https://github.com/apdo60311/regression-analyzer
A web application built using the Flask framework, designed to analyze and visualize data related to global happiness. The application allows users to upload multiple datasets, preprocess the data, select a machine learning model, train the model, and evaluate its performance.
https://github.com/apdo60311/regression-analyzer
flask regression regression-analysis
Last synced: 5 months ago
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A web application built using the Flask framework, designed to analyze and visualize data related to global happiness. The application allows users to upload multiple datasets, preprocess the data, select a machine learning model, train the model, and evaluate its performance.
- Host: GitHub
- URL: https://github.com/apdo60311/regression-analyzer
- Owner: apdo60311
- Created: 2024-05-08T19:20:15.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-18T19:07:28.000Z (about 2 years ago)
- Last Synced: 2025-08-12T12:44:58.854Z (11 months ago)
- Topics: flask, regression, regression-analysis
- Language: HTML
- Homepage:
- Size: 2.14 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Regression Analyser
Regression analyser is a Flask web application that allows users to perform regression analysis on their data. It provides a user-friendly interface for uploading data files, selecting independent and dependent variables, and running various regression models. The application generates detailed reports with visualizations, model summaries, and plots to help users understand the relationships between variables.
## Features
1. Read datframe files as csv, xlsx, and more
2. Explore data and perform some data preprocessing tasks
3. Building simple/multiple regression model
4. Plot model's result
5. Also contains Earth visualization (in case dataframes with country column)
## Folder Structure
* [app/](.\happiness-regression\app)
* [scripts/](.\happiness-regression\app\scripts)
* [static/](.\happiness-regression\app\static)
* [templates/](.\happiness-regression\app\templates)
* [app.py](.\happiness-regression\app\app.py)
* [data/](.\happiness-regression\data)
* [2015.csv](.\happiness-regression\data\2015.csv)
* [2016.csv](.\happiness-regression\data\2016.csv)
* [2017.csv](.\happiness-regression\data\2017.csv)
* [2018.csv](.\happiness-regression\data\2018.csv)
* [documentation/](.\happiness-regression\documentation)
* [notebooks/](.\happiness-regression\notebooks)
* [regression_model.ipynb](.\happiness-regression\notebooks\regression_model.ipynb)
* `app/` folder contains web application files.
* `scripts/` folder contains all scripts that used in the app.
* `static/` folder contains images, css, and javascript.
* `templates/` folder contains all html pages
* `app.py` is the main script that run the web application
* `data/` containes happiness dataframe for testing the application
* `notebooks/` containes jupyter notebooks
### Installation
1. Clone the repository: `git clone https://github.com/apdo60311/regression-analyzer`
2. Navigate to the project directory: `cd regression-analyzer`
3. Create a virtual environment: `python -m venv env`
4. Activate the virtual environment:
* On Windows: `env\Scripts\activate`
* On Unix or Linux: `source env/bin/activate`
5. Install the required packages: `pip install -r requirements.txt`
### Usage
1. Run the Flask application: `flask run` or `python app.py`
2. Open your web browser and visit `http://localhost:5000`
### Contributing
Contributions are welcome! Please follow these steps:
1. Fork the repository
2. Create a new branch: `git checkout -b my-feature-branch`
3. Make your changes and commit them: `git commit -m 'Add some feature'`
4. Push to the branch: `git push origin my-feature-branch`
5. Submit a pull request
### License
This project is licensed under the [MIT License](LICENSE).
### Contact
If you have any questions or suggestions, feel free to reach out to [apdo60311@gmail.com](apdo60311@gmail.com).