DATA ANALYSIS MODERN STACK

Introduction 📚

This repository contains an example of a modern data analysis stack. The stack is composed of the following tools:

🚀 FastApi: A modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.
🐼 Pandas: A fast, powerful, flexible and easy to use open-source data analysis and data manipulation library built on top of the Python programming language.
💬 PandasAI: A library that provides a simple way to use machine learning models with Pandas DataFrames.
💫 Astro: A modern frontend framework for building modern web applications with JavaScript, HTML, and CSS.

PandasAI 🐼💬

PandasAI is a library that provides a simple way to use machine learning models with Pandas DataFrames. It is built on top of the Pandas library and provides a simple interface for training and using machine learning models with Pandas DataFrames. Thanks to PandasAI, this project provides to the user a chat-bot that can answer questions about the data. The chat-bot is built using the FastApi framework and the PandasAI library, and it is served as a web application using the Astro frontend framework.

Before you start 📋

create a uploads directory in the api directory to avoid errors on application startup.

Quick Start 👷‍♂️

To run the project, you need to have Docker installed on your machine. Then, you can run the following commands:

docker-compose up

This will start Astro frontend and FastApi backend. You can access the web application at http://localhost.

Development 🛠️

To improve the project you can develop the frontend and the backend separately. All the frontend code is located in the app directory, and all the backend code is located in the api directory.

License 📜

This project is licensed under the MIT License - see the LICENSE file for details.