An open API service indexing awesome lists of open source software.

https://github.com/yash-kavaiya/eda-website

Easy-to-use web application for performing in-depth exploratory data analysis (EDA). Visualize, understand, and gain insights from your datasets.
https://github.com/yash-kavaiya/eda-website

flask python

Last synced: 2 months ago
JSON representation

Easy-to-use web application for performing in-depth exploratory data analysis (EDA). Visualize, understand, and gain insights from your datasets.

Awesome Lists containing this project

README

          

# EDA Website with CSV Upload and Download Options

## Table of Contents

1. [Introduction](#introduction)
2. [Features](#features)
3. [Requirements](#requirements)
4. [Installation](#installation)
5. [Usage](#usage)
6. [Contributing](#contributing)
7. [License](#license)

---

## 1. Introduction

This is a web application that allows users to perform Exploratory Data Analysis (EDA) on CSV files. Users can upload their datasets, perform EDA operations, and download the generated EDA report in HTML format.

## 2. Features

- **CSV Upload**: Users can upload their CSV files through the website interface.

- **EDA Generation**: The uploaded CSV files will be processed to generate an EDA report in HTML format.

- **Download Options**: Users can download the generated EDA report for further analysis.

## 3. Requirements

- Python 3.x
- Flask
- ydata profiling

## 4. Installation

1. Clone the repository:

```bash
git clone https://github.com/Yash-Kavaiya/eda-website
```

2. Navigate to the project directory:

```bash
cd eda-website
```

3. Install the required Python packages:

```bash
pip install -r requirements.txt
```

## 5. Usage

1. Run the application:

```bash
python app.py
```

2. Open your web browser and go to `http://localhost:5000` to access the EDA website.

3. Upload your CSV file using the provided interface.

4. Once the EDA is complete, you will be provided with a download link to get the generated HTML report.

## 6. Contributing

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

1. Fork the repository.

2. Create a new branch for your feature or bug fix:

```bash
git checkout -b feature_branch
```

3. Make your changes and commit them:

```bash
git commit -m "Description of changes"
```

4. Push your changes to your fork:

```bash
git push origin feature_branch
```

5. Create a pull request on the original repository.

## 7. License

This project is licensed under the [MIT License](LICENSE).

---

Feel free to customize this readme file to better suit your specific project. Make sure to replace placeholder values with your actual project details.