{ "cells": [ { "cell_type": "code", "execution_count": 3, "id": "e22ae889", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt \n", "import mlxtend\n", "from mlxtend.frequent_patterns import apriori, association_rules\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "94315aed", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\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",
" \n",
" <tr style="text-align: right;">\n",
" \n",
" Member_number\n",
" Date\n",
" itemDescription\n",
" \n",
" \n",
" \n",
" \n",
" 0\n",
" 1808\n",
" 21-07-2015\n",
" tropical fruit\n",
" \n",
" \n",
" 1\n",
" 2552\n",
" 05-01-2015\n",
" whole milk\n",
" \n",
" \n",
" 2\n",
" 2300\n",
" 19-09-2015\n",
" pip fruit\n",
" \n",
" \n",
" 3\n",
" 1187\n",
" 12-12-2015\n",
" other vegetables\n",
" \n",
" \n",
" 4\n",
" 3037\n",
" 01-02-2015\n",
" whole milk\n",
" \n",
" \n",
"\n",
"
"
],
"text/plain": [
" Member_number Date itemDescription\n",
"0 1808 21-07-2015 tropical fruit\n",
"1 2552 05-01-2015 whole milk\n",
"2 2300 19-09-2015 pip fruit\n",
"3 1187 12-12-2015 other vegetables\n",
"4 3037 01-02-2015 whole milk"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv("Market Basket Analysis - Groceries_dataset (1).csv")\n",
"\n",
"df.head()\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "38f87b15",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\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",
" \n",
" <tr style="text-align: right;">\n",
" \n",
" Member_number\n",
" Date\n",
" itemDescription_Instant food products\n",
" itemDescription_UHT-milk\n",
" itemDescription_abrasive cleaner\n",
" itemDescription_artif. sweetener\n",
" itemDescription_baby cosmetics\n",
" itemDescription_bags\n",
" itemDescription_baking powder\n",
" itemDescription_bathroom cleaner\n",
" ...\n",
" itemDescription_turkey\n",
" itemDescription_vinegar\n",
" itemDescription_waffles\n",
" itemDescription_whipped/sour cream\n",
" itemDescription_whisky\n",
" itemDescription_white bread\n",
" itemDescription_white wine\n",
" itemDescription_whole milk\n",
" itemDescription_yogurt\n",
" itemDescription_zwieback\n",
" \n",
" \n",
" \n",
" \n",
" 0\n",
" 1808\n",
" 21-07-2015\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" ...\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" \n",
" \n",
" 1\n",
" 2552\n",
" 05-01-2015\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" ...\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" True\n",
" False\n",
" False\n",
" \n",
" \n",
" 2\n",
" 2300\n",
" 19-09-2015\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" ...\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" \n",
" \n",
" 3\n",
" 1187\n",
" 12-12-2015\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" ...\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" \n",
" \n",
" 4\n",
" 3037\n",
" 01-02-2015\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" ...\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" False\n",
" True\n",
" False\n",
" False\n",
" \n",
" \n",
"\n",
"
"
],
"text/plain": [
" Member_number Date itemDescription_Instant food products \\n",
"0 1808 21-07-2015 False \n",
"1 2552 05-01-2015 False \n",
"2 2300 19-09-2015 False \n",
"3 1187 12-12-2015 False \n",
"4 3037 01-02-2015 False \n",
"\n",
" itemDescription_UHT-milk itemDescription_abrasive cleaner \\n",
"0 False False \n",
"1 False False \n",
"2 False False \n",
"3 False False \n",
"4 False False \n",
"\n",
" itemDescription_artif. sweetener itemDescription_baby cosmetics \\n",
"0 False False \n",
"1 False False \n",
"2 False False \n",
"3 False False \n",
"4 False False \n",
"\n",
" itemDescription_bags itemDescription_baking powder \\n",
"0 False False \n",
"1 False False \n",
"2 False False \n",
"3 False False \n",
"4 False False \n",
"\n",
" itemDescription_bathroom cleaner ... itemDescription_turkey \\n",
"0 False ... False \n",
"1 False ... False \n",
"2 False ... False \n",
"3 False ... False \n",
"4 False ... False \n",
"\n",
" itemDescription_vinegar itemDescription_waffles \\n",
"0 False False \n",
"1 False False \n",
"2 False False \n",
"3 False False \n",
"4 False False \n",
"\n",
" itemDescription_whipped/sour cream itemDescription_whisky \\n",
"0 False False \n",
"1 False False \n",
"2 False False \n",
"3 False False \n",
"4 False False \n",
"\n",
" itemDescription_white bread itemDescription_white wine \\n",
"0 False False \n",
"1 False False \n",
"2 False False \n",
"3 False False \n",
"4 False False \n",
"\n",
" itemDescription_whole milk itemDescription_yogurt \\n",
"0 False False \n",
"1 True False \n",
"2 False False \n",
"3 False False \n",
"4 True False \n",
"\n",
" itemDescription_zwieback \n",
"0 False \n",
"1 False \n",
"2 False \n",
"3 False \n",
"4 False \n",
"\n",
"[5 rows x 169 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_encoded = pd.get_dummies(df, columns=['itemDescription'])\n",
"df_encoded.head()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "b45fe653",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Member_number 0\n",
"Date 0\n",
"itemDescription 0\n",
"dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.isnull().sum().sort_values(ascending = False)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "0e00ccde",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 38765 entries, 0 to 38764\n",
"Data columns (total 4 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Member_number 38765 non-null int64 \n",
" 1 Date 38765 non-null object \n",
" 2 itemDescription 38765 non-null object \n",
" 3 date 38765 non-null datetime64[ns]\n",
"dtypes: datetime64ns, int64(1), object(2)\n",
"memory usage: 1.2+ MB\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\Users\Christabel Ehiagwina\AppData\Local\Temp\ipykernel_16892\2847483607.py:1: UserWarning: Parsing dates in %d-%m-%Y format when dayfirst=False (the default) was specified. Pass 5 rows × 169 columns
\n", "dayfirst=True or specify a format to silence this warning.\n",
" df["date"] = pd.to_datetime(df["Date"])\n"
]
}
],
"source": [
"df["date"] = pd.to_datetime(df["Date"])\n",
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "c5f1412c",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\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",
" \n",
" <tr style="text-align: right;">\n",
" \n",
" Member_number\n",
" Date\n",
" itemDescription\n",
" date\n",
" \n",
" \n",
" \n",
" \n",
" 0\n",
" 1808\n",
" 21-07-2015\n",
" tropical fruit\n",
" 2015-07-21\n",
" \n",
" \n",
" 1\n",
" 2552\n",
" 05-01-2015\n",
" whole milk\n",
" 2015-01-05\n",
" \n",
" \n",
" 2\n",
" 2300\n",
" 19-09-2015\n",
" pip fruit\n",
" 2015-09-19\n",
" \n",
" \n",
" 3\n",
" 1187\n",
" 12-12-2015\n",
" other vegetables\n",
" 2015-12-12\n",
" \n",
" \n",
" 4\n",
" 3037\n",
" 01-02-2015\n",
" whole milk\n",
" 2015-02-01\n",
" \n",
" \n",
"\n",
"
"
],
"text/plain": [
" Member_number Date itemDescription date\n",
"0 1808 21-07-2015 tropical fruit 2015-07-21\n",
"1 2552 05-01-2015 whole milk 2015-01-05\n",
"2 2300 19-09-2015 pip fruit 2015-09-19\n",
"3 1187 12-12-2015 other vegetables 2015-12-12\n",
"4 3037 01-02-2015 whole milk 2015-02-01"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "595bd8c0",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 1600x900 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"item_distr = df.groupby(by = 'itemDescription').size().reset_index(name='Frequency').sort_values(by = 'Frequency', ascending = False).head(10)\n",
"\n",
"bars = item_distr["itemDescription"]\n",
"height = item_distr["Frequency"]\n",
"x_pos = np.arange(len(bars))\n",
"\n",
"plt.figure(figsize=(16,9))\n",
"\n",
"plt.bar(x_pos, height, color=(0.2,0.3,0.5,0.5))\n",
"\n",
"plt.title("top 10 sold item")\n",
"plt.xlabel("item names")\n",
"plt.ylabel("number of quantity sold")\n",
"\n",
"plt.xticks(x_pos, bars)\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "9fea760b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\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",
" \n",
" <tr style="text-align: right;">\n",
" \n",
" Member_number\n",
" itemDescription\n",
" date\n",
" \n",
" \n",
" Date\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 21-07-2015\n",
" 1808\n",
" tropical fruit\n",
" 2015-07-21\n",
" \n",
" \n",
" 05-01-2015\n",
" 2552\n",
" whole milk\n",
" 2015-01-05\n",
" \n",
" \n",
" 19-09-2015\n",
" 2300\n",
" pip fruit\n",
" 2015-09-19\n",
" \n",
" \n",
" 12-12-2015\n",
" 1187\n",
" other vegetables\n",
" 2015-12-12\n",
" \n",
" \n",
" 01-02-2015\n",
" 3037\n",
" whole milk\n",
" 2015-02-01\n",
" \n",
" \n",
" ...\n",
" ...\n",
" ...\n",
" ...\n",
" \n",
" \n",
" 08-10-2014\n",
" 4471\n",
" sliced cheese\n",
" 2014-10-08\n",
" \n",
" \n",
" 23-02-2014\n",
" 2022\n",
" candy\n",
" 2014-02-23\n",
" \n",
" \n",
" 16-04-2014\n",
" 1097\n",
" cake bar\n",
" 2014-04-16\n",
" \n",
" \n",
" 03-12-2014\n",
" 1510\n",
" fruit/vegetable juice\n",
" 2014-12-03\n",
" \n",
" \n",
" 26-12-2014\n",
" 1521\n",
" cat food\n",
" 2014-12-26\n",
" \n",
" \n",
"\n",
"
"
],
"text/plain": [
" Member_number itemDescription date\n",
"Date \n",
"21-07-2015 1808 tropical fruit 2015-07-21\n",
"05-01-2015 2552 whole milk 2015-01-05\n",
"19-09-2015 2300 pip fruit 2015-09-19\n",
"12-12-2015 1187 other vegetables 2015-12-12\n",
"01-02-2015 3037 whole milk 2015-02-01\n",
"... ... ... ...\n",
"08-10-2014 4471 sliced cheese 2014-10-08\n",
"23-02-2014 2022 candy 2014-02-23\n",
"16-04-2014 1097 cake bar 2014-04-16\n",
"03-12-2014 1510 fruit/vegetable juice 2014-12-03\n",
"26-12-2014 1521 cat food 2014-12-26\n",
"\n",
"[38765 rows x 3 columns]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_date = df.set_index(['Date'])\n",
"df_date"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "4b0f6430",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"[Text(0.5, 0, 'Date'), Text(0, 0.5, 'Number of Items Sold')]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 2000x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_date["date"] = pd.to_datetime(df_date["date"])\n",
"\n",
"df_date.set_index("date", inplace=True)\n",
"\n",
"\n",
"monthly_count = df_date.resample("M")["itemDescription"].count()\n",
"monthly_count.plot(figsize=(20, 8), grid=True, title="Number of Items Sold by Month").set(xlabel="Date", ylabel="Number of Items Sold")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "e3de2fdb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Member_number Date itemDescription\n",
"0 1808 21-07-2015 tropical fruit\n",
"1 2552 05-01-2015 whole milk\n",
"2 2300 19-09-2015 pip fruit\n",
"3 1187 12-12-2015 other vegetables\n",
"4 3037 01-02-2015 whole milk\n"
]
}
],
"source": [
"df.columns = df.columns.str.strip()\n",
"\n",
"selected_variables = ['Member_number', 'Date', 'itemDescription']\n",
"df_selected = df[selected_variables]\n",
"\n",
"print(df_selected.head())"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "0a0f6ee6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Member_number itemDescription\n",
"0 1000 [soda, canned beer, sausage, sausage, whole mi...\n",
"1 1001 [frankfurter, frankfurter, beef, sausage, whol...\n",
"2 1002 [tropical fruit, butter milk, butter, frozen v...\n",
"3 1003 [sausage, root vegetables, rolls/buns, deterge...\n",
"4 1004 [other vegetables, pip fruit, root vegetables,...\n"
]
}
],
"source": [
"df_combined = df.groupby('Member_number')['itemDescription'].agg(list).reset_index()\n",
"\n",
"print(df_combined.head())"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f9b3a54a",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6f696a92",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "3da6f625",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "99bebf0f",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "cffc21dc",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
38765 rows × 3 columns
\n", "