Data_Preparation&RFM_analysis.ipynb

{"nbformat":4,"nbformat_minor":2,"metadata":{"colab":{"name":"e_commerce_RFM.ipynb","provenance":[],"collapsed_sections":[],"mount_file_id":"1DRfXvTB6F15OdKUmTFU0xxnlz0VlOM4r","authorship_tag":"ABX9TyM9QhGv6IqIpFKq/ElMD1dS"},"kernelspec":{"name":"python3","display_name":"Python 3.8.8 64-bit ('base': conda)"},"language_info":{"name":"python","version":"3.8.8","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"interpreter":{"hash":"c23d437dc897c5d39d3aca3d7626d7a2c2ecf3de474ef350afd872fd74ff197c"}},"cells":[{"cell_type":"markdown","source":["# UCI Online Retail II dataset - Exploratory Data Aanlysis & RFM Analysis"],"metadata":{"id":"cdcdweelXYMJ"}},{"cell_type":"markdown","source":["## Dataset Context\r\n","This Online Retail II data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers.\r\n","\r\n","<br>\r\n","\r\n","## Dataset Content\r\n","Attribute Information:\r\n","\r\n","- InvoiceNo: Invoice number. Nominal. A 6-digit integral number uniquely assigned to each transaction. If this code starts with the letter 'c', it indicates a cancellation.\r\n","- StockCode: Product (item) code. Nominal. A 5-digit integral number uniquely assigned to each distinct product.\r\n","Description: Product (item) name. Nominal.\r\n","- Quantity: The quantities of each product (item) per transaction. Numeric.\r\n","InvoiceDate: Invice date and time. Numeric. The day and time when a transaction was generated.\r\n","- UnitPrice: Unit price. Numeric. Product price per unit in sterling (Â£).\r\n","CustomerID: Customer number. Nominal. A 5-digit integral number uniquely assigned to each customer.\r\n","- Country: Country name. Nominal. The name of the country where a customer resides.\r\n","\r\n","<br>\r\n","\r\n","#### Reference\r\n","https://archive.ics.uci.edu/ml/datasets/Online+Retail+II"],"metadata":{"id":"85TnkmZTlwHf"}},{"cell_type":"code","execution_count":1,"source":["# !pip install wordcloud"],"outputs":[],"metadata":{"id":"DZTzY3PVmd_Q","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1628904356432,"user_tz":-480,"elapsed":3269,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"12ae93fc-cc9a-4f34-ab1a-3b2c9f648d84"}},{"cell_type":"markdown","source":["## EDA - Simple"],"metadata":{"id":"NTwJgPrgmqd3"}},{"cell_type":"code","execution_count":2,"source":["# import library\r\n","import pandas as pd\r\n","import numpy as np\r\n","import datetime\r\n","\r\n","# Data Viusalization\r\n","import matplotlib.pyplot as plt\r\n","import seaborn as sns\r\n","\r\n","# self-defined function for EDA\r\n","from eda_function import *"],"outputs":[],"metadata":{"id":"lENVzRgUIYPF","executionInfo":{"status":"ok","timestamp":1628904356836,"user_tz":-480,"elapsed":407,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":3,"source":["df = pd.read_csv(\"./data/online_retail_II.csv\")"],"outputs":[],"metadata":{"id":"0VoMKPMUlCgM","executionInfo":{"status":"ok","timestamp":1628904358411,"user_tz":-480,"elapsed":1577,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":4,"source":["df.rename(columns={\"Customer ID\":\"CustomerID\"},inplace=True)"],"outputs":[],"metadata":{"id":"bWS1Kx2JspRY","executionInfo":{"status":"ok","timestamp":1628904358414,"user_tz":-480,"elapsed":4,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":5,"source":["summary = df_summary(df)\r\n","summary"],"outputs":[{"output_type":"execute_result","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>dtype</th>\n","      <th>num_missing</th>\n","      <th>num_uniques</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Invoice</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>53628</td>\n","    </tr>\n","    <tr>\n","      <th>StockCode</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>5305</td>\n","    </tr>\n","    <tr>\n","      <th>Description</th>\n","      <td>object</td>\n","      <td>4382</td>\n","      <td>5698</td>\n","    </tr>\n","    <tr>\n","      <th>Quantity</th>\n","      <td>int64</td>\n","      <td>0</td>\n","      <td>1057</td>\n","    </tr>\n","    <tr>\n","      <th>InvoiceDate</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>47635</td>\n","    </tr>\n","    <tr>\n","      <th>Price</th>\n","      <td>float64</td>\n","      <td>0</td>\n","      <td>2807</td>\n","    </tr>\n","    <tr>\n","      <th>CustomerID</th>\n","      <td>float64</td>\n","      <td>243007</td>\n","      <td>5942</td>\n","    </tr>\n","    <tr>\n","      <th>Country</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>43</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["               dtype  num_missing  num_uniques\n","Invoice       object            0        53628\n","StockCode     object            0         5305\n","Description   object         4382         5698\n","Quantity       int64            0         1057\n","InvoiceDate   object            0        47635\n","Price        float64            0         2807\n","CustomerID   float64       243007         5942\n","Country       object            0           43"]},"metadata":{},"execution_count":5}],"metadata":{"id":"iWilOgIJmO-J","colab":{"base_uri":"https://localhost:8080/","height":297},"executionInfo":{"status":"ok","timestamp":1628904358829,"user_tz":-480,"elapsed":418,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"37d95bf1-f1bd-45ea-d1fe-1dab8e013cae"}},{"cell_type":"code","execution_count":6,"source":["print(\"Unique values of each columns: \")\r\n","for col in df.columns:\r\n","  print(f\"{col}: \\n {df[col].unique()}\\n\")\r\n"],"outputs":[{"output_type":"stream","name":"stdout","text":["Unique values of each columns: \n","Invoice: \n"," ['489434' '489435' '489436' ... '581585' '581586' '581587']\n","\n","StockCode: \n"," ['85048' '79323P' '79323W' ... '23609' '23617' '23843']\n","\n","Description: \n"," ['15CM CHRISTMAS GLASS BALL 20 LIGHTS' 'PINK CHERRY LIGHTS'\n"," ' WHITE CHERRY LIGHTS' ... 'mixed up'\n"," 'CREAM HANGING HEART T-LIGHT HOLDER' 'PAPER CRAFT , LITTLE BIRDIE']\n","\n","Quantity: \n"," [    12     48     24 ...    698  80995 -80995]\n","\n","InvoiceDate: \n"," ['2009-12-01 07:45:00' '2009-12-01 07:46:00' '2009-12-01 09:06:00' ...\n"," '2011-12-09 12:31:00' '2011-12-09 12:49:00' '2011-12-09 12:50:00']\n","\n","Price: \n"," [   6.95    6.75    2.1  ...  933.17 1714.17  224.69]\n","\n","CustomerID: \n"," [13085. 13078. 15362. ... 15520. 13298. 12713.]\n","\n","Country: \n"," ['United Kingdom' 'France' 'USA' 'Belgium' 'Australia' 'EIRE' 'Germany'\n"," 'Portugal' 'Japan' 'Denmark' 'Nigeria' 'Netherlands' 'Poland' 'Spain'\n"," 'Channel Islands' 'Italy' 'Cyprus' 'Greece' 'Norway' 'Austria' 'Sweden'\n"," 'United Arab Emirates' 'Finland' 'Switzerland' 'Unspecified' 'Malta'\n"," 'Bahrain' 'RSA' 'Bermuda' 'Hong Kong' 'Singapore' 'Thailand' 'Israel'\n"," 'Lithuania' 'West Indies' 'Lebanon' 'Korea' 'Brazil' 'Canada' 'Iceland'\n"," 'Saudi Arabia' 'Czech Republic' 'European Community']\n","\n"]}],"metadata":{"id":"jiT6QmtumPAD","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1628904359195,"user_tz":-480,"elapsed":370,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"145dcd41-7194-433a-d10d-f8c957351936"}},{"cell_type":"code","execution_count":7,"source":["# selling trend\r\n","plt.figure(figsize=(12,6))\r\n","sns.barplot(x=df.Description.value_counts().head(10), y=df.Description.value_counts().head(10).index)\r\n","plt.title(\"Top 10 products sold\")\r\n","plt.xlabel(\"quantity\")"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 0, 'quantity')"]},"metadata":{},"execution_count":7},{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 864x432 with 1 Axes>"]},"metadata":{}}],"metadata":{}},{"cell_type":"code","execution_count":8,"source":["# top 10 spent a lot customer\r\n","# selling trend\r\n","plt.figure(figsize=(12,6))\r\n","sns.barplot(x=df.CustomerID.value_counts().head(10).index, y=df.CustomerID.value_counts().head(10))\r\n","plt.title(\"Top 10 Customers\")\r\n","plt.xlabel(\"customer ID\")\r\n","plt.ylabel(\"Items Purchased\")"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Items Purchased')"]},"metadata":{},"execution_count":8},{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 864x432 with 1 Axes>"]},"metadata":{}}],"metadata":{}},{"cell_type":"code","execution_count":9,"source":["df['InvoiceDate'] = df['InvoiceDate'].astype(np.str).str.slice(0,10) \r\n","df['InvoiceDate'] = pd.to_datetime(df['InvoiceDate'])\r\n","\r\n","# or to_period()\r\n","df[\"InvoiceMonth\"] = df.InvoiceDate.dt.month\r\n","df[\"InvoiceYear\"] = df.InvoiceDate.dt.year\r\n","df[\"TotalPrice\"] = df[\"Price\"] * df[\"Quantity\"]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":10,"source":["plt.figure(figsize=(12,6))\r\n","df.groupby([\"InvoiceYear\",\"InvoiceMonth\"])[\"TotalPrice\"].sum().plot(kind=\"line\",label=\"sales\",grid=True)\r\n","plt.title(\"Sales amounts in Months\")\r\n","plt.ylabel(\"Sales amounts\")\r\n","plt.xlabel(\"Month\")"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 0, 'Month')"]},"metadata":{},"execution_count":10},{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 864x432 with 1 Axes>"]},"metadata":{}}],"metadata":{}},{"cell_type":"markdown","source":["## Data Cleaning\n","**remove all N/A and duplicated data**\n"],"metadata":{"id":"KLg0UI83m-Iv"}},{"cell_type":"code","execution_count":11,"source":["df_new = df.copy()\r\n","df_new.dropna(inplace=True)"],"outputs":[],"metadata":{"id":"ImMuRvRClO2R","executionInfo":{"status":"ok","timestamp":1628904359711,"user_tz":-480,"elapsed":518,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":12,"source":["df_new.duplicated().sum()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["26481"]},"metadata":{},"execution_count":12}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZpDgpgbfmY-J","executionInfo":{"status":"ok","timestamp":1628904360125,"user_tz":-480,"elapsed":415,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"eb8684af-d739-454d-c24e-dde076a1d3d0"}},{"cell_type":"code","execution_count":13,"source":["df_new.drop_duplicates(inplace=True)\r\n","df_new.duplicated().sum()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["0"]},"metadata":{},"execution_count":13}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"K_cqIjMCmyeI","executionInfo":{"status":"ok","timestamp":1628904361280,"user_tz":-480,"elapsed":1156,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"18429e3c-509e-4cc9-b7fa-517e33d0b332"}},{"cell_type":"markdown","source":["Our dataset after removing na columns and duplicated data:"],"metadata":{"id":"dmvIGpAUnmpM"}},{"cell_type":"code","execution_count":14,"source":["df_new.shape"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["(797883, 11)"]},"metadata":{},"execution_count":14}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ughEbBDiois4","executionInfo":{"status":"ok","timestamp":1628904361280,"user_tz":-480,"elapsed":3,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"bc1d01aa-982f-4223-ee81-e04f52d159f0"}},{"cell_type":"code","execution_count":15,"source":["summary_new = df_summary(df_new)\r\n","summary_new"],"outputs":[{"output_type":"execute_result","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>dtype</th>\n","      <th>num_missing</th>\n","      <th>num_uniques</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Invoice</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>44876</td>\n","    </tr>\n","    <tr>\n","      <th>StockCode</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>4646</td>\n","    </tr>\n","    <tr>\n","      <th>Description</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>5299</td>\n","    </tr>\n","    <tr>\n","      <th>Quantity</th>\n","      <td>int64</td>\n","      <td>0</td>\n","      <td>643</td>\n","    </tr>\n","    <tr>\n","      <th>InvoiceDate</th>\n","      <td>datetime64[ns]</td>\n","      <td>0</td>\n","      <td>604</td>\n","    </tr>\n","    <tr>\n","      <th>Price</th>\n","      <td>float64</td>\n","      <td>0</td>\n","      <td>1022</td>\n","    </tr>\n","    <tr>\n","      <th>CustomerID</th>\n","      <td>float64</td>\n","      <td>0</td>\n","      <td>5942</td>\n","    </tr>\n","    <tr>\n","      <th>Country</th>\n","      <td>object</td>\n","      <td>0</td>\n","      <td>41</td>\n","    </tr>\n","    <tr>\n","      <th>InvoiceMonth</th>\n","      <td>int64</td>\n","      <td>0</td>\n","      <td>12</td>\n","    </tr>\n","    <tr>\n","      <th>InvoiceYear</th>\n","      <td>int64</td>\n","      <td>0</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>TotalPrice</th>\n","      <td>float64</td>\n","      <td>0</td>\n","      <td>5625</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                       dtype  num_missing  num_uniques\n","Invoice               object            0        44876\n","StockCode             object            0         4646\n","Description           object            0         5299\n","Quantity               int64            0          643\n","InvoiceDate   datetime64[ns]            0          604\n","Price                float64            0         1022\n","CustomerID           float64            0         5942\n","Country               object            0           41\n","InvoiceMonth           int64            0           12\n","InvoiceYear            int64            0            3\n","TotalPrice           float64            0         5625"]},"metadata":{},"execution_count":15}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":297},"id":"DdMLDyezlO0O","executionInfo":{"status":"ok","timestamp":1628904361612,"user_tz":-480,"elapsed":334,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"aacdc998-9ea1-4c71-e8ec-df958b6427f4"}},{"cell_type":"code","execution_count":16,"source":["print(\"Unique values of each columns: \")\r\n","for col in df.columns:\r\n","  print(f\"{col}: \\n {df[col].unique()}\\n\")\r\n"],"outputs":[{"output_type":"stream","name":"stdout","text":["Unique values of each columns: \n","Invoice: \n"," ['489434' '489435' '489436' ... '581585' '581586' '581587']\n","\n","StockCode: \n"," ['85048' '79323P' '79323W' ... '23609' '23617' '23843']\n","\n","Description: \n"," ['15CM CHRISTMAS GLASS BALL 20 LIGHTS' 'PINK CHERRY LIGHTS'\n"," ' WHITE CHERRY LIGHTS' ... 'mixed up'\n"," 'CREAM HANGING HEART T-LIGHT HOLDER' 'PAPER CRAFT , LITTLE BIRDIE']\n","\n","Quantity: \n"," [    12     48     24 ...    698  80995 -80995]\n","\n","InvoiceDate: \n"," ['2009-12-01T00:00:00.000000000' '2009-12-02T00:00:00.000000000'\n"," '2009-12-03T00:00:00.000000000' '2009-12-04T00:00:00.000000000'\n"," '2009-12-05T00:00:00.000000000' '2009-12-06T00:00:00.000000000'\n"," '2009-12-07T00:00:00.000000000' '2009-12-08T00:00:00.000000000'\n"," '2009-12-09T00:00:00.000000000' '2009-12-10T00:00:00.000000000'\n"," '2009-12-11T00:00:00.000000000' '2009-12-13T00:00:00.000000000'\n"," '2009-12-14T00:00:00.000000000' '2009-12-15T00:00:00.000000000'\n"," '2009-12-16T00:00:00.000000000' '2009-12-17T00:00:00.000000000'\n"," '2009-12-18T00:00:00.000000000' '2009-12-20T00:00:00.000000000'\n"," '2009-12-21T00:00:00.000000000' '2009-12-22T00:00:00.000000000'\n"," '2009-12-23T00:00:00.000000000' '2010-01-04T00:00:00.000000000'\n"," '2010-01-05T00:00:00.000000000' '2010-01-06T00:00:00.000000000'\n"," '2010-01-07T00:00:00.000000000' '2010-01-08T00:00:00.000000000'\n"," '2010-01-10T00:00:00.000000000' '2010-01-11T00:00:00.000000000'\n"," '2010-01-12T00:00:00.000000000' '2010-01-13T00:00:00.000000000'\n"," '2010-01-14T00:00:00.000000000' '2010-01-15T00:00:00.000000000'\n"," '2010-01-17T00:00:00.000000000' '2010-01-18T00:00:00.000000000'\n"," '2010-01-19T00:00:00.000000000' '2010-01-20T00:00:00.000000000'\n"," '2010-01-21T00:00:00.000000000' '2010-01-22T00:00:00.000000000'\n"," '2010-01-24T00:00:00.000000000' '2010-01-25T00:00:00.000000000'\n"," '2010-01-26T00:00:00.000000000' '2010-01-27T00:00:00.000000000'\n"," '2010-01-28T00:00:00.000000000' '2010-01-29T00:00:00.000000000'\n"," '2010-01-31T00:00:00.000000000' '2010-02-01T00:00:00.000000000'\n"," '2010-02-02T00:00:00.000000000' '2010-02-03T00:00:00.000000000'\n"," '2010-02-04T00:00:00.000000000' '2010-02-05T00:00:00.000000000'\n"," '2010-02-07T00:00:00.000000000' '2010-02-08T00:00:00.000000000'\n"," '2010-02-09T00:00:00.000000000' '2010-02-10T00:00:00.000000000'\n"," '2010-02-11T00:00:00.000000000' '2010-02-12T00:00:00.000000000'\n"," '2010-02-14T00:00:00.000000000' '2010-02-15T00:00:00.000000000'\n"," '2010-02-16T00:00:00.000000000' '2010-02-17T00:00:00.000000000'\n"," '2010-02-18T00:00:00.000000000' '2010-02-19T00:00:00.000000000'\n"," '2010-02-21T00:00:00.000000000' '2010-02-22T00:00:00.000000000'\n"," '2010-02-23T00:00:00.000000000' '2010-02-24T00:00:00.000000000'\n"," '2010-02-25T00:00:00.000000000' '2010-02-26T00:00:00.000000000'\n"," '2010-02-28T00:00:00.000000000' '2010-03-01T00:00:00.000000000'\n"," '2010-03-02T00:00:00.000000000' '2010-03-03T00:00:00.000000000'\n"," '2010-03-04T00:00:00.000000000' '2010-03-05T00:00:00.000000000'\n"," '2010-03-07T00:00:00.000000000' '2010-03-08T00:00:00.000000000'\n"," '2010-03-09T00:00:00.000000000' '2010-03-10T00:00:00.000000000'\n"," '2010-03-11T00:00:00.000000000' '2010-03-12T00:00:00.000000000'\n"," '2010-03-14T00:00:00.000000000' '2010-03-15T00:00:00.000000000'\n"," '2010-03-16T00:00:00.000000000' '2010-03-17T00:00:00.000000000'\n"," '2010-03-18T00:00:00.000000000' '2010-03-19T00:00:00.000000000'\n"," '2010-03-21T00:00:00.000000000' '2010-03-22T00:00:00.000000000'\n"," '2010-03-23T00:00:00.000000000' '2010-03-24T00:00:00.000000000'\n"," '2010-03-25T00:00:00.000000000' '2010-03-26T00:00:00.000000000'\n"," '2010-03-28T00:00:00.000000000' '2010-03-29T00:00:00.000000000'\n"," '2010-03-30T00:00:00.000000000' '2010-03-31T00:00:00.000000000'\n"," '2010-04-01T00:00:00.000000000' '2010-04-06T00:00:00.000000000'\n"," '2010-04-07T00:00:00.000000000' '2010-04-08T00:00:00.000000000'\n"," '2010-04-09T00:00:00.000000000' '2010-04-11T00:00:00.000000000'\n"," '2010-04-12T00:00:00.000000000' '2010-04-13T00:00:00.000000000'\n"," '2010-04-14T00:00:00.000000000' '2010-04-15T00:00:00.000000000'\n"," '2010-04-16T00:00:00.000000000' '2010-04-18T00:00:00.000000000'\n"," '2010-04-19T00:00:00.000000000' '2010-04-20T00:00:00.000000000'\n"," '2010-04-21T00:00:00.000000000' '2010-04-22T00:00:00.000000000'\n"," '2010-04-23T00:00:00.000000000' '2010-04-25T00:00:00.000000000'\n"," '2010-04-26T00:00:00.000000000' '2010-04-27T00:00:00.000000000'\n"," '2010-04-28T00:00:00.000000000' '2010-04-29T00:00:00.000000000'\n"," '2010-04-30T00:00:00.000000000' '2010-05-02T00:00:00.000000000'\n"," '2010-05-04T00:00:00.000000000' '2010-05-05T00:00:00.000000000'\n"," '2010-05-06T00:00:00.000000000' '2010-05-07T00:00:00.000000000'\n"," '2010-05-09T00:00:00.000000000' '2010-05-10T00:00:00.000000000'\n"," '2010-05-11T00:00:00.000000000' '2010-05-12T00:00:00.000000000'\n"," '2010-05-13T00:00:00.000000000' '2010-05-14T00:00:00.000000000'\n"," '2010-05-16T00:00:00.000000000' '2010-05-17T00:00:00.000000000'\n"," '2010-05-18T00:00:00.000000000' '2010-05-19T00:00:00.000000000'\n"," '2010-05-20T00:00:00.000000000' '2010-05-21T00:00:00.000000000'\n"," '2010-05-23T00:00:00.000000000' '2010-05-24T00:00:00.000000000'\n"," '2010-05-25T00:00:00.000000000' '2010-05-26T00:00:00.000000000'\n"," '2010-05-27T00:00:00.000000000' '2010-05-28T00:00:00.000000000'\n"," '2010-05-30T00:00:00.000000000' '2010-06-01T00:00:00.000000000'\n"," '2010-06-02T00:00:00.000000000' '2010-06-03T00:00:00.000000000'\n"," '2010-06-04T00:00:00.000000000' '2010-06-06T00:00:00.000000000'\n"," '2010-06-07T00:00:00.000000000' '2010-06-08T00:00:00.000000000'\n"," '2010-06-09T00:00:00.000000000' '2010-06-10T00:00:00.000000000'\n"," '2010-06-11T00:00:00.000000000' '2010-06-13T00:00:00.000000000'\n"," '2010-06-14T00:00:00.000000000' '2010-06-15T00:00:00.000000000'\n"," '2010-06-16T00:00:00.000000000' '2010-06-17T00:00:00.000000000'\n"," '2010-06-18T00:00:00.000000000' '2010-06-20T00:00:00.000000000'\n"," '2010-06-21T00:00:00.000000000' '2010-06-22T00:00:00.000000000'\n"," '2010-06-23T00:00:00.000000000' '2010-06-24T00:00:00.000000000'\n"," '2010-06-25T00:00:00.000000000' '2010-06-27T00:00:00.000000000'\n"," '2010-06-28T00:00:00.000000000' '2010-06-29T00:00:00.000000000'\n"," '2010-06-30T00:00:00.000000000' '2010-07-01T00:00:00.000000000'\n"," '2010-07-02T00:00:00.000000000' '2010-07-04T00:00:00.000000000'\n"," '2010-07-05T00:00:00.000000000' '2010-07-06T00:00:00.000000000'\n"," '2010-07-07T00:00:00.000000000' '2010-07-08T00:00:00.000000000'\n"," '2010-07-09T00:00:00.000000000' '2010-07-11T00:00:00.000000000'\n"," '2010-07-12T00:00:00.000000000' '2010-07-13T00:00:00.000000000'\n"," '2010-07-14T00:00:00.000000000' '2010-07-15T00:00:00.000000000'\n"," '2010-07-16T00:00:00.000000000' '2010-07-18T00:00:00.000000000'\n"," '2010-07-19T00:00:00.000000000' '2010-07-20T00:00:00.000000000'\n"," '2010-07-21T00:00:00.000000000' '2010-07-22T00:00:00.000000000'\n"," '2010-07-23T00:00:00.000000000' '2010-07-25T00:00:00.000000000'\n"," '2010-07-26T00:00:00.000000000' '2010-07-27T00:00:00.000000000'\n"," '2010-07-28T00:00:00.000000000' '2010-07-29T00:00:00.000000000'\n"," '2010-07-30T00:00:00.000000000' '2010-08-01T00:00:00.000000000'\n"," '2010-08-02T00:00:00.000000000' '2010-08-03T00:00:00.000000000'\n"," '2010-08-04T00:00:00.000000000' '2010-08-05T00:00:00.000000000'\n"," '2010-08-06T00:00:00.000000000' '2010-08-08T00:00:00.000000000'\n"," '2010-08-09T00:00:00.000000000' '2010-08-10T00:00:00.000000000'\n"," '2010-08-11T00:00:00.000000000' '2010-08-12T00:00:00.000000000'\n"," '2010-08-13T00:00:00.000000000' '2010-08-15T00:00:00.000000000'\n"," '2010-08-16T00:00:00.000000000' '2010-08-17T00:00:00.000000000'\n"," '2010-08-18T00:00:00.000000000' '2010-08-19T00:00:00.000000000'\n"," '2010-08-20T00:00:00.000000000' '2010-08-22T00:00:00.000000000'\n"," '2010-08-23T00:00:00.000000000' '2010-08-24T00:00:00.000000000'\n"," '2010-08-25T00:00:00.000000000' '2010-08-26T00:00:00.000000000'\n"," '2010-08-27T00:00:00.000000000' '2010-08-29T00:00:00.000000000'\n"," '2010-08-31T00:00:00.000000000' '2010-09-01T00:00:00.000000000'\n"," '2010-09-02T00:00:00.000000000' '2010-09-03T00:00:00.000000000'\n"," '2010-09-05T00:00:00.000000000' '2010-09-06T00:00:00.000000000'\n"," '2010-09-07T00:00:00.000000000' '2010-09-08T00:00:00.000000000'\n"," '2010-09-09T00:00:00.000000000' '2010-09-10T00:00:00.000000000'\n"," '2010-09-12T00:00:00.000000000' '2010-09-13T00:00:00.000000000'\n"," '2010-09-14T00:00:00.000000000' '2010-09-15T00:00:00.000000000'\n"," '2010-09-16T00:00:00.000000000' '2010-09-17T00:00:00.000000000'\n"," '2010-09-19T00:00:00.000000000' '2010-09-20T00:00:00.000000000'\n"," '2010-09-21T00:00:00.000000000' '2010-09-22T00:00:00.000000000'\n"," '2010-09-23T00:00:00.000000000' '2010-09-24T00:00:00.000000000'\n"," '2010-09-26T00:00:00.000000000' '2010-09-27T00:00:00.000000000'\n"," '2010-09-28T00:00:00.000000000' '2010-09-29T00:00:00.000000000'\n"," '2010-09-30T00:00:00.000000000' '2010-10-01T00:00:00.000000000'\n"," '2010-10-03T00:00:00.000000000' '2010-10-04T00:00:00.000000000'\n"," '2010-10-05T00:00:00.000000000' '2010-10-06T00:00:00.000000000'\n"," '2010-10-07T00:00:00.000000000' '2010-10-08T00:00:00.000000000'\n"," '2010-10-10T00:00:00.000000000' '2010-10-11T00:00:00.000000000'\n"," '2010-10-12T00:00:00.000000000' '2010-10-13T00:00:00.000000000'\n"," '2010-10-14T00:00:00.000000000' '2010-10-15T00:00:00.000000000'\n"," '2010-10-17T00:00:00.000000000' '2010-10-18T00:00:00.000000000'\n"," '2010-10-19T00:00:00.000000000' '2010-10-20T00:00:00.000000000'\n"," '2010-10-21T00:00:00.000000000' '2010-10-22T00:00:00.000000000'\n"," '2010-10-24T00:00:00.000000000' '2010-10-25T00:00:00.000000000'\n"," '2010-10-26T00:00:00.000000000' '2010-10-27T00:00:00.000000000'\n"," '2010-10-28T00:00:00.000000000' '2010-10-29T00:00:00.000000000'\n"," '2010-10-31T00:00:00.000000000' '2010-11-01T00:00:00.000000000'\n"," '2010-11-02T00:00:00.000000000' 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'2011-10-14T00:00:00.000000000'\n"," '2011-10-16T00:00:00.000000000' '2011-10-17T00:00:00.000000000'\n"," '2011-10-18T00:00:00.000000000' '2011-10-19T00:00:00.000000000'\n"," '2011-10-20T00:00:00.000000000' '2011-10-21T00:00:00.000000000'\n"," '2011-10-23T00:00:00.000000000' '2011-10-24T00:00:00.000000000'\n"," '2011-10-25T00:00:00.000000000' '2011-10-26T00:00:00.000000000'\n"," '2011-10-27T00:00:00.000000000' '2011-10-28T00:00:00.000000000'\n"," '2011-10-30T00:00:00.000000000' '2011-10-31T00:00:00.000000000'\n"," '2011-11-01T00:00:00.000000000' '2011-11-02T00:00:00.000000000'\n"," '2011-11-03T00:00:00.000000000' '2011-11-04T00:00:00.000000000'\n"," '2011-11-06T00:00:00.000000000' '2011-11-07T00:00:00.000000000'\n"," '2011-11-08T00:00:00.000000000' '2011-11-09T00:00:00.000000000'\n"," '2011-11-10T00:00:00.000000000' '2011-11-11T00:00:00.000000000'\n"," '2011-11-13T00:00:00.000000000' '2011-11-14T00:00:00.000000000'\n"," '2011-11-15T00:00:00.000000000' '2011-11-16T00:00:00.000000000'\n"," '2011-11-17T00:00:00.000000000' '2011-11-18T00:00:00.000000000'\n"," '2011-11-20T00:00:00.000000000' '2011-11-21T00:00:00.000000000'\n"," '2011-11-22T00:00:00.000000000' '2011-11-23T00:00:00.000000000'\n"," '2011-11-24T00:00:00.000000000' '2011-11-25T00:00:00.000000000'\n"," '2011-11-27T00:00:00.000000000' '2011-11-28T00:00:00.000000000'\n"," '2011-11-29T00:00:00.000000000' '2011-11-30T00:00:00.000000000'\n"," '2011-12-01T00:00:00.000000000' '2011-12-02T00:00:00.000000000'\n"," '2011-12-04T00:00:00.000000000' '2011-12-05T00:00:00.000000000'\n"," '2011-12-06T00:00:00.000000000' '2011-12-07T00:00:00.000000000'\n"," '2011-12-08T00:00:00.000000000' '2011-12-09T00:00:00.000000000']\n","\n","Price: \n"," [   6.95    6.75    2.1  ...  933.17 1714.17  224.69]\n","\n","CustomerID: \n"," [13085. 13078. 15362. ... 15520. 13298. 12713.]\n","\n","Country: \n"," ['United Kingdom' 'France' 'USA' 'Belgium' 'Australia' 'EIRE' 'Germany'\n"," 'Portugal' 'Japan' 'Denmark' 'Nigeria' 'Netherlands' 'Poland' 'Spain'\n"," 'Channel Islands' 'Italy' 'Cyprus' 'Greece' 'Norway' 'Austria' 'Sweden'\n"," 'United Arab Emirates' 'Finland' 'Switzerland' 'Unspecified' 'Malta'\n"," 'Bahrain' 'RSA' 'Bermuda' 'Hong Kong' 'Singapore' 'Thailand' 'Israel'\n"," 'Lithuania' 'West Indies' 'Lebanon' 'Korea' 'Brazil' 'Canada' 'Iceland'\n"," 'Saudi Arabia' 'Czech Republic' 'European Community']\n","\n","InvoiceMonth: \n"," [12  1  2  3  4  5  6  7  8  9 10 11]\n","\n","InvoiceYear: \n"," [2009 2010 2011]\n","\n","TotalPrice: \n"," [ 83.4   81.   100.8  ...  25.08 469.44  66.36]\n","\n"]}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PoyQtrcAlOsA","executionInfo":{"status":"ok","timestamp":1628904361850,"user_tz":-480,"elapsed":241,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"463f7db8-68a2-40b6-c8bd-3a5cb2686bbe"}},{"cell_type":"code","execution_count":17,"source":["df_new.Country.value_counts().head(10)"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["United Kingdom    716113\n","Germany            17339\n","EIRE               16014\n","France             13897\n","Netherlands         5137\n","Spain               3754\n","Belgium             3110\n","Switzerland         3058\n","Portugal            2414\n","Australia           1890\n","Name: Country, dtype: int64"]},"metadata":{},"execution_count":17}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"a2xUjrFMnarn","executionInfo":{"status":"ok","timestamp":1628904362096,"user_tz":-480,"elapsed":248,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"e36f01ae-6365-411d-fdf9-bfee3f1bd42b"}},{"cell_type":"markdown","source":["Different country may have different purchasing preference due to the cultures, ecnonomy, in order to avoid being affected by these factors, we have to focus on a single country here, and since most of the data here are from UK, our customer anaylsis will focus on the UK market first."],"metadata":{"id":"xF_8RIhxnwBU"}},{"cell_type":"code","execution_count":18,"source":["df_new[df_new.Quantity < 0].head()"],"outputs":[{"output_type":"execute_result","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>Invoice</th>\n","      <th>StockCode</th>\n","      <th>Description</th>\n","      <th>Quantity</th>\n","      <th>InvoiceDate</th>\n","      <th>Price</th>\n","      <th>CustomerID</th>\n","      <th>Country</th>\n","      <th>InvoiceMonth</th>\n","      <th>InvoiceYear</th>\n","      <th>TotalPrice</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>178</th>\n","      <td>C489449</td>\n","      <td>22087</td>\n","      <td>PAPER BUNTING WHITE LACE</td>\n","      <td>-12</td>\n","      <td>2009-12-01</td>\n","      <td>2.95</td>\n","      <td>16321.0</td>\n","      <td>Australia</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>-35.4</td>\n","    </tr>\n","    <tr>\n","      <th>179</th>\n","      <td>C489449</td>\n","      <td>85206A</td>\n","      <td>CREAM FELT EASTER EGG BASKET</td>\n","      <td>-6</td>\n","      <td>2009-12-01</td>\n","      <td>1.65</td>\n","      <td>16321.0</td>\n","      <td>Australia</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>-9.9</td>\n","    </tr>\n","    <tr>\n","      <th>180</th>\n","      <td>C489449</td>\n","      <td>21895</td>\n","      <td>POTTING SHED SOW 'N' GROW SET</td>\n","      <td>-4</td>\n","      <td>2009-12-01</td>\n","      <td>4.25</td>\n","      <td>16321.0</td>\n","      <td>Australia</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>-17.0</td>\n","    </tr>\n","    <tr>\n","      <th>181</th>\n","      <td>C489449</td>\n","      <td>21896</td>\n","      <td>POTTING SHED TWINE</td>\n","      <td>-6</td>\n","      <td>2009-12-01</td>\n","      <td>2.10</td>\n","      <td>16321.0</td>\n","      <td>Australia</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>-12.6</td>\n","    </tr>\n","    <tr>\n","      <th>182</th>\n","      <td>C489449</td>\n","      <td>22083</td>\n","      <td>PAPER CHAIN KIT RETRO SPOT</td>\n","      <td>-12</td>\n","      <td>2009-12-01</td>\n","      <td>2.95</td>\n","      <td>16321.0</td>\n","      <td>Australia</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>-35.4</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["     Invoice StockCode                    Description  Quantity InvoiceDate  \\\n","178  C489449     22087       PAPER BUNTING WHITE LACE       -12  2009-12-01   \n","179  C489449    85206A   CREAM FELT EASTER EGG BASKET        -6  2009-12-01   \n","180  C489449     21895  POTTING SHED SOW 'N' GROW SET        -4  2009-12-01   \n","181  C489449     21896             POTTING SHED TWINE        -6  2009-12-01   \n","182  C489449     22083     PAPER CHAIN KIT RETRO SPOT       -12  2009-12-01   \n","\n","     Price  CustomerID    Country  InvoiceMonth  InvoiceYear  TotalPrice  \n","178   2.95     16321.0  Australia            12         2009       -35.4  \n","179   1.65     16321.0  Australia            12         2009        -9.9  \n","180   4.25     16321.0  Australia            12         2009       -17.0  \n","181   2.10     16321.0  Australia            12         2009       -12.6  \n","182   2.95     16321.0  Australia            12         2009       -35.4  "]},"metadata":{},"execution_count":18}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"id":"T5QYZCptpQH4","executionInfo":{"status":"ok","timestamp":1628904362097,"user_tz":-480,"elapsed":6,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"01563061-6d48-4de9-c65e-a1a9069afc13"}},{"cell_type":"markdown","source":["The negative in quantity refers to cancellation, the Invoice code of these transition are all starts with the letter \"c\" which prove the cancellation."],"metadata":{"id":"vDK7Xg1DpW1u"}},{"cell_type":"code","execution_count":19,"source":["df_new = df_new[(df_new.Quantity > 0) & (df_new.Price > 0)]"],"outputs":[],"metadata":{"id":"ucNoiU74sK9B","executionInfo":{"status":"ok","timestamp":1628904362097,"user_tz":-480,"elapsed":4,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":20,"source":["df_new = df_new[(df_new.Country == \"United Kingdom\")]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":21,"source":["df_new"],"outputs":[{"output_type":"execute_result","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>Invoice</th>\n","      <th>StockCode</th>\n","      <th>Description</th>\n","      <th>Quantity</th>\n","      <th>InvoiceDate</th>\n","      <th>Price</th>\n","      <th>CustomerID</th>\n","      <th>Country</th>\n","      <th>InvoiceMonth</th>\n","      <th>InvoiceYear</th>\n","      <th>TotalPrice</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>489434</td>\n","      <td>85048</td>\n","      <td>15CM CHRISTMAS GLASS BALL 20 LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.95</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>83.4</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>489434</td>\n","      <td>79323P</td>\n","      <td>PINK CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>81.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>489434</td>\n","      <td>79323W</td>\n","      <td>WHITE CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>81.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>489434</td>\n","      <td>22041</td>\n","      <td>RECORD FRAME 7\" SINGLE SIZE</td>\n","      <td>48</td>\n","      <td>2009-12-01</td>\n","      <td>2.10</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>100.8</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>489434</td>\n","      <td>21232</td>\n","      <td>STRAWBERRY CERAMIC TRINKET BOX</td>\n","      <td>24</td>\n","      <td>2009-12-01</td>\n","      <td>1.25</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>30.0</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>1067350</th>\n","      <td>581585</td>\n","      <td>22466</td>\n","      <td>FAIRY TALE COTTAGE NIGHT LIGHT</td>\n","      <td>12</td>\n","      <td>2011-12-09</td>\n","      <td>1.95</td>\n","      <td>15804.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>23.4</td>\n","    </tr>\n","    <tr>\n","      <th>1067351</th>\n","      <td>581586</td>\n","      <td>22061</td>\n","      <td>LARGE CAKE STAND  HANGING STRAWBERY</td>\n","      <td>8</td>\n","      <td>2011-12-09</td>\n","      <td>2.95</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>23.6</td>\n","    </tr>\n","    <tr>\n","      <th>1067352</th>\n","      <td>581586</td>\n","      <td>23275</td>\n","      <td>SET OF 3 HANGING OWLS OLLIE BEAK</td>\n","      <td>24</td>\n","      <td>2011-12-09</td>\n","      <td>1.25</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>30.0</td>\n","    </tr>\n","    <tr>\n","      <th>1067353</th>\n","      <td>581586</td>\n","      <td>21217</td>\n","      <td>RED RETROSPOT ROUND CAKE TINS</td>\n","      <td>24</td>\n","      <td>2011-12-09</td>\n","      <td>8.95</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>214.8</td>\n","    </tr>\n","    <tr>\n","      <th>1067354</th>\n","      <td>581586</td>\n","      <td>20685</td>\n","      <td>DOORMAT RED RETROSPOT</td>\n","      <td>10</td>\n","      <td>2011-12-09</td>\n","      <td>7.08</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>70.8</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>700386 rows × 11 columns</p>\n","</div>"],"text/plain":["        Invoice StockCode                          Description  Quantity  \\\n","0        489434     85048  15CM CHRISTMAS GLASS BALL 20 LIGHTS        12   \n","1        489434    79323P                   PINK CHERRY LIGHTS        12   \n","2        489434    79323W                  WHITE CHERRY LIGHTS        12   \n","3        489434     22041         RECORD FRAME 7\" SINGLE SIZE         48   \n","4        489434     21232       STRAWBERRY CERAMIC TRINKET BOX        24   \n","...         ...       ...                                  ...       ...   \n","1067350  581585     22466       FAIRY TALE COTTAGE NIGHT LIGHT        12   \n","1067351  581586     22061  LARGE CAKE STAND  HANGING STRAWBERY         8   \n","1067352  581586     23275     SET OF 3 HANGING OWLS OLLIE BEAK        24   \n","1067353  581586     21217        RED RETROSPOT ROUND CAKE TINS        24   \n","1067354  581586     20685                DOORMAT RED RETROSPOT        10   \n","\n","        InvoiceDate  Price  CustomerID         Country  InvoiceMonth  \\\n","0        2009-12-01   6.95     13085.0  United Kingdom            12   \n","1        2009-12-01   6.75     13085.0  United Kingdom            12   \n","2        2009-12-01   6.75     13085.0  United Kingdom            12   \n","3        2009-12-01   2.10     13085.0  United Kingdom            12   \n","4        2009-12-01   1.25     13085.0  United Kingdom            12   \n","...             ...    ...         ...             ...           ...   \n","1067350  2011-12-09   1.95     15804.0  United Kingdom            12   \n","1067351  2011-12-09   2.95     13113.0  United Kingdom            12   \n","1067352  2011-12-09   1.25     13113.0  United Kingdom            12   \n","1067353  2011-12-09   8.95     13113.0  United Kingdom            12   \n","1067354  2011-12-09   7.08     13113.0  United Kingdom            12   \n","\n","         InvoiceYear  TotalPrice  \n","0               2009        83.4  \n","1               2009        81.0  \n","2               2009        81.0  \n","3               2009       100.8  \n","4               2009        30.0  \n","...              ...         ...  \n","1067350         2011        23.4  \n","1067351         2011        23.6  \n","1067352         2011        30.0  \n","1067353         2011       214.8  \n","1067354         2011        70.8  \n","\n","[700386 rows x 11 columns]"]},"metadata":{},"execution_count":21}],"metadata":{}},{"cell_type":"code","execution_count":22,"source":["df_new.InvoiceDate = pd.to_datetime(df_new.InvoiceDate, format = '%Y-%m-%d')\r\n","df_new.InvoiceDate = df_new.InvoiceDate.dt.date"],"outputs":[],"metadata":{"id":"L-FYUTMJrquG","executionInfo":{"status":"ok","timestamp":1628904362465,"user_tz":-480,"elapsed":372,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":23,"source":["df_new[\"TotalAmount\"] = df_new.Price * df_new.Quantity"],"outputs":[],"metadata":{"id":"yT62fHO3lOxp","executionInfo":{"status":"ok","timestamp":1628904362829,"user_tz":-480,"elapsed":365,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":24,"source":["df_new"],"outputs":[{"output_type":"execute_result","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>Invoice</th>\n","      <th>StockCode</th>\n","      <th>Description</th>\n","      <th>Quantity</th>\n","      <th>InvoiceDate</th>\n","      <th>Price</th>\n","      <th>CustomerID</th>\n","      <th>Country</th>\n","      <th>InvoiceMonth</th>\n","      <th>InvoiceYear</th>\n","      <th>TotalPrice</th>\n","      <th>TotalAmount</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>489434</td>\n","      <td>85048</td>\n","      <td>15CM CHRISTMAS GLASS BALL 20 LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.95</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>83.4</td>\n","      <td>83.4</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>489434</td>\n","      <td>79323P</td>\n","      <td>PINK CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>81.0</td>\n","      <td>81.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>489434</td>\n","      <td>79323W</td>\n","      <td>WHITE CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>81.0</td>\n","      <td>81.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>489434</td>\n","      <td>22041</td>\n","      <td>RECORD FRAME 7\" SINGLE SIZE</td>\n","      <td>48</td>\n","      <td>2009-12-01</td>\n","      <td>2.10</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>100.8</td>\n","      <td>100.8</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>489434</td>\n","      <td>21232</td>\n","      <td>STRAWBERRY CERAMIC TRINKET BOX</td>\n","      <td>24</td>\n","      <td>2009-12-01</td>\n","      <td>1.25</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>30.0</td>\n","      <td>30.0</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>1067350</th>\n","      <td>581585</td>\n","      <td>22466</td>\n","      <td>FAIRY TALE COTTAGE NIGHT LIGHT</td>\n","      <td>12</td>\n","      <td>2011-12-09</td>\n","      <td>1.95</td>\n","      <td>15804.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>23.4</td>\n","      <td>23.4</td>\n","    </tr>\n","    <tr>\n","      <th>1067351</th>\n","      <td>581586</td>\n","      <td>22061</td>\n","      <td>LARGE CAKE STAND  HANGING STRAWBERY</td>\n","      <td>8</td>\n","      <td>2011-12-09</td>\n","      <td>2.95</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>23.6</td>\n","      <td>23.6</td>\n","    </tr>\n","    <tr>\n","      <th>1067352</th>\n","      <td>581586</td>\n","      <td>23275</td>\n","      <td>SET OF 3 HANGING OWLS OLLIE BEAK</td>\n","      <td>24</td>\n","      <td>2011-12-09</td>\n","      <td>1.25</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>30.0</td>\n","      <td>30.0</td>\n","    </tr>\n","    <tr>\n","      <th>1067353</th>\n","      <td>581586</td>\n","      <td>21217</td>\n","      <td>RED RETROSPOT ROUND CAKE TINS</td>\n","      <td>24</td>\n","      <td>2011-12-09</td>\n","      <td>8.95</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>214.8</td>\n","      <td>214.8</td>\n","    </tr>\n","    <tr>\n","      <th>1067354</th>\n","      <td>581586</td>\n","      <td>20685</td>\n","      <td>DOORMAT RED RETROSPOT</td>\n","      <td>10</td>\n","      <td>2011-12-09</td>\n","      <td>7.08</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>70.8</td>\n","      <td>70.8</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>700386 rows × 12 columns</p>\n","</div>"],"text/plain":["        Invoice StockCode                          Description  Quantity  \\\n","0        489434     85048  15CM CHRISTMAS GLASS BALL 20 LIGHTS        12   \n","1        489434    79323P                   PINK CHERRY LIGHTS        12   \n","2        489434    79323W                  WHITE CHERRY LIGHTS        12   \n","3        489434     22041         RECORD FRAME 7\" SINGLE SIZE         48   \n","4        489434     21232       STRAWBERRY CERAMIC TRINKET BOX        24   \n","...         ...       ...                                  ...       ...   \n","1067350  581585     22466       FAIRY TALE COTTAGE NIGHT LIGHT        12   \n","1067351  581586     22061  LARGE CAKE STAND  HANGING STRAWBERY         8   \n","1067352  581586     23275     SET OF 3 HANGING OWLS OLLIE BEAK        24   \n","1067353  581586     21217        RED RETROSPOT ROUND CAKE TINS        24   \n","1067354  581586     20685                DOORMAT RED RETROSPOT        10   \n","\n","        InvoiceDate  Price  CustomerID         Country  InvoiceMonth  \\\n","0        2009-12-01   6.95     13085.0  United Kingdom            12   \n","1        2009-12-01   6.75     13085.0  United Kingdom            12   \n","2        2009-12-01   6.75     13085.0  United Kingdom            12   \n","3        2009-12-01   2.10     13085.0  United Kingdom            12   \n","4        2009-12-01   1.25     13085.0  United Kingdom            12   \n","...             ...    ...         ...             ...           ...   \n","1067350  2011-12-09   1.95     15804.0  United Kingdom            12   \n","1067351  2011-12-09   2.95     13113.0  United Kingdom            12   \n","1067352  2011-12-09   1.25     13113.0  United Kingdom            12   \n","1067353  2011-12-09   8.95     13113.0  United Kingdom            12   \n","1067354  2011-12-09   7.08     13113.0  United Kingdom            12   \n","\n","         InvoiceYear  TotalPrice  TotalAmount  \n","0               2009        83.4         83.4  \n","1               2009        81.0         81.0  \n","2               2009        81.0         81.0  \n","3               2009       100.8        100.8  \n","4               2009        30.0         30.0  \n","...              ...         ...          ...  \n","1067350         2011        23.4         23.4  \n","1067351         2011        23.6         23.6  \n","1067352         2011        30.0         30.0  \n","1067353         2011       214.8        214.8  \n","1067354         2011        70.8         70.8  \n","\n","[700386 rows x 12 columns]"]},"metadata":{},"execution_count":24}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"6refwSYXlOvN","executionInfo":{"status":"ok","timestamp":1628904362830,"user_tz":-480,"elapsed":6,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"00d1031b-50f4-423e-ff57-bfca0b388b67"}},{"cell_type":"code","execution_count":25,"source":["df_new.describe()"],"outputs":[{"output_type":"execute_result","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>Quantity</th>\n","      <th>Price</th>\n","      <th>CustomerID</th>\n","      <th>InvoiceMonth</th>\n","      <th>InvoiceYear</th>\n","      <th>TotalPrice</th>\n","      <th>TotalAmount</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>700386.000000</td>\n","      <td>700386.000000</td>\n","      <td>700386.000000</td>\n","      <td>700386.000000</td>\n","      <td>700386.000000</td>\n","      <td>700386.000000</td>\n","      <td>700386.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>12.182429</td>\n","      <td>3.065462</td>\n","      <td>15550.403647</td>\n","      <td>7.434001</td>\n","      <td>2010.424933</td>\n","      <td>20.544673</td>\n","      <td>20.544673</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>143.110137</td>\n","      <td>25.598521</td>\n","      <td>1592.454624</td>\n","      <td>3.427001</td>\n","      <td>0.569810</td>\n","      <td>237.749194</td>\n","      <td>237.749194</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>1.000000</td>\n","      <td>0.001000</td>\n","      <td>12346.000000</td>\n","      <td>1.000000</td>\n","      <td>2009.000000</td>\n","      <td>0.001000</td>\n","      <td>0.001000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>2.000000</td>\n","      <td>1.250000</td>\n","      <td>14194.000000</td>\n","      <td>5.000000</td>\n","      <td>2010.000000</td>\n","      <td>4.250000</td>\n","      <td>4.250000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>4.000000</td>\n","      <td>1.950000</td>\n","      <td>15547.000000</td>\n","      <td>8.000000</td>\n","      <td>2010.000000</td>\n","      <td>10.500000</td>\n","      <td>10.500000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>12.000000</td>\n","      <td>3.750000</td>\n","      <td>16933.000000</td>\n","      <td>11.000000</td>\n","      <td>2011.000000</td>\n","      <td>17.850000</td>\n","      <td>17.850000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>80995.000000</td>\n","      <td>10953.500000</td>\n","      <td>18287.000000</td>\n","      <td>12.000000</td>\n","      <td>2011.000000</td>\n","      <td>168469.600000</td>\n","      <td>168469.600000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["            Quantity          Price     CustomerID   InvoiceMonth  \\\n","count  700386.000000  700386.000000  700386.000000  700386.000000   \n","mean       12.182429       3.065462   15550.403647       7.434001   \n","std       143.110137      25.598521    1592.454624       3.427001   \n","min         1.000000       0.001000   12346.000000       1.000000   \n","25%         2.000000       1.250000   14194.000000       5.000000   \n","50%         4.000000       1.950000   15547.000000       8.000000   \n","75%        12.000000       3.750000   16933.000000      11.000000   \n","max     80995.000000   10953.500000   18287.000000      12.000000   \n","\n","         InvoiceYear     TotalPrice    TotalAmount  \n","count  700386.000000  700386.000000  700386.000000  \n","mean     2010.424933      20.544673      20.544673  \n","std         0.569810     237.749194     237.749194  \n","min      2009.000000       0.001000       0.001000  \n","25%      2010.000000       4.250000       4.250000  \n","50%      2010.000000      10.500000      10.500000  \n","75%      2011.000000      17.850000      17.850000  \n","max      2011.000000  168469.600000  168469.600000  "]},"metadata":{},"execution_count":25}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":297},"id":"nACo2mYRps9k","executionInfo":{"status":"ok","timestamp":1628904362831,"user_tz":-480,"elapsed":6,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"e9088045-32c4-4e4a-b86a-55236466a111"}},{"cell_type":"markdown","source":["## Recency, Frequency and Monetary Value calculation"],"metadata":{"id":"IIXKIROPmSmd"}},{"cell_type":"code","execution_count":26,"source":["# snapshot day\r\n","print(f\"Data period: \\nStart:\\t{df_new.InvoiceDate.min()}\\nEnd:\\t{df_new.InvoiceDate.max()}\")\r\n","snapshot_date = df_new.InvoiceDate.max() + datetime.timedelta(days = 1)\r\n","print(f\"\\nSnapshot date: {snapshot_date}\")"],"outputs":[{"output_type":"stream","name":"stdout","text":["Data period: \n","Start:\t2009-12-01\n","End:\t2011-12-09\n","\n","Snapshot date: 2011-12-10\n"]}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1HgDkr5AthmL","executionInfo":{"status":"ok","timestamp":1628904363070,"user_tz":-480,"elapsed":4,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"809c9e1f-1eed-4e28-bc5c-52442257fb12"}},{"cell_type":"code","execution_count":27,"source":["df_new"],"outputs":[{"output_type":"execute_result","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>Invoice</th>\n","      <th>StockCode</th>\n","      <th>Description</th>\n","      <th>Quantity</th>\n","      <th>InvoiceDate</th>\n","      <th>Price</th>\n","      <th>CustomerID</th>\n","      <th>Country</th>\n","      <th>InvoiceMonth</th>\n","      <th>InvoiceYear</th>\n","      <th>TotalPrice</th>\n","      <th>TotalAmount</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>489434</td>\n","      <td>85048</td>\n","      <td>15CM CHRISTMAS GLASS BALL 20 LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.95</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>83.4</td>\n","      <td>83.4</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>489434</td>\n","      <td>79323P</td>\n","      <td>PINK CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>81.0</td>\n","      <td>81.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>489434</td>\n","      <td>79323W</td>\n","      <td>WHITE CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>81.0</td>\n","      <td>81.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>489434</td>\n","      <td>22041</td>\n","      <td>RECORD FRAME 7\" SINGLE SIZE</td>\n","      <td>48</td>\n","      <td>2009-12-01</td>\n","      <td>2.10</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>100.8</td>\n","      <td>100.8</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>489434</td>\n","      <td>21232</td>\n","      <td>STRAWBERRY CERAMIC TRINKET BOX</td>\n","      <td>24</td>\n","      <td>2009-12-01</td>\n","      <td>1.25</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>30.0</td>\n","      <td>30.0</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","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>1067350</th>\n","      <td>581585</td>\n","      <td>22466</td>\n","      <td>FAIRY TALE COTTAGE NIGHT LIGHT</td>\n","      <td>12</td>\n","      <td>2011-12-09</td>\n","      <td>1.95</td>\n","      <td>15804.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>23.4</td>\n","      <td>23.4</td>\n","    </tr>\n","    <tr>\n","      <th>1067351</th>\n","      <td>581586</td>\n","      <td>22061</td>\n","      <td>LARGE CAKE STAND  HANGING STRAWBERY</td>\n","      <td>8</td>\n","      <td>2011-12-09</td>\n","      <td>2.95</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>23.6</td>\n","      <td>23.6</td>\n","    </tr>\n","    <tr>\n","      <th>1067352</th>\n","      <td>581586</td>\n","      <td>23275</td>\n","      <td>SET OF 3 HANGING OWLS OLLIE BEAK</td>\n","      <td>24</td>\n","      <td>2011-12-09</td>\n","      <td>1.25</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>30.0</td>\n","      <td>30.0</td>\n","    </tr>\n","    <tr>\n","      <th>1067353</th>\n","      <td>581586</td>\n","      <td>21217</td>\n","      <td>RED RETROSPOT ROUND CAKE TINS</td>\n","      <td>24</td>\n","      <td>2011-12-09</td>\n","      <td>8.95</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>214.8</td>\n","      <td>214.8</td>\n","    </tr>\n","    <tr>\n","      <th>1067354</th>\n","      <td>581586</td>\n","      <td>20685</td>\n","      <td>DOORMAT RED RETROSPOT</td>\n","      <td>10</td>\n","      <td>2011-12-09</td>\n","      <td>7.08</td>\n","      <td>13113.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2011</td>\n","      <td>70.8</td>\n","      <td>70.8</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>700386 rows × 12 columns</p>\n","</div>"],"text/plain":["        Invoice StockCode                          Description  Quantity  \\\n","0        489434     85048  15CM CHRISTMAS GLASS BALL 20 LIGHTS        12   \n","1        489434    79323P                   PINK CHERRY LIGHTS        12   \n","2        489434    79323W                  WHITE CHERRY LIGHTS        12   \n","3        489434     22041         RECORD FRAME 7\" SINGLE SIZE         48   \n","4        489434     21232       STRAWBERRY CERAMIC TRINKET BOX        24   \n","...         ...       ...                                  ...       ...   \n","1067350  581585     22466       FAIRY TALE COTTAGE NIGHT LIGHT        12   \n","1067351  581586     22061  LARGE CAKE STAND  HANGING STRAWBERY         8   \n","1067352  581586     23275     SET OF 3 HANGING OWLS OLLIE BEAK        24   \n","1067353  581586     21217        RED RETROSPOT ROUND CAKE TINS        24   \n","1067354  581586     20685                DOORMAT RED RETROSPOT        10   \n","\n","        InvoiceDate  Price  CustomerID         Country  InvoiceMonth  \\\n","0        2009-12-01   6.95     13085.0  United Kingdom            12   \n","1        2009-12-01   6.75     13085.0  United Kingdom            12   \n","2        2009-12-01   6.75     13085.0  United Kingdom            12   \n","3        2009-12-01   2.10     13085.0  United Kingdom            12   \n","4        2009-12-01   1.25     13085.0  United Kingdom            12   \n","...             ...    ...         ...             ...           ...   \n","1067350  2011-12-09   1.95     15804.0  United Kingdom            12   \n","1067351  2011-12-09   2.95     13113.0  United Kingdom            12   \n","1067352  2011-12-09   1.25     13113.0  United Kingdom            12   \n","1067353  2011-12-09   8.95     13113.0  United Kingdom            12   \n","1067354  2011-12-09   7.08     13113.0  United Kingdom            12   \n","\n","         InvoiceYear  TotalPrice  TotalAmount  \n","0               2009        83.4         83.4  \n","1               2009        81.0         81.0  \n","2               2009        81.0         81.0  \n","3               2009       100.8        100.8  \n","4               2009        30.0         30.0  \n","...              ...         ...          ...  \n","1067350         2011        23.4         23.4  \n","1067351         2011        23.6         23.6  \n","1067352         2011        30.0         30.0  \n","1067353         2011       214.8        214.8  \n","1067354         2011        70.8         70.8  \n","\n","[700386 rows x 12 columns]"]},"metadata":{},"execution_count":27}],"metadata":{"id":"j0Z_mxwEmUk7","colab":{"base_uri":"https://localhost:8080/","height":419},"executionInfo":{"status":"ok","timestamp":1628904363300,"user_tz":-480,"elapsed":232,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"226434c9-5f0c-46a9-97be-88d2dce27de8"}},{"cell_type":"code","execution_count":28,"source":["rfm_df = df_new.groupby(\"CustomerID\").agg({'InvoiceDate': lambda x : (snapshot_date - x.max()).days,\r\n","                                           'Invoice':'count',\r\n","                                           'TotalAmount': 'sum'})"],"outputs":[],"metadata":{"id":"pPFd2riUmUjK","executionInfo":{"status":"ok","timestamp":1628904364576,"user_tz":-480,"elapsed":1279,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":29,"source":["rfm_df.rename(columns={'InvoiceDate':'Recency', 'Invoice':'Frequency', 'TotalAmount':'MonetaryValue'},inplace = True)"],"outputs":[],"metadata":{"id":"RFWQ4_4owUjg","executionInfo":{"status":"ok","timestamp":1628904364578,"user_tz":-480,"elapsed":4,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"markdown","source":["# relation between RFM\n"],"metadata":{"id":"8T5UMj0E59Z-"}},{"cell_type":"code","execution_count":30,"source":["dist_box_violin(rfm_df.Recency)"],"outputs":[{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 1152x432 with 3 Axes>"]},"metadata":{}}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":554},"id":"dHmkdmY827qY","executionInfo":{"status":"ok","timestamp":1628904365182,"user_tz":-480,"elapsed":607,"user":{"displayName":"Nicole 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","text/plain":["<Figure 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","text/plain":["<Figure size 1152x432 with 3 Axes>"]},"metadata":{}}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"nACCZLMG4E8p","executionInfo":{"status":"ok","timestamp":1628904366768,"user_tz":-480,"elapsed":1589,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"89d022c5-12e9-4561-8605-c968e533727e"}},{"cell_type":"code","execution_count":32,"source":["dist_box_violin(rfm_df.MonetaryValue)\r\n","dist_box_violin(np.log(rfm_df.MonetaryValue))"],"outputs":[{"output_type":"display_data","data":{"image/png":"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","text/plain":["<Figure size 1152x432 with 3 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","text/plain":["<Figure size 1152x432 with 3 Axes>"]},"metadata":{}}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"uXJFFNjV4E1o","executionInfo":{"status":"ok","timestamp":1628904367924,"user_tz":-480,"elapsed":1158,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"d999c394-8dac-4879-c906-e597797e1cbe"}},{"cell_type":"markdown","source":["**Finding;**\r\n","- generally, the mean of last time customers purchased from the brand is around 100 days, while a lot of recently purchase records."],"metadata":{"id":"aEUbcqWY4u2S"}},{"cell_type":"code","execution_count":33,"source":["# relation between RFM\r\n","\r\n","rfm_df.describe()"],"outputs":[{"output_type":"execute_result","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>Recency</th>\n","      <th>Frequency</th>\n","      <th>MonetaryValue</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>5350.000000</td>\n","      <td>5350.000000</td>\n","      <td>5350.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>203.546168</td>\n","      <td>130.913271</td>\n","      <td>2689.570340</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>209.973818</td>\n","      <td>313.455279</td>\n","      <td>11706.526134</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>2.950000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>26.000000</td>\n","      <td>20.000000</td>\n","      <td>330.202500</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>99.000000</td>\n","      <td>52.000000</td>\n","      <td>829.440000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>382.000000</td>\n","      <td>137.000000</td>\n","      <td>2156.250000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>739.000000</td>\n","      <td>12435.000000</td>\n","      <td>580987.040000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["           Recency     Frequency  MonetaryValue\n","count  5350.000000   5350.000000    5350.000000\n","mean    203.546168    130.913271    2689.570340\n","std     209.973818    313.455279   11706.526134\n","min       1.000000      1.000000       2.950000\n","25%      26.000000     20.000000     330.202500\n","50%      99.000000     52.000000     829.440000\n","75%     382.000000    137.000000    2156.250000\n","max     739.000000  12435.000000  580987.040000"]},"metadata":{},"execution_count":33}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":297},"id":"rXTTVCHC441S","executionInfo":{"status":"ok","timestamp":1628904368512,"user_tz":-480,"elapsed":592,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"2a3fca9f-7e79-485e-d492-61704141f326"}},{"cell_type":"code","execution_count":34,"source":["rfm_df"],"outputs":[{"output_type":"execute_result","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>Recency</th>\n","      <th>Frequency</th>\n","      <th>MonetaryValue</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>326</td>\n","      <td>34</td>\n","      <td>77556.46</td>\n","    </tr>\n","    <tr>\n","      <th>12608.0</th>\n","      <td>405</td>\n","      <td>16</td>\n","      <td>415.79</td>\n","    </tr>\n","    <tr>\n","      <th>12745.0</th>\n","      <td>487</td>\n","      <td>22</td>\n","      <td>723.85</td>\n","    </tr>\n","    <tr>\n","      <th>12746.0</th>\n","      <td>541</td>\n","      <td>17</td>\n","      <td>254.55</td>\n","    </tr>\n","    <tr>\n","      <th>12747.0</th>\n","      <td>3</td>\n","      <td>249</td>\n","      <td>8898.48</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>18283.0</th>\n","      <td>4</td>\n","      <td>938</td>\n","      <td>2664.90</td>\n","    </tr>\n","    <tr>\n","      <th>18284.0</th>\n","      <td>432</td>\n","      <td>28</td>\n","      <td>461.68</td>\n","    </tr>\n","    <tr>\n","      <th>18285.0</th>\n","      <td>661</td>\n","      <td>12</td>\n","      <td>427.00</td>\n","    </tr>\n","    <tr>\n","      <th>18286.0</th>\n","      <td>477</td>\n","      <td>67</td>\n","      <td>1296.43</td>\n","    </tr>\n","    <tr>\n","      <th>18287.0</th>\n","      <td>43</td>\n","      <td>155</td>\n","      <td>4182.99</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5350 rows × 3 columns</p>\n","</div>"],"text/plain":["            Recency  Frequency  MonetaryValue\n","CustomerID                                   \n","12346.0         326         34       77556.46\n","12608.0         405         16         415.79\n","12745.0         487         22         723.85\n","12746.0         541         17         254.55\n","12747.0           3        249        8898.48\n","...             ...        ...            ...\n","18283.0           4        938        2664.90\n","18284.0         432         28         461.68\n","18285.0         661         12         427.00\n","18286.0         477         67        1296.43\n","18287.0          43        155        4182.99\n","\n","[5350 rows x 3 columns]"]},"metadata":{},"execution_count":34}],"metadata":{"id":"-cmlnwd44iMs","colab":{"base_uri":"https://localhost:8080/","height":450},"executionInfo":{"status":"ok","timestamp":1628904368513,"user_tz":-480,"elapsed":15,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"731b80dc-79be-4c3e-ffd6-964609853e56"}},{"cell_type":"code","execution_count":35,"source":["# calculate R,F,M score\r\n","\r\n","rfm_df[\"R\"] = pd.qcut(rfm_df[\"Recency\"], q = 4, labels = [1,2,3,4]) # smaller the better\r\n","rfm_df[\"F\"] =  pd.qcut(rfm_df[\"Frequency\"], q = 4, labels = [4,3,2,1]) # larger the better\r\n","rfm_df[\"M\"] = pd.qcut(rfm_df[\"MonetaryValue\"], q = 4, labels = [4,3,2,1]) # larger the better\r\n","\r\n","rfm_df[\"RFMSegment\"] = rfm_df[\"R\"].astype(\"string\") + rfm_df[\"F\"].astype(\"string\") + rfm_df[\"M\"].astype(\"string\")\r\n","rfm_df[\"RFMScore\"] = rfm_df[\"R\"].astype(\"int\") + rfm_df[\"F\"].astype(\"int\") + rfm_df[\"M\"].astype(\"int\") "],"outputs":[],"metadata":{"id":"Cf0inKXwOtta","executionInfo":{"status":"ok","timestamp":1628904368514,"user_tz":-480,"elapsed":14,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":36,"source":["rfm_df"],"outputs":[{"output_type":"execute_result","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>Recency</th>\n","      <th>Frequency</th>\n","      <th>MonetaryValue</th>\n","      <th>R</th>\n","      <th>F</th>\n","      <th>M</th>\n","      <th>RFMSegment</th>\n","      <th>RFMScore</th>\n","    </tr>\n","    <tr>\n","      <th>CustomerID</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>12346.0</th>\n","      <td>326</td>\n","      <td>34</td>\n","      <td>77556.46</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>331</td>\n","      <td>7</td>\n","    </tr>\n","    <tr>\n","      <th>12608.0</th>\n","      <td>405</td>\n","      <td>16</td>\n","      <td>415.79</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>443</td>\n","      <td>11</td>\n","    </tr>\n","    <tr>\n","      <th>12745.0</th>\n","      <td>487</td>\n","      <td>22</td>\n","      <td>723.85</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>433</td>\n","      <td>10</td>\n","    </tr>\n","    <tr>\n","      <th>12746.0</th>\n","      <td>541</td>\n","      <td>17</td>\n","      <td>254.55</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>444</td>\n","      <td>12</td>\n","    </tr>\n","    <tr>\n","      <th>12747.0</th>\n","      <td>3</td>\n","      <td>249</td>\n","      <td>8898.48</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>111</td>\n","      <td>3</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>18283.0</th>\n","      <td>4</td>\n","      <td>938</td>\n","      <td>2664.90</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>111</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>18284.0</th>\n","      <td>432</td>\n","      <td>28</td>\n","      <td>461.68</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>433</td>\n","      <td>10</td>\n","    </tr>\n","    <tr>\n","      <th>18285.0</th>\n","      <td>661</td>\n","      <td>12</td>\n","      <td>427.00</td>\n","      <td>4</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>443</td>\n","      <td>11</td>\n","    </tr>\n","    <tr>\n","      <th>18286.0</th>\n","      <td>477</td>\n","      <td>67</td>\n","      <td>1296.43</td>\n","      <td>4</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>422</td>\n","      <td>8</td>\n","    </tr>\n","    <tr>\n","      <th>18287.0</th>\n","      <td>43</td>\n","      <td>155</td>\n","      <td>4182.99</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>211</td>\n","      <td>4</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5350 rows × 8 columns</p>\n","</div>"],"text/plain":["            Recency  Frequency  MonetaryValue  R  F  M RFMSegment  RFMScore\n","CustomerID                                                                 \n","12346.0         326         34       77556.46  3  3  1        331         7\n","12608.0         405         16         415.79  4  4  3        443        11\n","12745.0         487         22         723.85  4  3  3        433        10\n","12746.0         541         17         254.55  4  4  4        444        12\n","12747.0           3        249        8898.48  1  1  1        111         3\n","...             ...        ...            ... .. .. ..        ...       ...\n","18283.0           4        938        2664.90  1  1  1        111         3\n","18284.0         432         28         461.68  4  3  3        433        10\n","18285.0         661         12         427.00  4  4  3        443        11\n","18286.0         477         67        1296.43  4  2  2        422         8\n","18287.0          43        155        4182.99  2  1  1        211         4\n","\n","[5350 rows x 8 columns]"]},"metadata":{},"execution_count":36}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":450},"id":"260IUGj5O-6f","executionInfo":{"status":"ok","timestamp":1628904368515,"user_tz":-480,"elapsed":14,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"7729a00f-38bd-4fd1-aa0c-a75c246b5264"}},{"cell_type":"markdown","source":["## Analyzing RFM Segments"],"metadata":{"id":"ACY9krnWmVCg"}},{"cell_type":"markdown","source":["1. Segment the RFM_score and get the final group, \n","2. Add the RFM label to the new_df dataframe, \n","3. Call out what is the common product (Description) bought by each group."],"metadata":{"id":"w0XZ20Oh6UJm"}},{"cell_type":"code","execution_count":37,"source":["rfm_df.groupby(\"RFMScore\").agg({\"Recency\":\"mean\", \"Frequency\":\"mean\", \"MonetaryValue\":[\"mean\",\"count\"]}).round(2)"],"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead tr th {\n","        text-align: left;\n","    }\n","\n","    .dataframe thead tr:last-of-type th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr>\n","      <th></th>\n","      <th>Recency</th>\n","      <th>Frequency</th>\n","      <th colspan=\"2\" halign=\"left\">MonetaryValue</th>\n","    </tr>\n","    <tr>\n","      <th></th>\n","      <th>mean</th>\n","      <th>mean</th>\n","      <th>mean</th>\n","      <th>count</th>\n","    </tr>\n","    <tr>\n","      <th>RFMScore</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>3</th>\n","      <td>10.53</td>\n","      <td>541.81</td>\n","      <td>12675.66</td>\n","      <td>564</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>36.92</td>\n","      <td>277.21</td>\n","      <td>4774.65</td>\n","      <td>488</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>68.53</td>\n","      <td>172.00</td>\n","      <td>3125.23</td>\n","      <td>506</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>97.82</td>\n","      <td>109.92</td>\n","      <td>2204.62</td>\n","      <td>509</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>152.53</td>\n","      <td>74.24</td>\n","      <td>1376.97</td>\n","      <td>563</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>188.96</td>\n","      <td>49.31</td>\n","      <td>1091.10</td>\n","      <td>569</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>236.85</td>\n","      <td>34.55</td>\n","      <td>652.16</td>\n","      <td>566</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>318.03</td>\n","      <td>23.80</td>\n","      <td>407.53</td>\n","      <td>574</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>385.98</td>\n","      <td>17.18</td>\n","      <td>240.75</td>\n","      <td>513</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>547.29</td>\n","      <td>9.37</td>\n","      <td>168.59</td>\n","      <td>498</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["         Recency Frequency MonetaryValue      \n","            mean      mean          mean count\n","RFMScore                                      \n","3          10.53    541.81      12675.66   564\n","4          36.92    277.21       4774.65   488\n","5          68.53    172.00       3125.23   506\n","6          97.82    109.92       2204.62   509\n","7         152.53     74.24       1376.97   563\n","8         188.96     49.31       1091.10   569\n","9         236.85     34.55        652.16   566\n","10        318.03     23.80        407.53   574\n","11        385.98     17.18        240.75   513\n","12        547.29      9.37        168.59   498"]},"metadata":{},"execution_count":37}],"metadata":{"id":"BLaf_fdTmWsI","colab":{"base_uri":"https://localhost:8080/","height":421},"executionInfo":{"status":"ok","timestamp":1628904368515,"user_tz":-480,"elapsed":13,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"f151460f-524d-484d-c85d-93a9464d8bfb"}},{"cell_type":"markdown","source":["**Customers Segments:**\r\n","- 3 - 5\r\n","- 6 - 8\r\n","- 9 - 12"],"metadata":{"id":"yAAqQ_LfRaia"}},{"cell_type":"code","execution_count":38,"source":["customergroup_df = rfm_df.drop(columns=[\"Recency\",\"Frequency\",\"MonetaryValue\"])\r\n","customergroup_df[\"CustomerGroup\"] = np.where((customergroup_df[\"RFMScore\"] < 6), \"Gold\",\r\n","                                     np.where((customergroup_df[\"RFMScore\"] > 8), \"Bronze\",\"Sliver\"))"],"outputs":[],"metadata":{"id":"m2dSb21WTNeB","executionInfo":{"status":"ok","timestamp":1628905212568,"user_tz":-480,"elapsed":253,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":57,"source":["customergroup_df.reset_index(inplace=True)"],"outputs":[],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":450},"id":"z6ykXcQvURVL","executionInfo":{"status":"ok","timestamp":1628905217217,"user_tz":-480,"elapsed":262,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"e25882af-e788-4da0-d2b0-2d26ad56f3fc"}},{"cell_type":"code","execution_count":60,"source":["# save csv for further analysis\r\n","# customergroup_df.to_csv(\"customergroup_brief.csv\",index_label=False)"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":61,"source":["customergroup_df.RFMScore.value_counts()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["10    574\n","8     569\n","9     566\n","3     564\n","7     563\n","11    513\n","6     509\n","5     506\n","12    498\n","4     488\n","Name: RFMScore, dtype: int64"]},"metadata":{},"execution_count":61}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"c0pzh3MCUoSI","executionInfo":{"status":"ok","timestamp":1628905319729,"user_tz":-480,"elapsed":235,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"061908e3-f1db-43cb-bace-20e46e412891"}},{"cell_type":"code","execution_count":42,"source":["customergroup_df.CustomerGroup.value_counts()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["Bronze    2151\n","Sliver    1641\n","Gold      1558\n","Name: CustomerGroup, dtype: int64"]},"metadata":{},"execution_count":42}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"e6O2liH8UgI3","executionInfo":{"status":"ok","timestamp":1628905296726,"user_tz":-480,"elapsed":226,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"d3dee353-9175-451e-8beb-a9b29795cf79"}},{"cell_type":"markdown","source":["## Customers segmentation with RFMSegment"],"metadata":{"id":"vc8tc8jbVLL-"}},{"cell_type":"code","execution_count":43,"source":["final_df = df_new.merge(rfm_df, on=\"CustomerID\")\r\n","\r\n","final_df[\"CustomerGroup\"] = np.where((final_df[\"RFMScore\"] > 9), \"Gold\",\r\n","                                     np.where((final_df[\"RFMScore\"] < 7), \"Bronze\",\"Sliver\"))"],"outputs":[],"metadata":{"id":"LsVpHC4smZUv","executionInfo":{"status":"ok","timestamp":1628904369072,"user_tz":-480,"elapsed":567,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":44,"source":["final_df[\"RFMSegment\"].value_counts()"],"outputs":[{"output_type":"execute_result","data":{"text/plain":["111    305583\n","211    100659\n","311     37116\n","112     25792\n","212     21878\n","222     18171\n","322     17820\n","122     14338\n","312     14081\n","221      9641\n","121      8829\n","422      8292\n","323      7473\n","333      7396\n","433      7305\n","411      6741\n","412      6428\n","123      6397\n","223      5926\n","233      5401\n","423      5367\n","321      5299\n","434      4953\n","444      4664\n","133      3501\n","332      3338\n","113      3331\n","232      3293\n","344      2469\n","213      2452\n","334      2382\n","313      2271\n","432      2002\n","132      1975\n","234      1526\n","324      1504\n","244      1399\n","424      1393\n","443      1389\n","421      1311\n","343       995\n","134       900\n","231       800\n","224       764\n","144       740\n","131       727\n","243       691\n","124       649\n","143       643\n","413       501\n","331       388\n","431       337\n","242       282\n","342       254\n","442       187\n","142       129\n","341       124\n","241        79\n","441        76\n","141        34\n","Name: RFMSegment, dtype: Int64"]},"metadata":{},"execution_count":44}],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vh1wFg0qVb2U","executionInfo":{"status":"ok","timestamp":1628905560660,"user_tz":-480,"elapsed":240,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"f02ea8df-2acf-4a0e-c84f-7e073c51923a"}},{"cell_type":"markdown","source":["## RFM Customers segmentation for different marketing strategies:"],"metadata":{}},{"cell_type":"code","execution_count":45,"source":["best_customer = [\"111\"]\r\n","high_spending_new = [\"141\",\"142\"]\r\n","lowest_spending_loyal = [\"113\",\"114\"]\r\n","churned_best = [\"411\",\"412\",\"421\",\"422\"]\r\n","\r\n","id_list = [best_customer,high_spending_new,lowest_spending_loyal,churned_best]"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":46,"source":["# sub-function\r\n","def rfm_customer(label):\r\n","    array = final_df[final_df[\"RFMSegment\"] == label].CustomerID.unique()\r\n","    outcome_list = array.tolist()\r\n","    outcome_list = sorted([int(y) for y in outcome_list])\r\n","    \r\n","    return outcome_list \r\n","\r\n","# # main-function\r\n","# def rfm_id(group):\r\n","#       outcome_list = []\r\n","#       for x in high_spending_new:\r\n","#             id = rfm_customer(x)\r\n","\r\n","#             for y in id:\r\n","#                   outcome_list.append(y)\r\n","\r\n","#       return outcome_list"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":47,"source":["# a for loop print out all the customer group \r\n","for group in id_list:\r\n","      print(f\"These are the Customer ID for {group}:\")\r\n","      for label in group:\r\n","            print(f\"RFM Segment = *{label}*\")\r\n","            print(rfm_customer(label))\r\n","            print()\r\n","      print(\"-\"*200,\"\\n\")"],"outputs":[{"output_type":"stream","name":"stdout","text":["These are the Customer ID for ['111']:\n","RFM Segment = *111*\n","[12747, 12748, 12749, 12820, 12826, 12839, 12841, 12856, 12877, 12921, 12931, 12935, 12937, 12951, 12955, 12957, 12963, 12971, 13001, 13004, 13012, 13013, 13014, 13018, 13021, 13048, 13050, 13069, 13077, 13078, 13081, 13089, 13090, 13098, 13102, 13113, 13115, 13117, 13118, 13126, 13131, 13137, 13139, 13173, 13174, 13183, 13196, 13198, 13199, 13203, 13211, 13230, 13246, 13263, 13266, 13267, 13268, 13269, 13285, 13305, 13313, 13319, 13362, 13394, 13408, 13418, 13426, 13435, 13437, 13448, 13458, 13468, 13471, 13488, 13507, 13510, 13534, 13536, 13571, 13576, 13577, 13588, 13590, 13599, 13614, 13632, 13644, 13647, 13650, 13658, 13668, 13680, 13694, 13709, 13719, 13735, 13736, 13742, 13756, 13758, 13767, 13769, 13777, 13798, 13823, 13831, 13854, 13862, 13870, 13871, 13880, 13881, 13883, 13890, 13949, 13969, 13971, 13985, 13988, 13994, 13995, 13999, 14030, 14031, 14032, 14047, 14049, 14051, 14056, 14057, 14060, 14062, 14085, 14088, 14092, 14096, 14099, 14110, 14112, 14121, 14125, 14132, 14135, 14146, 14159, 14180, 14189, 14191, 14194, 14209, 14215, 14217, 14243, 14258, 14262, 14282, 14286, 14290, 14291, 14292, 14298, 14299, 14309, 14321, 14329, 14334, 14367, 14388, 14390, 14395, 14401, 14415, 14422, 14426, 14432, 14441, 14449, 14456, 14467, 14482, 14493, 14502, 14503, 14505, 14506, 14507, 14515, 14525, 14527, 14530, 14534, 14540, 14544, 14546, 14547, 14554, 14560, 14562, 14572, 14593, 14606, 14607, 14621, 14626, 14640, 14649, 14653, 14659, 14667, 14673, 14680, 14688, 14696, 14701, 14702, 14709, 14711, 14713, 14732, 14733, 14735, 14739, 14755, 14766, 14769, 14790, 14796, 14824, 14825, 14849, 14868, 14869, 14878, 14895, 14898, 14903, 14907, 14961, 14963, 15005, 15021, 15023, 15024, 15031, 15033, 15034, 15039, 15044, 15046, 15050, 15051, 15058, 15061, 15073, 15078, 15089, 15093, 15105, 15123, 15125, 15144, 15150, 15152, 15157, 15159, 15179, 15189, 15194, 15203, 15218, 15251, 15270, 15271, 15290, 15291, 15298, 15311, 15351, 15358, 15365, 15373, 15382, 15392, 15394, 15426, 15443, 15465, 15482, 15484, 15494, 15498, 15502, 15514, 15527, 15529, 15532, 15544, 15547, 15550, 15555, 15563, 15570, 15571, 15572, 15601, 15615, 15628, 15632, 15640, 15660, 15676, 15680, 15687, 15694, 15712, 15727, 15738, 15747, 15750, 15755, 15769, 15796, 15804, 15805, 15811, 15838, 15845, 15854, 15856, 15858, 15861, 15862, 15867, 15898, 15906, 15910, 15916, 15953, 15955, 15965, 15967, 15981, 15983, 15984, 15993, 16005, 16008, 16011, 16013, 16033, 16057, 16062, 16085, 16094, 16103, 16115, 16128, 16133, 16143, 16145, 16156, 16161, 16168, 16186, 16191, 16200, 16210, 16241, 16242, 16255, 16265, 16271, 16279, 16283, 16293, 16303, 16326, 16327, 16341, 16347, 16353, 16358, 16360, 16369, 16393, 16401, 16407, 16422, 16440, 16458, 16496, 16523, 16525, 16531, 16549, 16558, 16570, 16592, 16607, 16609, 16626, 16633, 16638, 16655, 16656, 16670, 16678, 16684, 16700, 16701, 16705, 16710, 16712, 16713, 16717, 16719, 16722, 16746, 16748, 16764, 16775, 16779, 16782, 16814, 16817, 16818, 16839, 16873, 16904, 16905, 16923, 16931, 16933, 16938, 16945, 16954, 16983, 16985, 16987, 16992, 17001, 17017, 17019, 17044, 17049, 17063, 17068, 17075, 17091, 17096, 17139, 17157, 17188, 17218, 17220, 17228, 17231, 17238, 17243, 17288, 17293, 17314, 17315, 17324, 17338, 17346, 17348, 17364, 17365, 17368, 17377, 17381, 17389, 17402, 17412, 17419, 17422, 17426, 17428, 17449, 17450, 17463, 17469, 17491, 17511, 17519, 17528, 17530, 17567, 17576, 17581, 17593, 17596, 17602, 17611, 17613, 17618, 17625, 17629, 17644, 17651, 17652, 17659, 17663, 17673, 17675, 17676, 17677, 17682, 17685, 17686, 17700, 17706, 17716, 17725, 17728, 17730, 17735, 17738, 17739, 17744, 17754, 17757, 17758, 17768, 17769, 17799, 17811, 17827, 17841, 17858, 17861, 17870, 17884, 17920, 17949, 17954, 17961, 17975, 18041, 18044, 18055, 18065, 18075, 18077, 18092, 18097, 18102, 18109, 18118, 18139, 18145, 18172, 18198, 18210, 18219, 18223, 18225, 18229, 18230, 18241, 18245, 18272, 18283]\n","\n","-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- \n","\n","These are the Customer ID for ['141', '142']:\n","RFM Segment = *141*\n","[15195, 16000, 16446, 16532, 17929]\n","\n","RFM Segment = *142*\n","[12882, 14434, 14477, 14987, 15267, 15473, 15621, 16989, 17500, 17856, 18080]\n","\n","-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- \n","\n","These are the Customer ID for ['113', '114']:\n","RFM Segment = *113*\n","[13212, 13428, 13558, 13569, 13596, 14234, 14508, 15720, 15872, 15901, 16015, 16406, 16411, 16469, 16936, 17254, 17371, 17561, 17777, 18034]\n","\n","RFM Segment = *114*\n","[]\n","\n","-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- \n","\n","These are the Customer ID for ['411', '412', '421', '422']:\n","RFM Segment = *411*\n","[12835, 12978, 13031, 13206, 13214, 13446, 14134, 14249, 14590, 14648, 14685, 15015, 15633, 15817, 16335, 16736, 17032, 17113, 17145, 17241, 17448, 17465, 17822]\n","\n","RFM Segment = *412*\n","[12911, 12926, 13042, 13443, 13567, 14343, 14399, 14469, 14686, 14994, 15003, 15013, 15425, 15542, 15879, 15911, 15972, 16032, 16300, 16391, 16501, 16521, 16797, 16798, 16894, 17137, 17539, 17610, 17851]\n","\n","RFM Segment = *421*\n","[12986, 13371, 13407, 13478, 13935, 14025, 14160, 15369, 15614, 15629, 16067, 16336, 16636, 16749, 16772, 18051]\n","\n","RFM Segment = *422*\n","[12862, 12905, 12932, 12960, 12972, 12975, 12998, 13039, 13152, 13154, 13156, 13201, 13202, 13204, 13293, 13333, 13337, 13360, 13377, 13393, 13440, 13459, 13613, 13648, 13665, 13775, 13797, 13855, 13857, 13872, 13916, 13920, 14136, 14186, 14225, 14478, 14490, 14492, 14634, 14671, 14695, 14734, 14831, 14839, 14899, 14909, 15064, 15141, 15151, 15248, 15259, 15439, 15441, 15559, 15590, 15600, 15710, 15736, 15751, 15792, 15798, 16004, 16129, 16130, 16167, 16176, 16197, 16228, 16290, 16296, 16307, 16314, 16329, 16435, 16588, 16608, 16631, 16661, 16702, 16787, 16854, 16946, 16991, 17020, 17028, 17132, 17143, 17332, 17366, 17421, 17529, 17544, 17635, 17713, 17726, 17853, 18057, 18060, 18214, 18286]\n","\n","-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- \n","\n"]}],"metadata":{}},{"cell_type":"markdown","source":["### From the above, we have the customer ID for each group, and lets go for the recommendation in maintaining good relationship with them"],"metadata":{}},{"cell_type":"markdown","source":["**111 - Best Customer**\r\n","\r\n","This group consist of those customers who are found in R-tier 1; F-tier 1; and M-tier 1, meaning that they purchased recently and spend more than other customers, we should maintain great relationship with this group of customers and make them feel valued and appreciated. They are likely generate high percentage of overall revenues and remaining a great relationship with them should be a priority."],"metadata":{}},{"cell_type":"markdown","source":["**141,142 - High-spending New-joined Customer**\r\n","\r\n","There are customers who are purchased very recently and spent a high amount. It is important to make them feel valued and appreciated, to give them terrific incentives to continue interacting with us. "],"metadata":{}},{"cell_type":"markdown","source":["**411,412,421,422 - Churned Customers**\r\n","\r\n","They are the customers who purchased frequently and spent a lot, but its been a long time since their last transaction, just like they are churned. They are valuable customers and it is challenging to re-engage them, but the high value of these customers makes it worthwhile trying."],"metadata":{}},{"cell_type":"markdown","source":["**113,114 - Lowest-Spending Loyal Customers**\r\n","\r\n","This group of customers spent the least among all, but purchased recently and do so often. These repeat purchasing shows that they are active and loyal, what we should do is to create their motivation/incentive to increase their spending level. As loyal customers, one of the most common way is to provide special offers to them.\r\n","\r\n"],"metadata":{}},{"cell_type":"markdown","source":["## Customer Anaylsis - Products Keywords"],"metadata":{"id":"44TdGjFrVEAh"}},{"cell_type":"markdown","source":["**Keyword of products in different segments**"],"metadata":{"id":"fxseOip8T7wa"}},{"cell_type":"code","execution_count":48,"source":["final_df.head()"],"outputs":[{"output_type":"execute_result","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>Invoice</th>\n","      <th>StockCode</th>\n","      <th>Description</th>\n","      <th>Quantity</th>\n","      <th>InvoiceDate</th>\n","      <th>Price</th>\n","      <th>CustomerID</th>\n","      <th>Country</th>\n","      <th>InvoiceMonth</th>\n","      <th>InvoiceYear</th>\n","      <th>...</th>\n","      <th>TotalAmount</th>\n","      <th>Recency</th>\n","      <th>Frequency</th>\n","      <th>MonetaryValue</th>\n","      <th>R</th>\n","      <th>F</th>\n","      <th>M</th>\n","      <th>RFMSegment</th>\n","      <th>RFMScore</th>\n","      <th>CustomerGroup</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>489434</td>\n","      <td>85048</td>\n","      <td>15CM CHRISTMAS GLASS BALL 20 LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.95</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>...</td>\n","      <td>83.4</td>\n","      <td>158</td>\n","      <td>84</td>\n","      <td>2433.28</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>321</td>\n","      <td>6</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>489434</td>\n","      <td>79323P</td>\n","      <td>PINK CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>...</td>\n","      <td>81.0</td>\n","      <td>158</td>\n","      <td>84</td>\n","      <td>2433.28</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>321</td>\n","      <td>6</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>489434</td>\n","      <td>79323W</td>\n","      <td>WHITE CHERRY LIGHTS</td>\n","      <td>12</td>\n","      <td>2009-12-01</td>\n","      <td>6.75</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>...</td>\n","      <td>81.0</td>\n","      <td>158</td>\n","      <td>84</td>\n","      <td>2433.28</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>321</td>\n","      <td>6</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>489434</td>\n","      <td>22041</td>\n","      <td>RECORD FRAME 7\" SINGLE SIZE</td>\n","      <td>48</td>\n","      <td>2009-12-01</td>\n","      <td>2.10</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>...</td>\n","      <td>100.8</td>\n","      <td>158</td>\n","      <td>84</td>\n","      <td>2433.28</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>321</td>\n","      <td>6</td>\n","      <td>Bronze</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>489434</td>\n","      <td>21232</td>\n","      <td>STRAWBERRY CERAMIC TRINKET BOX</td>\n","      <td>24</td>\n","      <td>2009-12-01</td>\n","      <td>1.25</td>\n","      <td>13085.0</td>\n","      <td>United Kingdom</td>\n","      <td>12</td>\n","      <td>2009</td>\n","      <td>...</td>\n","      <td>30.0</td>\n","      <td>158</td>\n","      <td>84</td>\n","      <td>2433.28</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>321</td>\n","      <td>6</td>\n","      <td>Bronze</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 21 columns</p>\n","</div>"],"text/plain":["  Invoice StockCode                          Description  Quantity  \\\n","0  489434     85048  15CM CHRISTMAS GLASS BALL 20 LIGHTS        12   \n","1  489434    79323P                   PINK CHERRY LIGHTS        12   \n","2  489434    79323W                  WHITE CHERRY LIGHTS        12   \n","3  489434     22041         RECORD FRAME 7\" SINGLE SIZE         48   \n","4  489434     21232       STRAWBERRY CERAMIC TRINKET BOX        24   \n","\n","  InvoiceDate  Price  CustomerID         Country  InvoiceMonth  InvoiceYear  \\\n","0  2009-12-01   6.95     13085.0  United Kingdom            12         2009   \n","1  2009-12-01   6.75     13085.0  United Kingdom            12         2009   \n","2  2009-12-01   6.75     13085.0  United Kingdom            12         2009   \n","3  2009-12-01   2.10     13085.0  United Kingdom            12         2009   \n","4  2009-12-01   1.25     13085.0  United Kingdom            12         2009   \n","\n","   ...  TotalAmount  Recency  Frequency  MonetaryValue  R  F  M RFMSegment  \\\n","0  ...         83.4      158         84        2433.28  3  2  1        321   \n","1  ...         81.0      158         84        2433.28  3  2  1        321   \n","2  ...         81.0      158         84        2433.28  3  2  1        321   \n","3  ...        100.8      158         84        2433.28  3  2  1        321   \n","4  ...         30.0      158         84        2433.28  3  2  1        321   \n","\n","  RFMScore  CustomerGroup  \n","0        6         Bronze  \n","1        6         Bronze  \n","2        6         Bronze  \n","3        6         Bronze  \n","4        6         Bronze  \n","\n","[5 rows x 21 columns]"]},"metadata":{},"execution_count":48}],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":394},"id":"4ceJiIAjQwXs","executionInfo":{"status":"ok","timestamp":1628904369073,"user_tz":-480,"elapsed":6,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"5fc8112d-ad4a-4482-a6fd-dcc023b66cd3"}},{"cell_type":"code","execution_count":49,"source":["# final_df.to_csv(\"customergroup_details.csv\",index=False)"],"outputs":[],"metadata":{"id":"yWUVCVsBWp2N","executionInfo":{"status":"ok","timestamp":1628904369073,"user_tz":-480,"elapsed":4,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":50,"source":["from wordcloud import WordCloud"],"outputs":[],"metadata":{}},{"cell_type":"code","execution_count":51,"source":["def group_word_cloud(labels):\r\n","  \"\"\"input group labels and return the keyword of products that group purchased\r\n","  \"\"\"\r\n","  print(f\"These are the keywords of the products purchased by *Group {labels}*:\")\r\n","  # getting a list of the descriptions in terms of words\r\n","  text = final_df[final_df[\"CustomerGroup\"] == labels].Description\r\n","  re_text = \" \".join(text.astype(\"string\"))\r\n","  \r\n","  # wordcloud part\r\n","  wordcloud = WordCloud(font_path=\"Lato-Bold.ttf\", width=800, height=400, background_color=\"white\").generate(re_text)\r\n","  \r\n","  # Display the images\r\n","  plt.imshow(wordcloud, interpolation='bilinear')\r\n","  plt.axis(\"off\")\r\n","  plt.show()  \r\n","\r\n","  # wordcloud.to_file((f\"{labels}.png\"))"],"outputs":[],"metadata":{"id":"WE71YMUOmd78","executionInfo":{"status":"ok","timestamp":1628904890376,"user_tz":-480,"elapsed":220,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}}}},{"cell_type":"code","execution_count":52,"source":["# group_word_cloud(\"Gold\")"],"outputs":[],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":327},"id":"ZzyBEO41RHra","executionInfo":{"status":"ok","timestamp":1628904896877,"user_tz":-480,"elapsed":5270,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"f80b6edc-ba22-44d4-db9a-51585989eaa0"}},{"cell_type":"code","execution_count":53,"source":["# group_word_cloud(\"Sliver\")"],"outputs":[],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":327},"id":"adxnvJM9R7Pm","executionInfo":{"status":"ok","timestamp":1628904905973,"user_tz":-480,"elapsed":9105,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"8c6eda71-3b3b-44c4-c974-b9b5917d1b7f"}},{"cell_type":"code","execution_count":54,"source":["# group_word_cloud(\"Bronze\")"],"outputs":[],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":327},"id":"IwsDIf63R7Lq","executionInfo":{"status":"ok","timestamp":1628904908083,"user_tz":-480,"elapsed":2114,"user":{"displayName":"Nicole TANG","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhwjTJBhn701pOplDcqW8HxCIcThoSKun607L5QwA=s64","userId":"11877175470727402703"}},"outputId":"64092642-5627-4b2b-9d37-adfeca393817"}},{"cell_type":"code","execution_count":null,"source":[],"outputs":[],"metadata":{}}]}