https://github.com/priyapuranik/diwali-sales-analysis_with-data-visualization

Diwali sales data analysis with visualizations, highlighting customer demographics, product categories, and purchase trends.
https://github.com/priyapuranik/diwali-sales-analysis_with-data-visualization

data-visualization matplotlib-pyplot pandas python seaborn

Last synced: 6 days ago
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Diwali sales data analysis with visualizations, highlighting customer demographics, product categories, and purchase trends.

• Host: GitHub
• URL: https://github.com/priyapuranik/diwali-sales-analysis_with-data-visualization
• Owner: priyapuranik
• Created: 2024-10-24T11:52:29.000Z (25 days ago)
• Default Branch: main
• Last Pushed: 2024-10-24T12:03:14.000Z (25 days ago)
• Last Synced: 2024-10-25T11:55:44.693Z (24 days ago)
• Topics: data-visualization, matplotlib-pyplot, pandas, python, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 531 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Diwali-Sales-Analysis_with-Data-Visualization

## Description

This project involves the analysis of Diwali sales data to uncover insights about customer demographics, product categories, and purchasing trends. The analysis includes visualizations that highlight key findings from the dataset.

## Data Description

The dataset contains the following columns:

- **User_ID**: Unique identifier for each user.

- **Cust_name**: Name of the customer.

- **Product_ID**: Identifier for the product purchased.

- **Gender**: Gender of the customer.

- **Age Group**: Age group category of the customer (e.g., 0-17, 18-25, 26-35, etc.).

- **Age**: Exact age of the customer.

- **Shaadi**: Marital status (0 for unmarried, 1 for married).

- **State**: State of the customer.

- **Zone**: Geographical zone of the customer.

- **Occupation**: Customer's occupation.

- **Product_Category**: Category of the product purchased.

- **Orders**: Number of orders placed.

- **Amount**: Total amount spent.

## Charts and Visualizations

The following charts have been created to represent the data visually:

- **Total Amount and Age group**: A bar chart illustrating age group performance and total amount throughout the Diwali season.

- **Average Spending by Product Category**: A bar chart showing each product category and it's average spending on amount.

- **Total number of Orders from top 10 states**: Bar charts depicting the highest number of orders that coming from which state.

- **Gender Distribution**: A pie chart showing distribution of Gender.

## Installation and Usage

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

- pandas

- matplotlib

- seaborn

- numpy

To install the required libraries, you can use pip:

```bash

pip install pandas matplotlib seaborn numpy