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ITIB$4134$ Programming for Data Analytics

Assignment Guidelines and Rubrics

Assignment $220\%$

Start: Week $7$

Due Date$($s$)$:

Week $13$

Learning Outcomes

CLO$3$: Apply pandas to extract, filter, and transform data from DataFrames in order to drill

the data that really matters $($C$3,$ P$4,$ PLO$2)$

CLO$4$: Solve data science questions by organizing, reshaping, and aggregating multiple

data sets $($C$3,$PLO$5)$

Instructions: Answer ALL questions. $(100$ Marks$)$

Assignment Title: Analyzing Customer Purchase Behavior

Assignment Description:

You are working for a retail company, and your task is to perform data analytics on customer

purchase behavior to gain insights that can help the company improve its sales and marketing

strategies. Find any dataset containing information about customer transactions. You can

search the datasets at Kaggle or GitHub

Requirements:

Your task is to create a Python script that performs the following data analytics tasks:

$1.$ Data Loading and Cleaning:

$$ Load the dataset into a pandas DataFrame.

$$ Check for missing values and handle them appropriately $($e$.$g$.,$ fill with zeros or remove

rows$).$

$$ Check for duplicates and remove them if necessary.

$2.$ Data Exploration:

Provide summary statistics and insights about the dataset, examples:

$$ Total number of customers.

$$ Total number of unique products.

$$ Total revenue generated.

$$ Most popular product category.

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$3.$ Customer Analysis:

$$ Calculate and visualize the distribution of the number of purchases per customer.

$$ Identify the top $10$ customers with the highest total purchase amount.

$4.$ Product Analysis:

$$ Calculate and visualize the distribution of product categories.

$$ Identify the top $10$ best$-$selling products.

$$ Calculate the average price for each product category.

$5.$ Visualization:

$$ Create informative visualizations $($e$.$g$.,$ bar charts, histograms, line plots$)$ to present your

findings.

$$ Use libraries such as Matplotlib or Seaborn for data visualization.

$6.$ Recommendations:

$$ Based on your analysis, provide at least three actionable recommendations for the

company to improve sales and marketing strategies.

Additional Guidelines:

$$ Ensure that your code is well$-$structured and includes comments to explain each step

of the analysis.

$$ Use appropriate data visualization techniques to effectively communicate your

findings.

$$ Consider the scalability of your code to handle larger datasets in the future.

$$ Provide a clear and concise report summarizing your analysis and recommendations.

Submission Requirements:

Submit a Python script $($e$.$g$.,$ customer$\_$purchase$\_$analysis.py$)$ along with a report $($in PDF

format$)$ that includes the results of your analysis, visualizations, and recommendations based

on your findings.

Note: You may choose to use Jupyter Notebook for your analysis and include both the

notebook and a Python script for the assignment submission.

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