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Data Analysis Platform (ongoing development)

Screenshot from 2024-12-20 19-03-39

A comprehensive data analysis platform that enables users to import, transform, analyze, and model data for machine learning projects. A new chatbot feature now allows querying and analyzing the dataset in natural language, making the platform more intuitive for users.

Description

This platform provides a suite of tools to streamline the data analysis process, from data import and transformation to training and testing machine learning models. A new chatbot feature allows users to interact with the data using natural language queries, making it more accessible for non-technical users.

Features

  • Data Import: Import data from various sources, including CSV, Excel, and databases.
  • Data Transformation: Transform and preprocess data to prepare it for machine learning algorithms.
  • Intelligent Chatbot: Query and analyze data using natural language:
    • Describe me the dataset.
    • Propose me a data analysis process.
    • Average column1 group by column2.
  • Univariate Analysis: Perform univariate analysis to understand the distribution of individual variables.
  • Bivariate Analysis: Perform bivariate analysis to understand the relationships between pairs of variables.
  • Machine Learning: Train and test machine learning models using various algorithms, including classification, regression, clustering, and more.

Technologies Used

  • Python
  • Dash
  • Pandas
  • Plotly
  • Scikit-learn
  • LLM API

Installation

To install and run this project, follow these steps:

  1. Clone the repository: git clone https://github.com/yaiciwalid/Data-analysis-app.git
  2. Create a virtual environment: python -m venv env
  3. Activate the virtual environment: source env/bin/activate (Linux/Mac) or env\Scripts\activate (Windows)
  4. Install the requirements: pip install -r requirements.txt
  5. Run the application: python app.py

Usage

Once the application is running, you can access it in your web browser at http://localhost:8050.

Contributing

If you would like to contribute to this project, please follow these guidelines:

  1. Fork the repository
  2. Create a new branch: git checkout -b feature/my-feature
  3. Make your changes and commit them: git commit -am 'Add my feature'
  4. Push to your fork: git push origin feature/my-feature
  5. Submit a pull request

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