{"id":19256637,"url":"https://github.com/sunnybibyan/random_data_generation","last_synced_at":"2025-02-23T17:43:07.003Z","repository":{"id":256768731,"uuid":"856360293","full_name":"SunnyBibyan/Random_Data_Generation","owner":"SunnyBibyan","description":"A project that generates a dataset using various statistical distributions (Normal, Uniform, Exponential, Random Integers, and Binomial) and performs data analysis. 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The dataset includes values from Normal, Uniform, Exponential, Random Integers, and Binomial distributions, allowing for a comprehensive analysis of different types of data.\n\nThe dataset is designed for educational purposes, offering a practical example of how to generate and analyze random data.\n\n## Dataset Generation\n\n### Key Features\n- **Data Sources:** Data is generated using Python libraries such as NumPy and Pandas.\n- **Distributions:**\n  - **Normal Distribution:** Simulates continuous data with a Gaussian distribution.\n  - **Uniform Distribution:** Provides values within a specified range.\n  - **Exponential Distribution:** Models the time between events.\n  - **Random Integers:** Simulates discrete values.\n  - **Binomial Distribution:** Represents binary outcomes.\n- **Statistics:** Descriptive statistics including mean, median, and standard deviation are computed.\n- **Visualizations:** Histograms are created to observe the distribution patterns.\n\n## Tools \u0026 Technologies\n- **Python:** For data generation and analysis.\n- **NumPy:** For numerical operations and random data generation.\n- **Pandas:** For data manipulation and analysis.\n- **Matplotlib:** For plotting visualizations.\n- **Seaborn:** For enhanced data visualization.\n\n## Dataset Information\nThe generated dataset includes the following columns:\n- **Normal Distribution:** Values drawn from a Gaussian distribution.\n- **Uniform Distribution:** Values uniformly distributed between specified limits.\n- **Exponential Distribution:** Values following an exponential distribution.\n- **Random Integers:** Integer values within a specified range.\n- **Binomial Distribution:** Values from a binomial distribution representing binary outcomes.\n\n## Visualizations\nThe project includes histograms for each type of distribution:\n- **Normal Distribution Histogram:** Shows the distribution of values from the Gaussian distribution.\n- **Uniform Distribution Histogram:** Displays the range and frequency of uniformly distributed values.\n- **Exponential Distribution Histogram:** Illustrates the spread of values from the exponential distribution.\n- **Random Integers Histogram:** Visualizes the frequency of discrete integer values.\n- **Binomial Distribution Histogram:** Represents the frequency of binary outcomes.\n\n## Project Structure\n\n### How to Use the Project\n1. **Run the Script:** Execute `App.py` to generate the dataset and visualizations.\n2. **Explore Visualizations:** Use the Streamlit interface to select columns and view histograms.\n3. **Download Data:** Use the download button to save the generated dataset as a CSV file.\n\n## Requirements\n- **Install the necessary Python libraries:**\n  ```sh\n  pip install -r requirements.txt\n## Insights and Recommendations**\n- **Distribution Patterns:** Analyze how different statistical distributions generate data with varying patterns.\n- **Data Analysis:** Utilize the generated dataset for educational purposes, testing, and further analysis.\n  \n## License\nThis project is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.\n\n## Connect with Me\n- **LinkedIn**: [Profile](https://www.linkedin.com/posts/sunny-bibyan)\n- **Contact**: [Sunny Bibyan](mailto:sunnykumar6121997@gmail.com)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsunnybibyan%2Frandom_data_generation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsunnybibyan%2Frandom_data_generation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsunnybibyan%2Frandom_data_generation/lists"}