This project is designed to analyze sales data from a CSV file, calculate profits, and visualize the data to provide insights into the sales and profit trends over time.

• csv: For reading and writing CSV files.
• pandas: Used for data manipulation and analysis.
• plotly.express: For creating interactive charts and graphs for data visualization.

The project performs several key operations on the sales data:

1. Reads sales data from a CSV file.
2. Calculates total sales across all months.
3. Extends the project to calculate profit (sales - expenditure) for each month, adding this data as a new column in the CSV.
4. Calculates the total profit across all months.
5. Identifies the maximum and minimum sales and profit values across all months.
6. Visualizes the profit across all months using a line graph.
7. Offers the option to display additional graphs for sales and expenditure on demand.

This project uses Plotly Express to create dynamic and interactive visualizations. Specifically, it features:

• A line graph showing profits across all months, which helps in understanding the profit trends over time.
• On-demand generation of line graphs for sales and expenditure, allowing for a deeper dive into the financial performance of the company.

Ensure you have the required libraries installed:

pip install pandas plotly

Run the script in a Python environment. The script will prompt you to choose whether you want to display additional graphs for sales and expenditure.

The script operates on a sales.csv file, which must include the columns month, sales, and expenditure. Ensure this file is in the same directory as the script for it to run correctly.

This project offers a comprehensive analysis and visualization of sales data, providing valuable insights into the company's financial performance over time.