN    NaN   \n",
       "2011-09-01      299.0   70.0   90.0   34.0    NaN    NaN    NaN    NaN    NaN   \n",
       "2011-10-01      358.0   86.0   41.0    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "2011-11-01      323.0   36.0    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "2011-12-01       41.0    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "\n",
       "CohortIndex        10     11     12     13  \n",
       "InvoiceDateMin                              \n",
       "2010-12-01      350.0  331.0  445.0  235.0  \n",
       "2011-01-01      136.0  152.0   49.0    NaN  \n",
       "2011-02-01      116.0   26.0    NaN    NaN  \n",
       "2011-03-01       39.0    NaN    NaN    NaN  \n",
       "2011-04-01        NaN    NaN    NaN    NaN  \n",
       "2011-05-01        NaN    NaN    NaN    NaN  \n",
       "2011-06-01        NaN    NaN    NaN    NaN  \n",
       "2011-07-01        NaN    NaN    NaN    NaN  \n",
       "2011-08-01        NaN    NaN    NaN    NaN  \n",
       "2011-09-01        NaN    NaN    NaN    NaN  \n",
       "2011-10-01        NaN    NaN    NaN    NaN  \n",
       "2011-11-01        NaN    NaN    NaN    NaN  \n",
       "2011-12-01        NaN    NaN    NaN    NaN  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Cohort_count = df_valid.groupby([\"InvoiceDateMin\", \"CohortIndex\"])['CustomerID'].nunique().unstack()\n",
    "Cohort_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 516
    },
    "executionInfo": {
     "elapsed": 1168,
     "status": "ok",
     "timestamp": 1634789359465,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
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     "user_tz": -540
    },
    "id": "u_HooWzvVUql",
    "outputId": "087b5350-76a3-4502-afa7-b7e8444dab91",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='CohortIndex', ylabel='InvoiceDateMin'>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "sns.heatmap(Cohort_count, annot=True, cmap=\"Blues\", fmt=\".0f\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 월별 신규 유입 고객 수 \n",
    "* Acqusition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceDateMin\n",
       "2010-12-01    885.0\n",
       "2011-01-01    417.0\n",
       "2011-02-01    380.0\n",
       "2011-03-01    452.0\n",
       "2011-04-01    300.0\n",
       "2011-05-01    284.0\n",
       "2011-06-01    242.0\n",
       "2011-07-01    188.0\n",
       "2011-08-01    169.0\n",
       "2011-09-01    299.0\n",
       "2011-10-01    358.0\n",
       "2011-11-01    323.0\n",
       "2011-12-01     41.0\n",
       "Name: 1, dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Cohort_count[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Acquision'}, xlabel='InvoiceDateMin'>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Cohort_count[1].plot.bar(figsize=(12, 4), rot=0, title='Acquision')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pBm8RhFuVUql"
   },
   "source": [
    "## 잔존율 구하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 10,
     "status": "ok",
     "timestamp": 1634789359466,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "tJPPTLnJVUqm",
    "outputId": "64bcbda8-8f14-4845-a4f5-c0e575d85a6b"
   },
   "outputs": [],
   "source": [
    "residual_rate = Cohort_count.div(Cohort_count[1], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 519
    },
    "executionInfo": {
     "elapsed": 630,
     "status": "ok",
     "timestamp": 1634789360088,
     "user": {
      "displayName": "JINY ROH",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi7VIzxUnr7MUJE9Bupl4bkwgEAsz4e1gsgrYIPZw=s64",
      "userId": "06348894780083418282"
     },
     "user_tz": -540
    },
    "id": "GNU1FBAhVUqm",
    "outputId": "90eb7c49-609c-4acf-b245-1298c8b6aff6"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "sns.heatmap(residual_rate, annot=True, cmap=\"Blues\", fmt=\".3f\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "Sales_sum = df_valid.groupby([\"InvoiceDateMin\", \"CohortIndex\"])['TotalPrice'].sum().unstack()\n",
    "Sales_sum = Sales_sum.div(Sales_sum[1], axis=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "sns.heatmap(Sales_sum, annot=True, cmap=\"Blues\", fmt=\".2f\")\n",
    "plt.show()"
   ]
  }
 ],
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  "colab": {
   "collapsed_sections": [],
   "name": "01-basic-eda.ipynb",
   "provenance": []
  },
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   "display_name": "Python 3.7.13 ('ML')",
   "language": "python",
   "name": "python3"
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  "language_info": {
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "toc": {
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   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "320px"
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   "toc_section_display": true,
   "toc_window_display": true
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   "types_to_exclude": [
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