Skip to content

Analyzing Diwali sales to get valuable insights of most buyers depending on (gender, age group, states, occupation, marital status), most sold category and most sold products.

Notifications You must be signed in to change notification settings

AANAND94/Diwali-Sales-Analysis-Python-Project-

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 

Repository files navigation

Diwali-Sales-Analysis-Python-Project-

Analyzing Diwali sales to get valuable insights of most buyers depending on (gender, age group, states, occupation, marital status), most sold category and most sold products.

Objective of project: ▪ Improving customer experience ▪ Increase sales revenue

Steps: ▪ Data Cleaning and manipulation - removing null and duplicate values ▪ Exploratory Data Analysis - depending on Gender, Age, Marital Status, State, Occupation, and Product Category ▪ Used different functions for sorting data, indicating values and different charts for data representation.

Insights: ▪ Most buyers from Gender: Female (7832) ▪ Most buyers from Age group: (26-35) ▪ Most orders from States : Uttar Pradesh, Maharashtra and Karnataka ▪ Most buyers by Marital status: Married Woman (6518) ▪ Most buyers from occupation: IT Sector(1583), Healthcare (1408) and Aviation (1310) ▪ Most sold product are: Clothing and Apparel (2655), Food (2490), and Electronic and Gadgets (2087) ▪ Most sold product id are: P00265242 (127), P00110942 (116), P00237542 (91)

These insights can be helpful for improving customer experience and to improve sales as well as inventory planning and meeting demands of products.

About

Analyzing Diwali sales to get valuable insights of most buyers depending on (gender, age group, states, occupation, marital status), most sold category and most sold products.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published