{"id":19218554,"url":"https://github.com/donmaruko/flask-data-analysis","last_synced_at":"2026-05-03T23:33:04.230Z","repository":{"id":180322343,"uuid":"664949534","full_name":"donmaruko/Flask-Data-Analysis","owner":"donmaruko","description":"Flask API for statistical calculations. Data analysis, cleansing, visualization, and manipulation. 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It includes operations for cleansing text, performing statistical calculations, visualizing data, and more.\n\n## Table of Contents\n\n- [Installation](#installation)\n- [Usage](#usage)\n- [Endpoints](#endpoints)\n- [Contributing](#contributing)\n\n## Installation\n\n1. Clone this repository to your local machine:\n```shell\ngit clone https://github.com/donmaruko/Flask-Data-Analysis.git\n```\n\n2. Install the required Python packages listed in the `requirements.txt` file:\n```shell\npip install -r requirements.txt\n```\n\n3. Start the Flask application\n```shell\npython API.py\n```\n\n4. The application will be accessible at `http://localhost:8000`.\n\n## Endpoints\n\nThe API endpoints provided by this application are documented using Swagger. You can access the Swagger documentation by visiting `http://localhost:8000/apidocs/` while the application is running.\n\n### Text-Related Endpoints:\n\nThe application expects data files in CSV format for data analysis and text files for text manipulation. You can upload these files to the corresponding endpoints for processing.\n\n- `/cleanse_text`: Cleanses text by removing non-alphanumeric characters.\n- `/cleanse_text_file`: Cleanses text from an uploaded file.\n- `/multiply_numbers`: Multiplies two numbers.\n- `/reverse_text`: Reverses the order of characters in text.\n- `/count_words`: Counts the number of words in text.\n\n### Data-Visualization Endpoints:\n\n- `/analyze_data`: Analyzes data from an uploaded CSV file.\n- `/visualize_data`: Visualizes data distribution from an uploaded CSV file.\n- `/generate_pie_chart`: Generates a pie chart for a specific column in a CSV file.\n- `/generate_word_cloud`: Generates a word cloud from text data.\n- `/frequency_word_cloud`: Generates a word cloud based on word frequencies.\n- `/visualize_skewness`: Visualizes skewness for a specific column.\n- `/visualize_kurtosis`: Visualizes kurtosis for a specific column.\n\n### Git Endpoints:\n\n- `/git_pull`: Performs a Git pull to update the repository.\n- `/git_push`: Performs a Git push to push changes to the repository.\n\nPlease refer to the Swagger documentation for more details on how to use these endpoints.\n\n## Contributing\n\nContributions are welcome! If you have any suggestions, bug reports, or feature requests, please create an issue or submit a pull request.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdonmaruko%2Fflask-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdonmaruko%2Fflask-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdonmaruko%2Fflask-data-analysis/lists"}