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Created December 1, 2023 16:16
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e-commerce.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/rohzzn/7cb592fa1327edbfac60a9b103d5925d/e-commerce.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"id": "6a7d5404",
"metadata": {
"id": "6a7d5404"
},
"source": [
"#You have been given the role of a business analyst for an E-Commerce company and have been asked to prepare a basic report on the data. Follow the steps below for preparation of the report.\n",
"\n",
"Before you start analysing the data, it is always a good practice to see the size of the data, its features and feature types. If the data set is big, it is not possible to print out all the records.\n",
" \n",
"#### Note: Use the markdown feature of Python to explain your answer."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f6f973a2",
"metadata": {
"id": "f6f973a2"
},
"outputs": [],
"source": [
"## Load the necessary libraries. Import and load the dataset with a name ECom_Data ."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "eec2a3b5",
"metadata": {
"scrolled": false,
"id": "eec2a3b5"
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"pd.options.display.max_rows = 10"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8e1fcc97",
"metadata": {
"scrolled": true,
"id": "8e1fcc97"
},
"outputs": [],
"source": [
"# Get the Data\n",
"\n",
"ECom_Data=pd.read_csv(\"E-Commerce.csv\")\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "2cf5f20f",
"metadata": {
"id": "2cf5f20f"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" We have read the data and stored the data in \"ECom_Data\" variable </font>"
]
},
{
"cell_type": "markdown",
"id": "a0a4f84a",
"metadata": {
"id": "a0a4f84a"
},
"source": [
"## Q 1.\tTo get familiar with the data\n",
"## a)\tPrint out the first 10 and the last 10 records of the data. (2 marks)\n",
"## b)\tHow many rows and columns are present in the dataset? Use any two different methods to extract this information. (2 + 2 + 2 marks)\n",
"## c)\tHow many object data types are there? (1 mark)\n",
"## d)\tIs there any Boolean data type? (1 mark)\n",
"#### Note: Use the markdown feature of Python to explain your answer.\n"
]
},
{
"cell_type": "markdown",
"id": "0ba43d74",
"metadata": {
"id": "0ba43d74"
},
"source": [
"#### Ans 1 a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6684f5a1",
"metadata": {
"scrolled": true,
"id": "6684f5a1",
"outputId": "46ad2bc7-745f-4d85-d7a4-8f95f1e0f247"
},
"outputs": [
{
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Customer_uniq_id</th>\n",
" <th>Region</th>\n",
" <th>Order_Date</th>\n",
" <th>Expected_Delivery_Date</th>\n",
" <th>Delivered_Date</th>\n",
" <th>product_name</th>\n",
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" <th>retail_price</th>\n",
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" <th>Brand</th>\n",
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" </tr>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>e71017e224688489edfe856f2308806d</td>\n",
" <td>East</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Indcrown Net Embroidered Semi-stitched Lehenga...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEJX2NHNKCYHKA</td>\n",
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" <td>699</td>\n",
" <td>4.0</td>\n",
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" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Fabric\", \"...</td>\n",
" <td>Key Features of Indcrown Net Embroidered Semi-...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>6286847ee2da18f587503db49511c539</td>\n",
" <td>East</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Shopmania Music Band A5 Notebook Spiral Bound</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Diaries &amp; Notebooks</td>\n",
" <td>Notebooks</td>\n",
" <td>Designer</td>\n",
" <td>DIAEJ6Z8BEDTGGYY</td>\n",
" <td>499</td>\n",
" <td>275</td>\n",
" <td>1.0</td>\n",
" <td>SHOPMANIA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ruling\", \"...</td>\n",
" <td>Specifications of Shopmania Music Band A5 Note...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0686fec9b70e5039583a38119ca0c835</td>\n",
" <td>West</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Shopmania Music Band A5 Notebook Spiral Bound</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Diaries &amp; Notebooks</td>\n",
" <td>Notebooks</td>\n",
" <td>Designer</td>\n",
" <td>DIAEJ6Z8KQFWDEGH</td>\n",
" <td>499</td>\n",
" <td>275</td>\n",
" <td>2.0</td>\n",
" <td>SHOPMANIA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ruling\", \"...</td>\n",
" <td>Specifications of Shopmania Music Band A5 Note...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ea2406dc597bee2abb6b867fa668501f</td>\n",
" <td>West</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Tiara Diaries 2016-2017 Designer LA Kaarta \"TA...</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Diaries &amp; Notebooks</td>\n",
" <td>Notebooks</td>\n",
" <td>Designer</td>\n",
" <td>DIAEJ8FGHZ3K86JU</td>\n",
" <td>1000</td>\n",
" <td>837</td>\n",
" <td>3.0</td>\n",
" <td>TIARA DIARIES</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ruling\", \"...</td>\n",
" <td>Specifications of Tiara Diaries 2016-2017 Desi...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5935ed077915347dc695744df68c565c</td>\n",
" <td>East</td>\n",
" <td>03-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>KAJCI Embroidered Women's Waistcoat</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Formal Wear</td>\n",
" <td>Waistcoats</td>\n",
" <td>WSCEG2FYDYFDSVZ6</td>\n",
" <td>1200</td>\n",
" <td>699</td>\n",
" <td>5.0</td>\n",
" <td>KAJCI</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pattern\", ...</td>\n",
" <td>Specifications of KAJCI Embroidered Women's Wa...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>89fcdddaad50084e395d0928a7426afe</td>\n",
" <td>East</td>\n",
" <td>03-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>Packman 8 x 10 inches Security Bags Without PO...</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Office Supplies</td>\n",
" <td>Packaging Security Bags</td>\n",
" <td>Packman Packaging Security Bags</td>\n",
" <td>PKBEGBTRKKHU26YQ</td>\n",
" <td>350</td>\n",
" <td>298</td>\n",
" <td>4.0</td>\n",
" <td>PACKMAN</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Bubble Wra...</td>\n",
" <td>Key Features of Packman 8 x 10 inches Security...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>b9b183aa18d3a721d2ac23e7184525b0</td>\n",
" <td>East</td>\n",
" <td>03-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>Pick Pocket Embroidered Women's Waistcoat</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Formal Wear</td>\n",
" <td>Waistcoats</td>\n",
" <td>WSCEFUV4TVWT73ZB</td>\n",
" <td>899</td>\n",
" <td>899</td>\n",
" <td>1.0</td>\n",
" <td>PICK POCKET</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Pattern\", ...</td>\n",
" <td>Specifications of Pick Pocket Embroidered Wome...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>dee64864c0419bec80fbbb94d19bc40d</td>\n",
" <td>East</td>\n",
" <td>03-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>Angelfish Silk Potali Potli</td>\n",
" <td>Bags, Wallets &amp; Belts</td>\n",
" <td>Bags</td>\n",
" <td>Pouches and Potlis</td>\n",
" <td>Angelfish Pouches and Potlis</td>\n",
" <td>PPSEGFYAGD8FYUXV</td>\n",
" <td>999</td>\n",
" <td>399</td>\n",
" <td>4.0</td>\n",
" <td>ANGELFISH</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Closure\", ...</td>\n",
" <td>Angelfish Silk Potali Potli (Multicolor) Price...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>595f55f2c1293f07ea9ec9fa2bb39f46</td>\n",
" <td>East</td>\n",
" <td>03-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>Oye Boy's Dungaree</td>\n",
" <td>Clothing</td>\n",
" <td>Kids' Clothing</td>\n",
" <td>Boys Wear</td>\n",
" <td>Dungarees &amp; Jumpsuits</td>\n",
" <td>DRPEF2XSFBAP4SUZ</td>\n",
" <td>899</td>\n",
" <td>764</td>\n",
" <td>1.0</td>\n",
" <td>OYE</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Number of ...</td>\n",
" <td>Specifications of Oye Boy's Dungaree Top Detai...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>547b6585272473ae006bcfbdb47b6ae0</td>\n",
" <td>West</td>\n",
" <td>26-08-2021</td>\n",
" <td>27-08-2021</td>\n",
" <td>27-08-2021</td>\n",
" <td>Nuride Canvas Shoes</td>\n",
" <td>Footwear</td>\n",
" <td>Women's Footwear</td>\n",
" <td>Casual Shoes</td>\n",
" <td>Canvas</td>\n",
" <td>SHOEGVQCT2ZSGUHY</td>\n",
" <td>1999</td>\n",
" <td>1349</td>\n",
" <td>2.0</td>\n",
" <td>NURIDE</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Occasion\",...</td>\n",
" <td>Key Features of Nuride Canvas Shoes Material: ...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer_uniq_id Region Order_Date Expected_Delivery_Date \\\n",
"0 e71017e224688489edfe856f2308806d East 24-10-2021 25-10-2021 \n",
"1 6286847ee2da18f587503db49511c539 East 24-10-2021 25-10-2021 \n",
"2 0686fec9b70e5039583a38119ca0c835 West 24-10-2021 25-10-2021 \n",
"3 ea2406dc597bee2abb6b867fa668501f West 24-10-2021 25-10-2021 \n",
"4 5935ed077915347dc695744df68c565c East 03-09-2021 04-09-2021 \n",
"5 89fcdddaad50084e395d0928a7426afe East 03-09-2021 04-09-2021 \n",
"6 b9b183aa18d3a721d2ac23e7184525b0 East 03-09-2021 04-09-2021 \n",
"7 dee64864c0419bec80fbbb94d19bc40d East 03-09-2021 04-09-2021 \n",
"8 595f55f2c1293f07ea9ec9fa2bb39f46 East 03-09-2021 04-09-2021 \n",
"9 547b6585272473ae006bcfbdb47b6ae0 West 26-08-2021 27-08-2021 \n",
"\n",
" Delivered_Date product_name \\\n",
"0 25-10-2021 Indcrown Net Embroidered Semi-stitched Lehenga... \n",
"1 25-10-2021 Shopmania Music Band A5 Notebook Spiral Bound \n",
"2 25-10-2021 Shopmania Music Band A5 Notebook Spiral Bound \n",
"3 25-10-2021 Tiara Diaries 2016-2017 Designer LA Kaarta \"TA... \n",
"4 04-09-2021 KAJCI Embroidered Women's Waistcoat \n",
"5 04-09-2021 Packman 8 x 10 inches Security Bags Without PO... \n",
"6 04-09-2021 Pick Pocket Embroidered Women's Waistcoat \n",
"7 04-09-2021 Angelfish Silk Potali Potli \n",
"8 04-09-2021 Oye Boy's Dungaree \n",
"9 27-08-2021 Nuride Canvas Shoes \n",
"\n",
" product_main_category product_subcategory product_category_filter \\\n",
"0 Clothing Women's Clothing Ethnic Wear \n",
"1 Pens & Stationery Diaries & Notebooks Notebooks \n",
"2 Pens & Stationery Diaries & Notebooks Notebooks \n",
"3 Pens & Stationery Diaries & Notebooks Notebooks \n",
"4 Clothing Women's Clothing Formal Wear \n",
"5 Pens & Stationery Office Supplies Packaging Security Bags \n",
"6 Clothing Women's Clothing Formal Wear \n",
"7 Bags, Wallets & Belts Bags Pouches and Potlis \n",
"8 Clothing Kids' Clothing Boys Wear \n",
"9 Footwear Women's Footwear Casual Shoes \n",
"\n",
" product_category_subfilter product_unique ID retail_price \\\n",
"0 Fabric FABEJX2NHNKCYHKA 999 \n",
"1 Designer DIAEJ6Z8BEDTGGYY 499 \n",
"2 Designer DIAEJ6Z8KQFWDEGH 499 \n",
"3 Designer DIAEJ8FGHZ3K86JU 1000 \n",
"4 Waistcoats WSCEG2FYDYFDSVZ6 1200 \n",
"5 Packman Packaging Security Bags PKBEGBTRKKHU26YQ 350 \n",
"6 Waistcoats WSCEFUV4TVWT73ZB 899 \n",
"7 Angelfish Pouches and Potlis PPSEGFYAGD8FYUXV 999 \n",
"8 Dungarees & Jumpsuits DRPEF2XSFBAP4SUZ 899 \n",
"9 Canvas SHOEGVQCT2ZSGUHY 1999 \n",
"\n",
" discounted_price product_rating Brand \\\n",
"0 699 4.0 INDCROWN \n",
"1 275 1.0 SHOPMANIA \n",
"2 275 2.0 SHOPMANIA \n",
"3 837 3.0 TIARA DIARIES \n",
"4 699 5.0 KAJCI \n",
"5 298 4.0 PACKMAN \n",
"6 899 1.0 PICK POCKET \n",
"7 399 4.0 ANGELFISH \n",
"8 764 1.0 OYE \n",
"9 1349 2.0 NURIDE \n",
"\n",
" product_specifications \\\n",
"0 {\"product_specification\"=>[{\"key\"=>\"Fabric\", \"... \n",
"1 {\"product_specification\"=>[{\"key\"=>\"Ruling\", \"... \n",
"2 {\"product_specification\"=>[{\"key\"=>\"Ruling\", \"... \n",
"3 {\"product_specification\"=>[{\"key\"=>\"Ruling\", \"... \n",
"4 {\"product_specification\"=>[{\"key\"=>\"Pattern\", ... \n",
"5 {\"product_specification\"=>[{\"key\"=>\"Bubble Wra... \n",
"6 {\"product_specification\"=>[{\"key\"=>\"Pattern\", ... \n",
"7 {\"product_specification\"=>[{\"key\"=>\"Closure\", ... \n",
"8 {\"product_specification\"=>[{\"key\"=>\"Number of ... \n",
"9 {\"product_specification\"=>[{\"key\"=>\"Occasion\",... \n",
"\n",
" description \n",
"0 Key Features of Indcrown Net Embroidered Semi-... \n",
"1 Specifications of Shopmania Music Band A5 Note... \n",
"2 Specifications of Shopmania Music Band A5 Note... \n",
"3 Specifications of Tiara Diaries 2016-2017 Desi... \n",
"4 Specifications of KAJCI Embroidered Women's Wa... \n",
"5 Key Features of Packman 8 x 10 inches Security... \n",
"6 Specifications of Pick Pocket Embroidered Wome... \n",
"7 Angelfish Silk Potali Potli (Multicolor) Price... \n",
"8 Specifications of Oye Boy's Dungaree Top Detai... \n",
"9 Key Features of Nuride Canvas Shoes Material: ... "
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Head() function is used to list out the first few elements of the dataset\n",
"\n",
"ECom_Data.head(10)"
]
},
{
"cell_type": "markdown",
"id": "e984fe0e",
"metadata": {
"id": "e984fe0e"
},
"source": [
"we got th result of first 10 rows of the Ecommerce dataset"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0ac3ef5d",
"metadata": {
"id": "0ac3ef5d",
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},
"outputs": [
{
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" <th>8896</th>\n",
" <td>4db03bc4ccbe216cf151b2f2b904ba3f</td>\n",
" <td>East</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Luca Fashion Girls Heels</td>\n",
" <td>Footwear</td>\n",
" <td>Kids' &amp; Infant Footwear</td>\n",
" <td>For Girls</td>\n",
" <td>Sandals</td>\n",
" <td>SNDEHG3DNVBFGAT5</td>\n",
" <td>999</td>\n",
" <td>499</td>\n",
" <td>4.0</td>\n",
" <td>LUCA FASHION</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Occasion\",...</td>\n",
" <td>Key Features of Luca Fashion Girls Heels Occas...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8897</th>\n",
" <td>4d4d6aeb13fa253499d0dd45a5abd87e</td>\n",
" <td>West</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Shoetopia Girls Sandals</td>\n",
" <td>Footwear</td>\n",
" <td>Kids' &amp; Infant Footwear</td>\n",
" <td>For Girls</td>\n",
" <td>Sandals</td>\n",
" <td>SNDEG7DRWSX8HFXZ</td>\n",
" <td>499</td>\n",
" <td>399</td>\n",
" <td>4.0</td>\n",
" <td>SHOETOPIA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
" <td>Key Features of Shoetopia Girls Sandals Flats ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8898</th>\n",
" <td>ea19e7ef703293d3f6c799ca9db4642d</td>\n",
" <td>West</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>SMART TRADERS Girls Sandals</td>\n",
" <td>Footwear</td>\n",
" <td>Kids' &amp; Infant Footwear</td>\n",
" <td>For Girls</td>\n",
" <td>Sandals</td>\n",
" <td>SNDEG7MZHHKZ58D2</td>\n",
" <td>999</td>\n",
" <td>499</td>\n",
" <td>5.0</td>\n",
" <td>SMART TRADERS</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Ideal For\"...</td>\n",
" <td>Key Features of SMART TRADERS Girls Sandals Oc...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8899</th>\n",
" <td>19a53a958992fb575acffb5d41e7ef9e</td>\n",
" <td>East</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Beanz Girls Flats</td>\n",
" <td>Footwear</td>\n",
" <td>Kids' &amp; Infant Footwear</td>\n",
" <td>For Girls</td>\n",
" <td>Sandals</td>\n",
" <td>SNDEG7DYVFWHZBC4</td>\n",
" <td>1299</td>\n",
" <td>1299</td>\n",
" <td>3.0</td>\n",
" <td>BEANZ</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Occasion\",...</td>\n",
" <td>Key Features of Beanz Girls Flats Occasion: Ca...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8900</th>\n",
" <td>09abab80c8dfdc6f268e0a6f05a0be11</td>\n",
" <td>North</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Nova KT 728S Electric Kettle</td>\n",
" <td>Home &amp; Kitchen</td>\n",
" <td>Kitchen Appliances</td>\n",
" <td>Electric Jug(heater)/Travel Kettles</td>\n",
" <td>Nova Electric Jug(heater)/Travel Kettles</td>\n",
" <td>EKTDG5C5QSADZZ8J</td>\n",
" <td>3195</td>\n",
" <td>699</td>\n",
" <td>3.6</td>\n",
" <td>NOVA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Brand\", \"v...</td>\n",
" <td>Specifications of Nova KT 728S Electric Kettle...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8901</th>\n",
" <td>90d30478255e23621e8929ed15c2f6e4</td>\n",
" <td>South</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Sinina Chanderi Embroidered Salwar Suit Dupatt...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEGGHHDFMY8BZU</td>\n",
" <td>2980</td>\n",
" <td>1490</td>\n",
" <td>3.0</td>\n",
" <td>SININA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Fabric\", \"...</td>\n",
" <td>Key Features of Sinina Chanderi Embroidered Sa...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8902</th>\n",
" <td>20a73e3f41490a73ceeba5f17658db8f</td>\n",
" <td>West</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Aarushi Fashion Chanderi Embroidered Salwar Su...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEG8GFDUWRSNU3</td>\n",
" <td>2600</td>\n",
" <td>1300</td>\n",
" <td>1.0</td>\n",
" <td>AARUSHI FASHION</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Fabric\", \"...</td>\n",
" <td>Key Features of Aarushi Fashion Chanderi Embro...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8903</th>\n",
" <td>5c1554cd45f9d538c2c6947dbdd59c75</td>\n",
" <td>East</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Ambika Lahenga Embroidered Lehenga, Choli and ...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Lehenga Cholis</td>\n",
" <td>LEHEGGEHYN4G2RPW</td>\n",
" <td>39992</td>\n",
" <td>24995</td>\n",
" <td>1.0</td>\n",
" <td>AMBIKA LAHENGA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Fabric\", \"...</td>\n",
" <td>Key Features of Ambika Lahenga Embroidered Leh...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8904</th>\n",
" <td>6b737a4deca1ed0e56c179e66036e994</td>\n",
" <td>West</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Sinina Chanderi Embroidered Salwar Suit Dupatt...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEGGHHGSVCHGFV</td>\n",
" <td>2000</td>\n",
" <td>1000</td>\n",
" <td>3.0</td>\n",
" <td>SININA</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Fabric\", \"...</td>\n",
" <td>Key Features of Sinina Chanderi Embroidered Sa...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8905</th>\n",
" <td>a5235ac28d3d5487f54025f9d6b57433</td>\n",
" <td>North</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Aarushi Fashion Silk Striped Salwar Suit Dupat...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEG8GYDAABECZH</td>\n",
" <td>2800</td>\n",
" <td>1350</td>\n",
" <td>4.0</td>\n",
" <td>AARUSHI FASHION</td>\n",
" <td>{\"product_specification\"=&gt;[{\"key\"=&gt;\"Fabric\", \"...</td>\n",
" <td>Key Features of Aarushi Fashion Silk Striped S...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer_uniq_id Region Order_Date \\\n",
"8896 4db03bc4ccbe216cf151b2f2b904ba3f East 01-12-2020 \n",
"8897 4d4d6aeb13fa253499d0dd45a5abd87e West 01-12-2020 \n",
"8898 ea19e7ef703293d3f6c799ca9db4642d West 01-12-2020 \n",
"8899 19a53a958992fb575acffb5d41e7ef9e East 01-12-2020 \n",
"8900 09abab80c8dfdc6f268e0a6f05a0be11 North 01-12-2020 \n",
"8901 90d30478255e23621e8929ed15c2f6e4 South 01-12-2020 \n",
"8902 20a73e3f41490a73ceeba5f17658db8f West 01-12-2020 \n",
"8903 5c1554cd45f9d538c2c6947dbdd59c75 East 01-12-2020 \n",
"8904 6b737a4deca1ed0e56c179e66036e994 West 01-12-2020 \n",
"8905 a5235ac28d3d5487f54025f9d6b57433 North 01-12-2020 \n",
"\n",
" Expected_Delivery_Date Delivered_Date \\\n",
"8896 04-12-2020 04-12-2020 \n",
"8897 04-12-2020 04-12-2020 \n",
"8898 04-12-2020 04-12-2020 \n",
"8899 04-12-2020 04-12-2020 \n",
"8900 04-12-2020 04-12-2020 \n",
"8901 04-12-2020 04-12-2020 \n",
"8902 04-12-2020 04-12-2020 \n",
"8903 04-12-2020 04-12-2020 \n",
"8904 04-12-2020 04-12-2020 \n",
"8905 04-12-2020 04-12-2020 \n",
"\n",
" product_name product_main_category \\\n",
"8896 Luca Fashion Girls Heels Footwear \n",
"8897 Shoetopia Girls Sandals Footwear \n",
"8898 SMART TRADERS Girls Sandals Footwear \n",
"8899 Beanz Girls Flats Footwear \n",
"8900 Nova KT 728S Electric Kettle Home & Kitchen \n",
"8901 Sinina Chanderi Embroidered Salwar Suit Dupatt... Clothing \n",
"8902 Aarushi Fashion Chanderi Embroidered Salwar Su... Clothing \n",
"8903 Ambika Lahenga Embroidered Lehenga, Choli and ... Clothing \n",
"8904 Sinina Chanderi Embroidered Salwar Suit Dupatt... Clothing \n",
"8905 Aarushi Fashion Silk Striped Salwar Suit Dupat... Clothing \n",
"\n",
" product_subcategory product_category_filter \\\n",
"8896 Kids' & Infant Footwear For Girls \n",
"8897 Kids' & Infant Footwear For Girls \n",
"8898 Kids' & Infant Footwear For Girls \n",
"8899 Kids' & Infant Footwear For Girls \n",
"8900 Kitchen Appliances Electric Jug(heater)/Travel Kettles \n",
"8901 Women's Clothing Ethnic Wear \n",
"8902 Women's Clothing Ethnic Wear \n",
"8903 Women's Clothing Ethnic Wear \n",
"8904 Women's Clothing Ethnic Wear \n",
"8905 Women's Clothing Ethnic Wear \n",
"\n",
" product_category_subfilter product_unique ID \\\n",
"8896 Sandals SNDEHG3DNVBFGAT5 \n",
"8897 Sandals SNDEG7DRWSX8HFXZ \n",
"8898 Sandals SNDEG7MZHHKZ58D2 \n",
"8899 Sandals SNDEG7DYVFWHZBC4 \n",
"8900 Nova Electric Jug(heater)/Travel Kettles EKTDG5C5QSADZZ8J \n",
"8901 Fabric FABEGGHHDFMY8BZU \n",
"8902 Fabric FABEG8GFDUWRSNU3 \n",
"8903 Lehenga Cholis LEHEGGEHYN4G2RPW \n",
"8904 Fabric FABEGGHHGSVCHGFV \n",
"8905 Fabric FABEG8GYDAABECZH \n",
"\n",
" retail_price discounted_price product_rating Brand \\\n",
"8896 999 499 4.0 LUCA FASHION \n",
"8897 499 399 4.0 SHOETOPIA \n",
"8898 999 499 5.0 SMART TRADERS \n",
"8899 1299 1299 3.0 BEANZ \n",
"8900 3195 699 3.6 NOVA \n",
"8901 2980 1490 3.0 SININA \n",
"8902 2600 1300 1.0 AARUSHI FASHION \n",
"8903 39992 24995 1.0 AMBIKA LAHENGA \n",
"8904 2000 1000 3.0 SININA \n",
"8905 2800 1350 4.0 AARUSHI FASHION \n",
"\n",
" product_specifications \\\n",
"8896 {\"product_specification\"=>[{\"key\"=>\"Occasion\",... \n",
"8897 {\"product_specification\"=>[{\"key\"=>\"Ideal For\"... \n",
"8898 {\"product_specification\"=>[{\"key\"=>\"Ideal For\"... \n",
"8899 {\"product_specification\"=>[{\"key\"=>\"Occasion\",... \n",
"8900 {\"product_specification\"=>[{\"key\"=>\"Brand\", \"v... \n",
"8901 {\"product_specification\"=>[{\"key\"=>\"Fabric\", \"... \n",
"8902 {\"product_specification\"=>[{\"key\"=>\"Fabric\", \"... \n",
"8903 {\"product_specification\"=>[{\"key\"=>\"Fabric\", \"... \n",
"8904 {\"product_specification\"=>[{\"key\"=>\"Fabric\", \"... \n",
"8905 {\"product_specification\"=>[{\"key\"=>\"Fabric\", \"... \n",
"\n",
" description \n",
"8896 Key Features of Luca Fashion Girls Heels Occas... \n",
"8897 Key Features of Shoetopia Girls Sandals Flats ... \n",
"8898 Key Features of SMART TRADERS Girls Sandals Oc... \n",
"8899 Key Features of Beanz Girls Flats Occasion: Ca... \n",
"8900 Specifications of Nova KT 728S Electric Kettle... \n",
"8901 Key Features of Sinina Chanderi Embroidered Sa... \n",
"8902 Key Features of Aarushi Fashion Chanderi Embro... \n",
"8903 Key Features of Ambika Lahenga Embroidered Leh... \n",
"8904 Key Features of Sinina Chanderi Embroidered Sa... \n",
"8905 Key Features of Aarushi Fashion Silk Striped S... "
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Tail() function is used to list out the first few elements of the dataset\n",
"\n",
"ECom_Data.tail(10)"
]
},
{
"cell_type": "markdown",
"id": "5b278fa9",
"metadata": {
"id": "5b278fa9"
},
"source": [
"we got the result of the last 10 rows of the dataset"
]
},
{
"cell_type": "markdown",
"id": "48baeda6",
"metadata": {
"id": "48baeda6"
},
"source": [
"#### Ans 1 b)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "38ddefc6",
"metadata": {
"scrolled": true,
"id": "38ddefc6",
"outputId": "467bc23e-dd13-42cf-dda9-89acfe373973"
},
"outputs": [
{
"data": {
"text/plain": [
"(8906, 17)"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#shape attribute is used to return a tuple where the first element represents the number of rows and the second element represents the number of columns\n",
"\n",
"ECom_Data.shape\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "d441031d",
"metadata": {
"id": "d441031d"
},
"source": [
"from the output we know that there are 8906 rows and 17 columns in the dataset"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f224dac8",
"metadata": {
"id": "f224dac8",
"outputId": "b944d8df-9e4d-48df-a1f6-c63bd7ce651b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rows and cols are (8906,17)\n"
]
}
],
"source": [
"# another method is using the len() of axes\n",
"rows = len(ECom_Data.axes[0])\n",
"cols = len(ECom_Data.axes[1])\n",
"print(\"rows and cols are ({},{})\".format(rows,cols))"
]
},
{
"cell_type": "markdown",
"id": "dc0f4c79",
"metadata": {
"id": "dc0f4c79"
},
"source": [
"this is another method to get the shape of the dataset, here the output is much more detailed an clean"
]
},
{
"cell_type": "markdown",
"id": "6aaa54a0",
"metadata": {
"id": "6aaa54a0"
},
"source": [
"Ans 1 c)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "115627b2",
"metadata": {
"id": "115627b2",
"outputId": "4e2837ca-92c5-4b4e-94d0-6dd4eae5ceb3"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 8906 entries, 0 to 8905\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Customer_uniq_id 8906 non-null object \n",
" 1 Region 8906 non-null object \n",
" 2 Order_Date 8906 non-null object \n",
" 3 Expected_Delivery_Date 8906 non-null object \n",
" 4 Delivered_Date 8906 non-null object \n",
" 5 product_name 8906 non-null object \n",
" 6 product_main_category 8906 non-null object \n",
" 7 product_subcategory 8906 non-null object \n",
" 8 product_category_filter 8906 non-null object \n",
" 9 product_category_subfilter 8906 non-null object \n",
" 10 product_unique ID 8906 non-null object \n",
" 11 retail_price 8906 non-null int64 \n",
" 12 discounted_price 8906 non-null int64 \n",
" 13 product_rating 8906 non-null float64\n",
" 14 Brand 8906 non-null object \n",
" 15 product_specifications 8906 non-null object \n",
" 16 description 8906 non-null object \n",
"dtypes: float64(1), int64(2), object(14)\n",
"memory usage: 1.2+ MB\n"
]
}
],
"source": [
"#the info() method is used to get the different data types in a dataset\n",
"\n",
"ECom_Data.info()"
]
},
{
"cell_type": "markdown",
"id": "5ac7ad13",
"metadata": {
"id": "5ac7ad13"
},
"source": [
"there are 14 object datatypes , 2 int datatype and 1 float datatype"
]
},
{
"cell_type": "markdown",
"id": "5e63573c",
"metadata": {
"id": "5e63573c"
},
"source": [
"### Ans 1 d)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2b96d5be",
"metadata": {
"id": "2b96d5be",
"outputId": "3e9ac61c-6b86-4ada-b4ba-00b21a0d5d68"
},
"outputs": [
{
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"<p>8906 rows × 0 columns</p>\n",
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"text/plain": [
"Empty DataFrame\n",
"Columns: []\n",
"Index: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...]\n",
"\n",
"[8906 rows x 0 columns]"
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},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"ECom_Data.select_dtypes(include = \"bool\")\n",
"\n",
"# Since there are no columns in the dataset with boolean datatypes, there is no boolean datatype"
]
},
{
"cell_type": "markdown",
"id": "2ed2fc9d",
"metadata": {
"id": "2ed2fc9d"
},
"source": [
"there is no dtype called boolean in the dataset"
]
},
{
"cell_type": "markdown",
"id": "cc5d76f1",
"metadata": {
"id": "cc5d76f1"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" Once you are familiar with the data, you may decide that not all features are of use to you and you may want to delete the non-informative features (columns)</font>"
]
},
{
"cell_type": "markdown",
"id": "90db65ce",
"metadata": {
"id": "90db65ce"
},
"source": [
"## Q 2.\tEliminating the non-informative columns.\n",
"## a)\tDrop the columns product_specifications and description. (2 marks)\n",
"## b)\tWhich method or function is used to permanently delete the columns mentioned in part (a)? Write the code explicitly (2 marks)\n",
"### Note: Use the markdown feature of Python to explain your answer.\n"
]
},
{
"cell_type": "markdown",
"id": "e0e7e762",
"metadata": {
"id": "e0e7e762"
},
"source": [
"### Ans 2 a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "35ad0821",
"metadata": {
"id": "35ad0821",
"outputId": "cf75fc17-a9ff-4e43-841f-c4f9602f3343"
},
"outputs": [
{
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" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Customer_uniq_id</th>\n",
" <th>Region</th>\n",
" <th>Order_Date</th>\n",
" <th>Expected_Delivery_Date</th>\n",
" <th>Delivered_Date</th>\n",
" <th>product_name</th>\n",
" <th>product_main_category</th>\n",
" <th>product_subcategory</th>\n",
" <th>product_category_filter</th>\n",
" <th>product_category_subfilter</th>\n",
" <th>product_unique ID</th>\n",
" <th>retail_price</th>\n",
" <th>discounted_price</th>\n",
" <th>product_rating</th>\n",
" <th>Brand</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>e71017e224688489edfe856f2308806d</td>\n",
" <td>East</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Indcrown Net Embroidered Semi-stitched Lehenga...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEJX2NHNKCYHKA</td>\n",
" <td>999</td>\n",
" <td>699</td>\n",
" <td>4.0</td>\n",
" <td>INDCROWN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>6286847ee2da18f587503db49511c539</td>\n",
" <td>East</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Shopmania Music Band A5 Notebook Spiral Bound</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Diaries &amp; Notebooks</td>\n",
" <td>Notebooks</td>\n",
" <td>Designer</td>\n",
" <td>DIAEJ6Z8BEDTGGYY</td>\n",
" <td>499</td>\n",
" <td>275</td>\n",
" <td>1.0</td>\n",
" <td>SHOPMANIA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0686fec9b70e5039583a38119ca0c835</td>\n",
" <td>West</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Shopmania Music Band A5 Notebook Spiral Bound</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Diaries &amp; Notebooks</td>\n",
" <td>Notebooks</td>\n",
" <td>Designer</td>\n",
" <td>DIAEJ6Z8KQFWDEGH</td>\n",
" <td>499</td>\n",
" <td>275</td>\n",
" <td>2.0</td>\n",
" <td>SHOPMANIA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ea2406dc597bee2abb6b867fa668501f</td>\n",
" <td>West</td>\n",
" <td>24-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>25-10-2021</td>\n",
" <td>Tiara Diaries 2016-2017 Designer LA Kaarta \"TA...</td>\n",
" <td>Pens &amp; Stationery</td>\n",
" <td>Diaries &amp; Notebooks</td>\n",
" <td>Notebooks</td>\n",
" <td>Designer</td>\n",
" <td>DIAEJ8FGHZ3K86JU</td>\n",
" <td>1000</td>\n",
" <td>837</td>\n",
" <td>3.0</td>\n",
" <td>TIARA DIARIES</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5935ed077915347dc695744df68c565c</td>\n",
" <td>East</td>\n",
" <td>03-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>04-09-2021</td>\n",
" <td>KAJCI Embroidered Women's Waistcoat</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Formal Wear</td>\n",
" <td>Waistcoats</td>\n",
" <td>WSCEG2FYDYFDSVZ6</td>\n",
" <td>1200</td>\n",
" <td>699</td>\n",
" <td>5.0</td>\n",
" <td>KAJCI</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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8901</th>\n",
" <td>90d30478255e23621e8929ed15c2f6e4</td>\n",
" <td>South</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Sinina Chanderi Embroidered Salwar Suit Dupatt...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEGGHHDFMY8BZU</td>\n",
" <td>2980</td>\n",
" <td>1490</td>\n",
" <td>3.0</td>\n",
" <td>SININA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8902</th>\n",
" <td>20a73e3f41490a73ceeba5f17658db8f</td>\n",
" <td>West</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Aarushi Fashion Chanderi Embroidered Salwar Su...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEG8GFDUWRSNU3</td>\n",
" <td>2600</td>\n",
" <td>1300</td>\n",
" <td>1.0</td>\n",
" <td>AARUSHI FASHION</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8903</th>\n",
" <td>5c1554cd45f9d538c2c6947dbdd59c75</td>\n",
" <td>East</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Ambika Lahenga Embroidered Lehenga, Choli and ...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Lehenga Cholis</td>\n",
" <td>LEHEGGEHYN4G2RPW</td>\n",
" <td>39992</td>\n",
" <td>24995</td>\n",
" <td>1.0</td>\n",
" <td>AMBIKA LAHENGA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8904</th>\n",
" <td>6b737a4deca1ed0e56c179e66036e994</td>\n",
" <td>West</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Sinina Chanderi Embroidered Salwar Suit Dupatt...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEGGHHGSVCHGFV</td>\n",
" <td>2000</td>\n",
" <td>1000</td>\n",
" <td>3.0</td>\n",
" <td>SININA</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8905</th>\n",
" <td>a5235ac28d3d5487f54025f9d6b57433</td>\n",
" <td>North</td>\n",
" <td>01-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>04-12-2020</td>\n",
" <td>Aarushi Fashion Silk Striped Salwar Suit Dupat...</td>\n",
" <td>Clothing</td>\n",
" <td>Women's Clothing</td>\n",
" <td>Ethnic Wear</td>\n",
" <td>Fabric</td>\n",
" <td>FABEG8GYDAABECZH</td>\n",
" <td>2800</td>\n",
" <td>1350</td>\n",
" <td>4.0</td>\n",
" <td>AARUSHI FASHION</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8906 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" Customer_uniq_id Region Order_Date \\\n",
"0 e71017e224688489edfe856f2308806d East 24-10-2021 \n",
"1 6286847ee2da18f587503db49511c539 East 24-10-2021 \n",
"2 0686fec9b70e5039583a38119ca0c835 West 24-10-2021 \n",
"3 ea2406dc597bee2abb6b867fa668501f West 24-10-2021 \n",
"4 5935ed077915347dc695744df68c565c East 03-09-2021 \n",
"... ... ... ... \n",
"8901 90d30478255e23621e8929ed15c2f6e4 South 01-12-2020 \n",
"8902 20a73e3f41490a73ceeba5f17658db8f West 01-12-2020 \n",
"8903 5c1554cd45f9d538c2c6947dbdd59c75 East 01-12-2020 \n",
"8904 6b737a4deca1ed0e56c179e66036e994 West 01-12-2020 \n",
"8905 a5235ac28d3d5487f54025f9d6b57433 North 01-12-2020 \n",
"\n",
" Expected_Delivery_Date Delivered_Date \\\n",
"0 25-10-2021 25-10-2021 \n",
"1 25-10-2021 25-10-2021 \n",
"2 25-10-2021 25-10-2021 \n",
"3 25-10-2021 25-10-2021 \n",
"4 04-09-2021 04-09-2021 \n",
"... ... ... \n",
"8901 04-12-2020 04-12-2020 \n",
"8902 04-12-2020 04-12-2020 \n",
"8903 04-12-2020 04-12-2020 \n",
"8904 04-12-2020 04-12-2020 \n",
"8905 04-12-2020 04-12-2020 \n",
"\n",
" product_name product_main_category \\\n",
"0 Indcrown Net Embroidered Semi-stitched Lehenga... Clothing \n",
"1 Shopmania Music Band A5 Notebook Spiral Bound Pens & Stationery \n",
"2 Shopmania Music Band A5 Notebook Spiral Bound Pens & Stationery \n",
"3 Tiara Diaries 2016-2017 Designer LA Kaarta \"TA... Pens & Stationery \n",
"4 KAJCI Embroidered Women's Waistcoat Clothing \n",
"... ... ... \n",
"8901 Sinina Chanderi Embroidered Salwar Suit Dupatt... Clothing \n",
"8902 Aarushi Fashion Chanderi Embroidered Salwar Su... Clothing \n",
"8903 Ambika Lahenga Embroidered Lehenga, Choli and ... Clothing \n",
"8904 Sinina Chanderi Embroidered Salwar Suit Dupatt... Clothing \n",
"8905 Aarushi Fashion Silk Striped Salwar Suit Dupat... Clothing \n",
"\n",
" product_subcategory product_category_filter \\\n",
"0 Women's Clothing Ethnic Wear \n",
"1 Diaries & Notebooks Notebooks \n",
"2 Diaries & Notebooks Notebooks \n",
"3 Diaries & Notebooks Notebooks \n",
"4 Women's Clothing Formal Wear \n",
"... ... ... \n",
"8901 Women's Clothing Ethnic Wear \n",
"8902 Women's Clothing Ethnic Wear \n",
"8903 Women's Clothing Ethnic Wear \n",
"8904 Women's Clothing Ethnic Wear \n",
"8905 Women's Clothing Ethnic Wear \n",
"\n",
" product_category_subfilter product_unique ID retail_price \\\n",
"0 Fabric FABEJX2NHNKCYHKA 999 \n",
"1 Designer DIAEJ6Z8BEDTGGYY 499 \n",
"2 Designer DIAEJ6Z8KQFWDEGH 499 \n",
"3 Designer DIAEJ8FGHZ3K86JU 1000 \n",
"4 Waistcoats WSCEG2FYDYFDSVZ6 1200 \n",
"... ... ... ... \n",
"8901 Fabric FABEGGHHDFMY8BZU 2980 \n",
"8902 Fabric FABEG8GFDUWRSNU3 2600 \n",
"8903 Lehenga Cholis LEHEGGEHYN4G2RPW 39992 \n",
"8904 Fabric FABEGGHHGSVCHGFV 2000 \n",
"8905 Fabric FABEG8GYDAABECZH 2800 \n",
"\n",
" discounted_price product_rating Brand \n",
"0 699 4.0 INDCROWN \n",
"1 275 1.0 SHOPMANIA \n",
"2 275 2.0 SHOPMANIA \n",
"3 837 3.0 TIARA DIARIES \n",
"4 699 5.0 KAJCI \n",
"... ... ... ... \n",
"8901 1490 3.0 SININA \n",
"8902 1300 1.0 AARUSHI FASHION \n",
"8903 24995 1.0 AMBIKA LAHENGA \n",
"8904 1000 3.0 SININA \n",
"8905 1350 4.0 AARUSHI FASHION \n",
"\n",
"[8906 rows x 15 columns]"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NEW=ECom_Data.drop(['product_specifications','description'],axis=1,inplace=False)\n",
"NEW\n",
"\n",
"#the drop() method eliminates the selected columns but doesn't delete them permanently"
]
},
{
"cell_type": "markdown",
"id": "bea9e49c",
"metadata": {
"id": "bea9e49c"
},
"source": [
"we created a dew dataset as NEW and deleted the columns product_specifications and description, as we set implace as false the columns wont be perminently deleted"
]
},
{
"cell_type": "markdown",
"id": "e6159f6a",
"metadata": {
"id": "e6159f6a"
},
"source": [
"### Ans 2 b)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "47a63265",
"metadata": {
"id": "47a63265"
},
"outputs": [],
"source": [
"#ECom_Data.drop(['product_specifications','description'],axis=1,inplace=True)\n",
"\n",
"#if the inplace parameter is set to True, then the columns are permanently deleted from the DataFrame"
]
},
{
"cell_type": "markdown",
"id": "b87a849f",
"metadata": {
"id": "b87a849f"
},
"source": [
"as we set the inplace as false the columns wont be permenently deleted"
]
},
{
"cell_type": "markdown",
"id": "cde421e0",
"metadata": {
"id": "cde421e0"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" The next steps in this project involves summarization of data at various levels and visualization. Apparently, such simple steps are very useful to get an overall sense of the data.\n",
" </font>"
]
},
{
"cell_type": "markdown",
"id": "41c30ad7",
"metadata": {
"id": "41c30ad7"
},
"source": [
"## Q 3. Here we summarize the data at Brand level.\n",
"## a) How many unique Brand are there? (2 marks)\n",
"## b) Note that each Brand contains multiple products. Show the average product_rating within each Brand (2 marks)\n"
]
},
{
"cell_type": "markdown",
"id": "beb3f83f",
"metadata": {
"id": "beb3f83f"
},
"source": [
"### Ans 3 a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "41dcb79f",
"metadata": {
"id": "41dcb79f",
"outputId": "456cd13a-0699-4bee-fe4f-06847aeb9c98"
},
"outputs": [
{
"data": {
"text/plain": [
"2484"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(ECom_Data['Brand'].unique())\n",
"\n",
"# There are 2484 unique Brands in the DataFrame. Found using the unique() method"
]
},
{
"cell_type": "markdown",
"id": "5083d866",
"metadata": {
"id": "5083d866"
},
"source": [
"### Ans 3 b)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "10018c2c",
"metadata": {
"id": "10018c2c",
"outputId": "3c9c7da4-f1bf-4854-a480-c06f5257bc19"
},
"outputs": [
{
"data": {
"text/plain": [
"Brand\n",
"1OAK 1.500000\n",
"3A AUTOCARE 3.268293\n",
"3D MAT 3.000000\n",
"3KFACTORY 2.000000\n",
"4D 3.600000\n",
" ... \n",
"ZORDEN 4.000000\n",
"ZOSIGN 3.400000\n",
"ZRESTHA 1.000000\n",
"ZYXEL 3.333333\n",
" TARKAN 5.000000\n",
"Name: product_rating, Length: 2484, dtype: float64"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ECom_Data.groupby(['Brand'])['product_rating'].mean()\n",
"\n",
"# we use groupby to collect data under one column, in this case Brand column"
]
},
{
"cell_type": "markdown",
"id": "bbf162af",
"metadata": {
"id": "bbf162af"
},
"source": [
"## Q 4. Next we study the main categories of the products.\n",
"\n",
"## a) Create an appropriate plot to show the count of items ordered for each product_main_category. (6 marks).\n",
"\n",
"### Hint: Create a bar chart titled \"Product Category type\" where product_main_category are on x-axis and counts are on y-axis.\n",
"\n",
"### Note: Both axis labels, i.e. the names of the product_main_category and counts must be clearly legible.\n",
"\n",
"## b) From the plot identify for which two product_main_category(s) maximum and minimum orders were placed. (2 marks)\n",
"\n",
"## c) Write code to print out the top 5 product_main_category(s) in descending order? (3 marks"
]
},
{
"cell_type": "markdown",
"id": "36c72928",
"metadata": {
"id": "36c72928"
},
"source": [
"### Ans 4 a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f60dd2c1",
"metadata": {
"scrolled": true,
"id": "f60dd2c1",
"outputId": "b7188905-07a9-4e92-98c3-eddd9940985a"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"sns.countplot(data=ECom_Data, x=\"product_main_category\");\n",
"plt.xticks(rotation = 90);"
]
},
{
"cell_type": "markdown",
"id": "bc18dc19",
"metadata": {
"id": "bc18dc19"
},
"source": [
"the below plot show the count of items ordered for each product_main_category, clothing has the maximum number of orders while wearable smart watches has the least number of orders"
]
},
{
"cell_type": "markdown",
"id": "13a5b355",
"metadata": {
"id": "13a5b355"
},
"source": [
"### Ans 4 b)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "24d3f75c",
"metadata": {
"id": "24d3f75c",
"outputId": "32b0bcaf-ae99-4376-dd97-cc465bba736a"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"maximum product_main_category is product_main_category\n",
"Clothing 2943\n",
"Name: product_main_category, dtype: int64\n"
]
}
],
"source": [
"df=ECom_Data.groupby('product_main_category')['product_main_category'].count().sort_values(ascending = False).head(1)\n",
"print(\"maximum product_main_category is \",df)"
]
},
{
"cell_type": "markdown",
"id": "eb9a540e",
"metadata": {
"id": "eb9a540e"
},
"source": [
"maximum orders were placed in clothing"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8649c5f5",
"metadata": {
"id": "8649c5f5",
"outputId": "218cfc30-d12a-4e12-cb7b-acc3b8c9b20d"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"minimum product_main_category is product_main_category\n",
"Wearable Smart Devices 1\n",
"Name: product_main_category, dtype: int64\n"
]
}
],
"source": [
"df=ECom_Data.groupby('product_main_category')['product_main_category'].count().sort_values(ascending = False).tail(1)\n",
"print(\"minimum product_main_category is \",df)"
]
},
{
"cell_type": "markdown",
"id": "0fdcc5b4",
"metadata": {
"id": "0fdcc5b4"
},
"source": [
"minimum orders were placed in wearable smart watches"
]
},
{
"cell_type": "markdown",
"id": "4ea60c92",
"metadata": {
"id": "4ea60c92"
},
"source": [
"### Ans 4 c)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f704116",
"metadata": {
"id": "7f704116",
"outputId": "73eaf86c-8ec9-4bba-f06f-d301276472bc"
},
"outputs": [
{
"data": {
"text/plain": [
"product_main_category\n",
"Clothing 2943\n",
"Mobiles & Accessories 1084\n",
"Automotive 1001\n",
"Home Decor & Festive Needs 727\n",
"Computers 558\n",
"Name: product_main_category, dtype: int64"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# use groupby on 'product_main_category\n",
"#count() function is used to find the number of orders of each item\n",
"#ascending=False will give out the top product_main_category\n",
"\n",
"ECom_Data.groupby('product_main_category')['product_main_category'].count().sort_values(ascending = False).head(5)\n"
]
},
{
"cell_type": "markdown",
"id": "c8cc6fe6",
"metadata": {
"id": "c8cc6fe6"
},
"source": [
"the output shows the top 5 product_main_category"
]
},
{
"cell_type": "markdown",
"id": "a9f81605",
"metadata": {
"id": "a9f81605"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" In E-commerce, both the retailers (here brands) and the company have to make profit to sustain in the business.\n",
" The E-Commerce company has the following rule for computing their own revenue: </font>\n",
" \n",
"#### The company charges \n",
"#### (i) 25% on the orders having final price (discounted price) greater than 600\n",
"\n",
"#### (ii) 15% on the orders having final price (discounted price) greater than 350 but less than or equal to 600\n",
"\n",
"#### (iii) 10% on the orders having final price (discounted price) greater than 100 but less than or equal to 350\n",
"\n",
"#### (iv) Otherwise, 5% on the final price (discounted price) </font>"
]
},
{
"cell_type": "markdown",
"id": "0f255fea",
"metadata": {
"id": "0f255fea"
},
"source": [
"## Q 5. Find the Total Revenue generated by the E-Commerce company over all orders placed. (6 marks)\n",
"\n",
"#### Hint: Calculate revenue of E-commerce company using the conditions mentioned above and then do the total (sum) of all to get total Revenue."
]
},
{
"cell_type": "markdown",
"id": "1f6b8028",
"metadata": {
"id": "1f6b8028"
},
"source": [
"### Ans 5"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c62d888f",
"metadata": {
"id": "c62d888f",
"outputId": "eda09df3-b508-4020-b90f-b8032b571005"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total ECOM_Revenue Generated: $ 2217486.85\n"
]
}
],
"source": [
"\n",
"ECom_Data['ECOM_revenue'] = 0.0\n",
"\n",
"# Apply the revenue calculation rules\n",
"ECom_Data.loc[ECom_Data['discounted_price'] > 600, 'ECOM_revenue'] = ECom_Data.loc[ECom_Data['discounted_price'] > 600, 'discounted_price'] * 0.25\n",
"ECom_Data.loc[(ECom_Data['discounted_price'] > 350) & (ECom_Data['discounted_price'] <= 600), 'ECOM_revenue'] = ECom_Data.loc[(ECom_Data['discounted_price'] > 350) & (ECom_Data['discounted_price'] <= 600), 'discounted_price'] * 0.15\n",
"ECom_Data.loc[(ECom_Data['discounted_price'] > 100) & (ECom_Data['discounted_price'] <= 350), 'ECOM_revenue'] = ECom_Data.loc[(ECom_Data['discounted_price'] > 100) & (ECom_Data['discounted_price'] <= 350), 'discounted_price'] * 0.10\n",
"ECom_Data.loc[ECom_Data['discounted_price'] <= 100, 'ECOM_revenue'] = ECom_Data.loc[ECom_Data['discounted_price'] <= 100, 'discounted_price'] * 0.05\n",
"\n",
"# Compute the total revenue\n",
"total_ECOM_revenue = ECom_Data['ECOM_revenue'].sum()\n",
"\n",
"print(\"Total ECOM_Revenue Generated: $\", total_ECOM_revenue)\n"
]
},
{
"cell_type": "markdown",
"id": "c01af1b5",
"metadata": {
"id": "c01af1b5"
},
"source": [
"the total revenue generated by ecommerce company is $2217486.85"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3f48a373",
"metadata": {
"id": "3f48a373",
"outputId": "1f8b33b4-cd2f-4d80-9ed6-876ac21ae1c1"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total ECOM revenue is 2217486.85\n"
]
}
],
"source": [
"# another way to solve is by using a user defined function\n",
"def calculation(discounted_price):\n",
" if discounted_price > 600:\n",
" return discounted_price * 0.25\n",
" elif discounted_price > 350 and discounted_price <= 600:\n",
" return discounted_price * 0.15\n",
" elif discounted_price > 100 and discounted_price <= 350:\n",
" return discounted_price * 0.10\n",
" else:\n",
" return discounted_price * 0.05\n",
"\n",
"ECom_Data['calc'] = ECom_Data['discounted_price'].apply(calculation)\n",
"print(\"total ECOM revenue is\",ECom_Data['calc'].sum())\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "c15c1a1e",
"metadata": {
"id": "c15c1a1e"
},
"source": [
"the total ECOM revenue generated is $2217486.85"
]
},
{
"cell_type": "markdown",
"id": "9161ca8c",
"metadata": {
"id": "9161ca8c"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" Now you need to find the revenue for each retailer (Brand)\n",
" </font>"
]
},
{
"cell_type": "markdown",
"id": "73dd23c3",
"metadata": {
"id": "73dd23c3"
},
"source": [
"## Q6.Calculate the total BrandRevenue and list the top 10 Brand having maximum revenue in descending order (6 marks)\n",
"#### Hint: Total BrandRevenue is BrandRevenue which is generated after all the deductions. Also, BrandRevenue is different from the E-Commerce company's revenue.\n",
"#### Brand Revenue is the discounted price minus the Revenue (generated using the conditions given above Q5)\n"
]
},
{
"cell_type": "markdown",
"id": "3514fa79",
"metadata": {
"id": "3514fa79"
},
"source": [
"### Ans 6"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "437c69b5",
"metadata": {
"id": "437c69b5",
"outputId": "d80be3f5-3917-4833-f830-ef0f08f6e904"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total brand revenue is 7522992.15\n"
]
}
],
"source": [
"# Calculate the brand revenue for each retailer (brand)\n",
"ECom_Data['brand_revenue'] = ECom_Data['discounted_price'] - ECom_Data['ECOM_revenue']\n",
"\n",
"# Calculate the total brand revenue for each brand\n",
"brand_revenue_total = ECom_Data['brand_revenue'].sum()\n",
"print(\"total brand revenue is\",brand_revenue_total)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3df41984",
"metadata": {
"id": "3df41984",
"outputId": "a5aa45f3-f4db-4d18-90ef-6e199e109568"
},
"outputs": [
{
"data": {
"text/plain": [
"Brand\n",
"ALLURE AUTO 498464.25\n",
"GAGA 237390.00\n",
"SLIM 212062.60\n",
"DAILYOBJECTS 181980.00\n",
"DIVINITI 143115.00\n",
"THELOSTPUPPY 127287.50\n",
"REGULAR 126536.50\n",
"ENTHOPIA 123146.25\n",
"ASUS 99241.50\n",
"SPRINGWEL 88978.50\n",
"Name: brand_revenue, dtype: float64"
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ECom_Data.groupby('Brand')['brand_revenue'].sum().sort_values(ascending=False).head(10)"
]
},
{
"cell_type": "markdown",
"id": "a84e6dfc",
"metadata": {
"id": "a84e6dfc"
},
"source": [
"the outputs shows the top 10 brands having the maximum revenue"
]
},
{
"cell_type": "markdown",
"id": "2a2bbd83",
"metadata": {
"id": "2a2bbd83"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
"Let us now investigate multiple features for each product to determine any pattern.\n",
"</font>"
]
},
{
"cell_type": "markdown",
"id": "1aa1834b",
"metadata": {
"id": "1aa1834b"
},
"source": [
"## Q 7. Compare prices for each product.\n",
"\n",
"## a)\tDraw boxplots of retail_price & discounted_price. (3 marks)\n",
"\n",
"## b)\t Are there any outliers? (Yes/No) (1mark)\n",
"\n",
"## c)\tCreate a scatterplot of retail_price (x-axis) and discounted_price (y-axis) (3 marks)\n"
]
},
{
"cell_type": "markdown",
"id": "d5aae861",
"metadata": {
"id": "d5aae861"
},
"source": [
"### Ans 7 a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "510fd4d0",
"metadata": {
"id": "510fd4d0",
"outputId": "7c412131-a055-470a-ccc9-4ee726001657"
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='retail_price', ylabel='discounted_price'>"
]
},
"execution_count": 94,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.boxplot(data=ECom_Data,x='retail_price',y='discounted_price')"
]
},
{
"cell_type": "markdown",
"id": "19a8621e",
"metadata": {
"id": "19a8621e"
},
"source": [
"the figure shows the boxplot of retail_price and discounted_price."
]
},
{
"cell_type": "markdown",
"id": "78b92e7c",
"metadata": {
"id": "78b92e7c"
},
"source": [
"### Ans 7 b)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7455beb0",
"metadata": {
"id": "7455beb0",
"outputId": "40b4a2ca-317c-4c91-dfa6-1323fc4e3fa4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Are there any outliers? Yes\n"
]
}
],
"source": [
"outliers = ECom_Data[(ECom_Data['retail_price'] > ECom_Data['retail_price'].quantile(0.75) + 1.5 * (ECom_Data['retail_price'].quantile(0.75) - ECom_Data['retail_price'].quantile(0.25))) |\n",
" (ECom_Data['retail_price'] < ECom_Data['retail_price'].quantile(0.25) - 1.5 * (ECom_Data['retail_price'].quantile(0.75) - ECom_Data['retail_price'].quantile(0.25))) |\n",
" (ECom_Data['discounted_price'] > ECom_Data['discounted_price'].quantile(0.75) + 1.5 * (ECom_Data['discounted_price'].quantile(0.75) - ECom_Data['discounted_price'].quantile(0.25))) |\n",
" (ECom_Data['discounted_price'] < ECom_Data['discounted_price'].quantile(0.25) - 1.5 * (ECom_Data['discounted_price'].quantile(0.75) - ECom_Data['discounted_price'].quantile(0.25)))]\n",
"\n",
"if outliers.empty:\n",
" print(\"Are there any outliers? No\")\n",
"else:\n",
" print(\"Are there any outliers? Yes\")"
]
},
{
"cell_type": "markdown",
"id": "9802390d",
"metadata": {
"id": "9802390d"
},
"source": [
"from the above output we can see that there are no outliers."
]
},
{
"cell_type": "markdown",
"id": "0389c9b8",
"metadata": {
"id": "0389c9b8"
},
"source": [
"### Ans 7 c)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d8c44be9",
"metadata": {
"id": "d8c44be9",
"outputId": "d91625d2-22f3-4395-8fd2-ebbf1b0dda93"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=ECom_Data,x='retail_price',y='discounted_price');"
]
},
{
"cell_type": "markdown",
"id": "3dd1d9c4",
"metadata": {
"id": "3dd1d9c4"
},
"source": [
"this above figure shows the scatter plot between retail price and discounted price"
]
},
{
"cell_type": "markdown",
"id": "3bc47f55",
"metadata": {
"id": "3bc47f55"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" The next steps will enable to study brand-level information.\n",
" </font>"
]
},
{
"cell_type": "markdown",
"id": "b9bd00f7",
"metadata": {
"id": "b9bd00f7"
},
"source": [
"## Q 8. Create a new dataframe to include the Brand specific information as stated:\n",
"## i.\ttotal number of orders placed per Brand\n",
"## ii.\ttotal retail_price per Brand\n",
"## iii.\ttotal discounted_price per Brand, and\n",
"## iv.\ttotal BrandRevenue generated per Brand.\n",
"\n",
"## Also, draw a pairplot using these four features. (6 marks)\n"
]
},
{
"cell_type": "markdown",
"id": "8f83cea9",
"metadata": {
"id": "8f83cea9"
},
"source": [
"### Ans 8"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ae749847",
"metadata": {
"id": "ae749847",
"outputId": "db1be647-1054-455b-e922-8747a7a348ca"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x1000 with 20 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Total Orders Total Retail Price Total Discounted Price \\\n",
"Brand \n",
"1OAK 2 1698 1274 \n",
"3A AUTOCARE 41 107059 74134 \n",
"3D MAT 1 7250 6999 \n",
"3KFACTORY 1 399 174 \n",
"4D 5 17500 7948 \n",
"... ... ... ... \n",
"ZORDEN 1 3999 2799 \n",
"ZOSIGN 5 6995 6995 \n",
"ZRESTHA 1 1999 899 \n",
"ZYXEL 9 64742 35392 \n",
" TARKAN 1 1999 349 \n",
"\n",
" Total Brand Revenue \n",
"Brand \n",
"1OAK 1015.40 \n",
"3A AUTOCARE 55647.90 \n",
"3D MAT 5249.25 \n",
"3KFACTORY 156.60 \n",
"4D 5961.00 \n",
"... ... \n",
"ZORDEN 2099.25 \n",
"ZOSIGN 5246.25 \n",
"ZRESTHA 674.25 \n",
"ZYXEL 26544.00 \n",
" TARKAN 314.10 \n",
"\n",
"[2484 rows x 4 columns]\n"
]
}
],
"source": [
"import seaborn as sns\n",
"\n",
"# Create a new dataframe with brand-specific information\n",
"brand_data = pd.DataFrame()\n",
"\n",
"# Calculate the total number of orders placed per brand\n",
"brand_data['Total Orders'] = ECom_Data.groupby('Brand')['Customer_uniq_id'].count()\n",
"\n",
"# Calculate the total retail_price per brand\n",
"brand_data['Total Retail Price'] = ECom_Data.groupby('Brand')['retail_price'].sum()\n",
"\n",
"# Calculate the total discounted_price per brand\n",
"brand_data['Total Discounted Price'] = ECom_Data.groupby('Brand')['discounted_price'].sum()\n",
"\n",
"# Calculate the total brand revenue generated per brand\n",
"brand_data['Total Brand Revenue'] = ECom_Data.groupby('Brand')['brand_revenue'].sum()\n",
"\n",
"# Draw a pairplot using the four features\n",
"sns.pairplot(brand_data)\n",
"plt.title('Pairplot of Brand Information')\n",
"plt.show()\n",
"\n",
"# Print the new dataframe\n",
"print(brand_data)"
]
},
{
"cell_type": "markdown",
"id": "bfbd8086",
"metadata": {
"id": "bfbd8086"
},
"source": [
"thepairplot is created using the new dataset which is created using 4 features"
]
},
{
"cell_type": "markdown",
"id": "ecec83f4",
"metadata": {
"id": "ecec83f4"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" The E-Commerce company operate in multiple regions. It is important to understand its performance in each region.\n",
" </font>"
]
},
{
"cell_type": "markdown",
"id": "dd09b8aa",
"metadata": {
"id": "dd09b8aa"
},
"source": [
"## Q 9.Compare performance regionwise\n",
"\n",
"## a)\tDraw a lineplot for the monthly Revenue of E-Commerce Company for each region separately. (4 marks)\n",
"\n",
"## b)\tIdentify the best and the worst performing months for each region. (2 marks)\n",
"\n",
"#### Note: Only those days with actual orders(Order_Date) placed are present in the dataset. Assuming there were no orders on other days. Also, show Month and Year on x-axis."
]
},
{
"cell_type": "markdown",
"id": "e6d64aea",
"metadata": {
"id": "e6d64aea"
},
"source": [
"### Ans 9 a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a5064b8e",
"metadata": {
"scrolled": true,
"id": "a5064b8e"
},
"outputs": [],
"source": [
"ECom_Data['Order_Date']=pd.to_datetime(ECom_Data['Order_Date'],dayfirst=True) #converts order_Date data-type from object to datetime\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "070515fd",
"metadata": {
"id": "070515fd",
"outputId": "5ec00f11-0ec9-4057-dcf4-29ce0948fea6"
},
"outputs": [
{
"data": {
"text/plain": [
"0 10\n",
"1 10\n",
"2 10\n",
"3 10\n",
"4 9\n",
" ..\n",
"8901 12\n",
"8902 12\n",
"8903 12\n",
"8904 12\n",
"8905 12\n",
"Name: Order_Date, Length: 8906, dtype: int32"
]
},
"execution_count": 99,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ECom_Data['Month']=ECom_Data['Order_Date'].dt.month\n",
"ECom_Data['Order_Date'].dt.month\n",
"\n",
"#creates a month column using the orderdates"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f5bcea02",
"metadata": {
"scrolled": true,
"id": "f5bcea02",
"outputId": "501dbcaa-ee78-4c9e-925e-c3f985f1150b"
},
"outputs": [
{
"data": {
"text/plain": [
"Month\n",
"1 513165.25\n",
"2 41176.35\n",
"3 347232.70\n",
"4 151446.70\n",
"5 59677.60\n",
" ... \n",
"7 1194.35\n",
"8 1936.25\n",
"9 680.15\n",
"10 439.00\n",
"12 956624.00\n",
"Name: ECOM_revenue, Length: 11, dtype: float64"
]
},
"execution_count": 100,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ECom_Data.groupby('Month')['ECOM_revenue'].sum()"
]
},
{
"cell_type": "markdown",
"id": "7402d2fb",
"metadata": {
"id": "7402d2fb"
},
"source": [
"the output shows the revenue generated for each month seperately"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9250838f",
"metadata": {
"id": "9250838f",
"outputId": "1218262a-7d30-463e-ffa9-bb846132455c"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Convert 'Order_Date' column to datetime\n",
"ECom_Data['Order_Date'] = pd.to_datetime(ECom_Data['Order_Date'], dayfirst=True)\n",
"\n",
"# Extract the month from 'Order_Date'\n",
"ECom_Data['Month'] = ECom_Data['Order_Date'].dt.month\n",
"\n",
"# Create a line plot for the monthly revenue of each region\n",
"plt.figure(figsize=(12, 6))\n",
"sns.lineplot(data=ECom_Data, x='Month', y='ECOM_revenue', hue='Region')\n",
"plt.title('Monthly Revenue by Region')\n",
"plt.xlabel('Month')\n",
"plt.ylabel('ECOM_revenue')\n",
"plt.xticks(range(1, 13))\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "bfadaf33",
"metadata": {
"id": "bfadaf33"
},
"source": [
"the lineplot shows the monthly Revenue of E-Commerce Company for each region"
]
},
{
"cell_type": "markdown",
"id": "dac59dc4",
"metadata": {
"id": "dac59dc4"
},
"source": [
"### Ans 9 b)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9f569635",
"metadata": {
"id": "9f569635",
"outputId": "16e3ada5-3ddf-4031-d6aa-e61db5990420"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Best Performing Months by Region:\n",
" Region Order_Date ECOM_revenue\n",
"0 East 2020-12-31 363413.85\n",
"11 North 2020-12-31 195149.95\n",
"20 South 2020-12-31 95088.25\n",
"27 West 2020-12-31 302971.95\n",
"\n",
"Worst Performing Months by Region:\n",
" Region Order_Date ECOM_revenue\n",
"10 East 2021-10-31 202.25\n",
"18 North 2021-07-31 306.00\n",
"25 South 2021-05-31 3708.75\n",
"36 West 2021-10-31 236.75\n"
]
}
],
"source": [
"# Calculate the monthly revenue for each region\n",
"monthly_revenue = ECom_Data.groupby(['Region', pd.Grouper(key='Order_Date', freq='M')])['ECOM_revenue'].sum().reset_index()\n",
"\n",
"# Find the best and worst performing months for each region\n",
"best_months = monthly_revenue.groupby('Region')['ECOM_revenue'].idxmax()\n",
"worst_months = monthly_revenue.groupby('Region')['ECOM_revenue'].idxmin()\n",
"\n",
"best_performance = monthly_revenue.loc[best_months, ['Region', 'Order_Date', 'ECOM_revenue']]\n",
"worst_performance = monthly_revenue.loc[worst_months, ['Region', 'Order_Date', 'ECOM_revenue']]\n",
"\n",
"print(\"Best Performing Months by Region:\")\n",
"print(best_performance)\n",
"print(\"\\nWorst Performing Months by Region:\")\n",
"print(worst_performance)"
]
},
{
"cell_type": "markdown",
"id": "61f6bda8",
"metadata": {
"id": "61f6bda8"
},
"source": [
"the best performing months for east,north,south and west is 12th month\n",
"the worst performing months for east region is 10th, for north is 7th, for south is 5th and for west is 10th month"
]
},
{
"cell_type": "markdown",
"id": "dcb8d39f",
"metadata": {
"id": "dcb8d39f"
},
"source": [
"<font color='blue'>\n",
" <font size = 5>\n",
" Congratulations! You have learnt how to approach a complex data and extract information out of it.\n",
" </font>"
]
}
],
"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": "3.11.4"
},
"colab": {
"provenance": [],
"include_colab_link": true
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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