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https://github.com/otherwa/csvdash
Analyze and visualize CSV data with ease using this Streamlit-powered data analytics tool
https://github.com/otherwa/csvdash
analytics data-analysis huggingface llama-index pandas python statistics streamlit
Last synced: about 2 months ago
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Analyze and visualize CSV data with ease using this Streamlit-powered data analytics tool
- Host: GitHub
- URL: https://github.com/otherwa/csvdash
- Owner: Otherwa
- Created: 2023-09-17T10:52:50.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-08T07:54:19.000Z (10 months ago)
- Last Synced: 2024-04-14T03:24:52.710Z (9 months ago)
- Topics: analytics, data-analysis, huggingface, llama-index, pandas, python, statistics, streamlit
- Language: Python
- Homepage: https://csvdash.streamlit.app/
- Size: 457 KB
- Stars: 6
- Watchers: 1
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: Readme.md
Awesome Lists containing this project
README
# Streamlit CSV Analytics App
This Streamlit app is designed to help you analyze and visualize data from CSV files. It allows you to upload your own CSV data and generate various analytics, including mean, mode, standard deviation, and variance for selected columns.
## Features
- Upload your CSV data.
- Select the columns you want to analyze.
- Calculate and display mean, mode, standard deviation, and variance for the selected columns.
- Visualize your data with interactive charts (you can add this feature if desired).
## Usage
1. **Upload Your CSV File**
- Click the "Choose a CSV file" button to upload your CSV data.
2. **Select Columns for Analysis**
- After uploading the file, use the multiselect dropdown to select the columns you want to analyze.
3. **Calculate Statistics**
- Click the "Calculate Statistics" button to generate analytics for the selected columns.
4. **View Results**
- The calculated statistics will be displayed for each selected column.
## Getting Started
1. Clone this repository to your local machine.
```bash
git clone https://github.com/your-username/streamlit-csv-analytics.git
```
2. Install the required Python packages.
```bash
pip install -r requirements.txt
```
3. Run the Streamlit app.
```bash
streamlit run app.py
```
4. Access the app in your web browser.
```
http://localhost:8501
```
## Dependencies
- Streamlit: [Streamlit Documentation](https://docs.streamlit.io/)
- Pandas: [Pandas Documentation](https://pandas.pydata.org/pandas-docs/stable/index.html)
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- [Streamlit](https://streamlit.io/) for making it easy to create data apps with Python.