Ecommerce Case Study Through Python

Online shopping has taken the world by storm as the share of E-commerce has grown 3X in last 5 years. Learn all important metrics and how to solve problems in the e-commerce industry.

Learn the following Python Concepts:

• How to get N rows of data in Python
• How to use Aggregate Functions in Python
  • Count, Count Distinct, Sum, Maximum, Minimum etc.
• How to Group data and aggregate in Python
• How to combine Grouping and Sorting in Python
• How to use Mathematical Functions on Aggregate Values in Python
• How to use Date Functions in Python
  • How to extract parts of date from a column in Python
• How to do time-series analysis of a metric in Python
• How to run Subqueries in Select statement in Python
• How to run Subqueries as a column in Python
• How to convert an aggregate column to percentage in Python
• How to use Window Functions in Python
• How to find running total through SUM OVER() Function in Python

Learn the following Concepts about E-commerce:

• Understand the difference between Orders and Units in E-commerce
• What is Gross Merchandise Value and how to calculate it
• How to Find the Average Order Value
• How to get the Total Users and Average Revenue per User
• What is Basket Size in E-commerce and how to calculate it
• Analyze product categories based on Gross Merchandise Value
• How to do Time-series analysis of Gross Merchandise Value
• What is Monthly/Weekly/Daily Active Users (MAU, WAU, DAU)
  • How to do Time-series analysis of Monthly Active Users
• How to do sales distribution analysis by time cuts
• How to calculate monthly running or cumulative revenue in E-commerce