Diwali Sales Data Analysis 🪔📈

Project Summary:

This project analyzes Diwali sales data, providing insights into customer demographics and purchase behavior. The dataset comprises 11,251 entries and 15 columns, including information about customers, products, gender, age, marital status, state, occupation, product categories, orders, and amounts. The data exploration uncovers patterns and trends in sales during the festive season.

Objective:

The primary objective is to gain a deeper understanding of customer behavior during Diwali sales, identifying key demographics and product categories that drive sales.

Dataset Info:

• Number of records: 11,251
• Number of features: 15

Significant features include:

• User_ID: Unique identifier for each customer.
• Cust_name: Customer name.
• Product_ID: Unique product identifier.
• Gender: Gender of the customer.
• Age Group: Age group of the customer.
• Age: Age of the customer.
• Marital_Status: Marital status of the customer.
• State: State of the customer.
• Zone: Geographic zone.
• Occupation: Customer's occupation.
• Product_Category: Category of the purchased product.
• Orders: Number of orders placed.
• Amount: Purchase amount.

Project Workflow:

• Importing Python Libraries
• Data Wrangling
  1. Reading CSV Data File
  2. Data Assessment
  3. Data Cleaning
• Exploratory Data Analysis (EDA)
  1. Gender Analysis
  2. Age Group Analysis
  3. State Analysis
  4. Marital Status Analysis
  5. Occupation Analysis
  6. Product Category Analysis
• Conclusion