This project contains an analysis of Diwali sales data. The analysis is performed using Python and various data science libraries such as NumPy, Pandas, Matplotlib, and Seaborn. The purpose of the used Diwali Sales dataset has been taken from Kaggle since it is one of the ideal dataset for performing EDA and taking a step towards the most amazing and interesting field of data science.
The data used in this project includes various details such as User ID, Customer Name, Product ID, Gender, Age Group, Age, Marital Status, State, Zone, Occupation, Product Category, Orders, Amount, and Status.
- Performed Data Cleaning and Data Manipulation.
- Performed Exploratory Data Analysis (EDA) using Pandas, NumPy, Matplotlib, Seaborn Libraries.
- Improved Customer experience by identifying potential customers across different states, occupation, gender and age groups.
- Improved sales by identifying most selling product categories and products, which can help to plan inventory and hence meet the demands.
The project includes various visualizations such as:
- Count plot of Occupation
- Bar plot of Orders by State
- Bar plot of Orders by Product ID
The analysis includes various visualizations and insights derived from the data. Some of the key findings include:
- Married women age group 26-35 yrs from UP,
- Maharastra and Karnataka working in IT,
- Healthcare and Aviation are more likely to buy products from Food,Clothing and Electronics category
