https://github.com/pcastiglione99/datatool

Intuitive and user-friendly application designed for exploring, analyzing, and enhancing datasets through newly identified metrics
https://github.com/pcastiglione99/datatool

Last synced: 13 days ago
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Intuitive and user-friendly application designed for exploring, analyzing, and enhancing datasets through newly identified metrics

• Host: GitHub
• URL: https://github.com/pcastiglione99/datatool
• Owner: pcastiglione99
• Created: 2024-12-19T12:45:37.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2025-01-11T19:04:58.000Z (about 1 month ago)
• Last Synced: 2025-01-11T20:18:44.919Z (about 1 month ago)
• Language: Python
• Homepage:
• Size: 2.63 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://datatool-app.streamlit.app)

# DataTool

![DataTool](./datatool.gif)

## Description

This repository contains an intuitive and user-friendly application designed for exploring, analyzing, and enhancing datasets through newly identified metrics. Built using **Streamlit**, this interactive tool provides a streamlined workflow for evaluating data quality, editing datasets, and generating actionable insights during the data preparation phase.

## Features

- **Simplified Interface**: Effortless navigation and usability, ideal for both beginners and advanced users.

- **Metric Exploration**: Analyze your dataset with innovative metrics and interpret results easily.

- **Dataset Upload**: Seamlessly import datasets for evaluation and editing.

- **Data Analysis**: Generate instant insights based on the selected metrics.

- **Metrics Summary**: View detailed summaries and visualizations for each metric.

- **Dataset Editing**: Create modified versions of your data to enhance experimentation and analysis.

- **Multi-page Organization**: Dedicated pages for:

  - **Dataset Upload**

  - **Analysis**

  - **Summary of Metrics**

  - **Editing**

## Getting Started

### Checkout the demo app

[DataTool](https://datatool-app.streamlit.app)

### Install

1. Clone the repository:

    ```bash

    git clone https://github.com/pcastiglione99/DataTool.git

    ```

2. Install dependencies:

    ```bash

    pip install -r requirements.txt  

    ```

3. Run the application:

    ```bash

    streamlit run App/🏠_Home.py

    ```