Diwali Sales Analysis

Welcome to the Diwali Sales Analysis project! This project focuses on analyzing sales data to gain valuable insights into customer behavior and product performance during the Diwali season. Using Python and data analysis libraries such as NumPy, Pandas, Matplotlib, and Seaborn, I've conducted an in-depth analysis based on various factors, including age, gender, occupation, and marital status.

Data Cleaning and Manipulation: I started by cleaning and preparing the dataset, ensuring accuracy and consistency.

Exploratory Data Analysis (EDA): Through EDA, I leveraged Pandas, Matplotlib, and Seaborn to visualize data trends, uncover patterns, and make informed decisions.

Customer Segmentation: I improved customer experience by identifying potential customers across different states, occupations, genders, and age groups. This segmentation can help tailor marketing strategies.

Product Category Analysis: By analyzing order counts and the amount spent, I identified the most selling product categories. This information can be instrumental in inventory planning to meet demand effectively.