https://github.com/hecatops/insightbench
Insight Bench is a web-based CSV analysis tool built with Streamlit, designed for quick, effortless exploration of your CSV files. Simply upload your file and get instant insights without needing any setup or coding.
https://github.com/hecatops/insightbench
data-visualization exploratory-data-analysis python shadcn-ui streamlit
Last synced: 10 months ago
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Insight Bench is a web-based CSV analysis tool built with Streamlit, designed for quick, effortless exploration of your CSV files. Simply upload your file and get instant insights without needing any setup or coding.
- Host: GitHub
- URL: https://github.com/hecatops/insightbench
- Owner: hecatops
- License: mit
- Created: 2024-10-17T15:21:46.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-09T05:46:42.000Z (about 1 year ago)
- Last Synced: 2025-05-07T15:39:39.719Z (11 months ago)
- Topics: data-visualization, exploratory-data-analysis, python, shadcn-ui, streamlit
- Language: Python
- Homepage: https://insightbench.streamlit.app/
- Size: 166 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# What's in my CSV? 📊
**What's in my CSV?** is a web-based CSV analysis tool built with Streamlit, designed for quick, effortless exploration of your CSV files. Simply upload your file and get instant insights without needing any setup or coding. 🚀
---
## Features ✨
- **Dataset Overview** 🗂️: Get a quick summary of your dataset's dimensions (rows and columns).
- **Data Preview** 🔍: View the first 10 rows of your data.
- **Column Details** 🧠: See information about all columns, including data types and null values.
---
## Usage 🛠️
To use the **What's in my CSV?** Streamlit app, follow these steps:
1. **Clone the Repository** 📥:
```bash
git clone https://github.com/aditi-manthri/whatsinmycsv.git
cd whatsinmycsv
```
2. **Set Up a Virtual Environment** 🌱 (Optional but Recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. **Install Required Packages** 📦:
```bash
pip install -r requirements.txt
```
4. **Run the Streamlit App** 🚀:
```bash
streamlit run streamlit_app.py
```
5. **Access the App** 🌐:
Open your web browser and go to [http://localhost:8501](http://localhost:8501).
---
## Contributing 💡
We welcome contributions! If you have any suggestions or improvements, feel free to open an issue or submit a pull request. 🤝
---
## License 📜
This project is licensed under the **MIT License**.
---
### 🌟 **Enjoy Exploring Your CSV Files!** 🌟
Happy analyzing! ✨📊