PandasAI Visualization Project in Google Colab

Overview

This project demonstrates how to create data visualizations using PandasAI within a Google Colab environment. It showcases the power of combining pandas for data manipulation with AI-assisted visualization techniques.

Features

• Data preprocessing using pandas
• AI-assisted visualization creation with PandasAI
• Implementation in Google Colab for easy accessibility and collaboration

Requirements

• Google Colab account
• Python 3.x
• PandasAI library

Installation

Provide instructions on how to set up the project in Google Colab, including any necessary Python Install Package (pip).

!pip install pandasai

Usage

Explain how to use your notebook, including:

1. How to load the data
2. Key functions or cells for creating visualizations
3. Examples of visualizations that can be created

Example Visualizations

Here are some sample visualizations created by this project:

	This line chart displays daily revenue trends over a three-month period, showing fluctuations and patterns in sales performance.
	This bar chart compares the total revenue generated by different payment methods, including cash, credit card, and e-wallet transactions.
	This pie chart illustrates the distribution of revenue across various payment types, providing a clear breakdown of the percentage contribution of each method.

These visualizations were generated using PandasAI in our Google Colab notebook. They demonstrate the capability of our project to create insightful and visually appealing data representations.