Retail Sales Data Analysis with Pandas

Dive into the world of sales and marketing analytics using a real-world Retail Sales dataset. This microlearning course will help you explore multi-store, multi-region sales data using Python’s Pandas library. You’ll uncover business insights like best-selling products, seasonal sales trends, and regional performance — all through practical data handling, cleaning, grouping, and visualization.

Perfect for aspiring data analysts, marketers, and business professionals seeking a hands-on, project-based introduction to EDA.

Aspiring Data Analysts & Data Science Beginners
Those looking to build real-world portfolio projects
Learners transitioning from Excel to Python
🔹 Business and Marketing Students
Learners who want to explore business data analysis
MBA or BBA students interested in retail analytics
🔹 Freelancers & Junior Analysts
Professionals who want to automate sales reporting
Freelancers working on eCommerce or retail projects
🔹 Small Business Owners / Entrepreneurs
Founders looking to understand sales patterns using data
Curious non-techies wanting to analyze their own store data
🔹 Job Seekers & Resume BuildersCandidates preparing for roles in data, BI, or business analytics
Freshers looking to add a practical project to GitHub or LinkedIn

Course Content

Module 1: Dataset Overview
Understanding the Dataset

Module 2: Data Preparation
Converting Date column to datetime format Creating Month, Weekday, and Quarter features Fixing data types and checking missing values

Module 3: Data Cleaning
Handling missing/invalid price and sales values Creating Net Sales = Units Sold * Price Adding Discounted Price and Revenue features

Module 4: EDA – Store & Region Performance
Grouping by Region and Store ID Identifying top 5 performing stores Average price vs revenue analysis

Module 5: EDA – Product and Seasonal Trends
Best-selling products by volume and revenue Sales trend by month and weekday Impact of discounts on product sales

Module 6: Data Visualization
Line plot: Monthly sales trend Bar plot: Region-wise revenue comparison Histogram: Price distribution Box plot: Discount vs Units Sold

Module 7: Retail Sales Dashboard Report
Prepare a report summarizing your key findings Combine visualizations and key metrics

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₹399.00 ~~₹899.00~~
Instructor:admin
Duration: 1 hour
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Level:Beginner
Certifications:No

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Course Content

Module 1: Dataset Overview
Understanding the Dataset

Module 2: Data Preparation
Converting Date column to datetime format Creating Month, Weekday, and Quarter features Fixing data types and checking missing values

Module 3: Data Cleaning
Handling missing/invalid price and sales values Creating Net Sales = Units Sold * Price Adding Discounted Price and Revenue features

Module 4: EDA – Store & Region Performance
Grouping by Region and Store ID Identifying top 5 performing stores Average price vs revenue analysis

Module 5: EDA – Product and Seasonal Trends
Best-selling products by volume and revenue Sales trend by month and weekday Impact of discounts on product sales

Module 6: Data Visualization
Line plot: Monthly sales trend Bar plot: Region-wise revenue comparison Histogram: Price distribution Box plot: Discount vs Units Sold

Module 7: Retail Sales Dashboard Report
Prepare a report summarizing your key findings Combine visualizations and key metrics

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Retail Sales Data Analysis with Pandas

What Will You Learn?

Material Includes

Audience

Course Content

Module 1: Dataset Overview Understanding the Dataset

Module 2: Data Preparation Converting Date column to datetime format Creating Month, Weekday, and Quarter features Fixing data types and checking missing values

Module 3: Data Cleaning Handling missing/invalid price and sales values Creating Net Sales = Units Sold * Price Adding Discounted Price and Revenue features

Module 4: EDA – Store & Region Performance Grouping by Region and Store ID Identifying top 5 performing stores Average price vs revenue analysis

Module 5: EDA – Product and Seasonal Trends Best-selling products by volume and revenue Sales trend by month and weekday Impact of discounts on product sales

Module 6: Data Visualization Line plot: Monthly sales trend Bar plot: Region-wise revenue comparison Histogram: Price distribution Box plot: Discount vs Units Sold

Module 7: Retail Sales Dashboard Report Prepare a report summarizing your key findings Combine visualizations and key metrics

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Module 1: Dataset Overview
Understanding the Dataset

Module 2: Data Preparation
Converting Date column to datetime format Creating Month, Weekday, and Quarter features Fixing data types and checking missing values

Module 3: Data Cleaning
Handling missing/invalid price and sales values Creating Net Sales = Units Sold * Price Adding Discounted Price and Revenue features

Module 4: EDA – Store & Region Performance
Grouping by Region and Store ID Identifying top 5 performing stores Average price vs revenue analysis

Module 5: EDA – Product and Seasonal Trends
Best-selling products by volume and revenue Sales trend by month and weekday Impact of discounts on product sales

Module 6: Data Visualization
Line plot: Monthly sales trend Bar plot: Region-wise revenue comparison Histogram: Price distribution Box plot: Discount vs Units Sold

Module 7: Retail Sales Dashboard Report
Prepare a report summarizing your key findings Combine visualizations and key metrics