DAPRO Data Analysis Notebook

Overview

This Jupyter Notebook performs data analysis on a dataset related to Diwali sales. It utilizes various Python libraries to clean, analyze, and visualize the sales data.

Dependencies

To run this notebook, you will need the following Python libraries:

• numpy
• pandas
• matplotlib
• seaborn
• google.colab (for file uploads)

You can install the required libraries using pip:

pip install numpy pandas matplotlib seaborn

Usage

1. Upload the Diwali Sales Data.csv file when prompted.
2. Run the notebook cells sequentially to perform data cleaning and analysis.
3. The notebook includes visualizations that display sales trends based on gender, age group, marital status, occupation, and product category.

Analysis Features

• Data cleaning: Dropping unnecessary columns and handling missing values.
• Grouping and summarizing data: Analyzing sales by gender, age group, marital status, occupation, and product category.
• Visualizations: Generating bar plots and count plots to illustrate sales trends.

Conclusion

This notebook provides insights into Diwali sales data, helping to understand customer behavior and sales performance across different demographics.