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https://github.com/abdurrehman2003/data-sweeper

Data Sweeper: A Streamlit web app for quick CSV/Excel conversions, data cleaning, and simple visualizations.
https://github.com/abdurrehman2003/data-sweeper

data-cleaning data-transformation data-visualization spreadsheet-tools streamlit-web-app

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Data Sweeper: A Streamlit web app for quick CSV/Excel conversions, data cleaning, and simple visualizations.

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# Data Sweeper

Data Sweeper is a Streamlit web application that allows you to:

* **Transform files:** Convert between CSV and Excel formats.
* **Clean data:** Remove duplicates and fill missing values.
* **Visualize data:** Generate bar charts.
* **Select columns:** Choose specific columns to work with.

## Features

* **File Upload:** Upload CSV and Excel files.
* **Data Preview:** View a preview of your data in a table.
* **Data Cleaning:**
* Remove duplicate rows.
* Fill missing numerical values with the mean.
* **Column Selection:** Choose specific columns for processing.
* **Data Visualization:** Generate bar charts of numerical columns.
* **File Conversion:** Convert files between CSV and Excel formats.
* **Easy Download:** Download the processed files.

## Usage

1. **Upload Files:** Use the sidebar to upload your CSV or Excel files.
2. **Data Preview:** View the data preview on the main page.
3. **Data Cleaning:** Check the "Clean Data" box and use the buttons to remove duplicates or fill missing values.
4. **Column Selection:** Select the columns you want to keep.
5. **Data Visualization:** Check the "Show Bar Chart" box to generate a bar chart.
6. **File Conversion:** Choose the desired output format (CSV or Excel) and click "Convert."
7. **Download:** Click the "Download" button to save the converted file.

## Installation

1. **Clone the Repository:**

```bash
git clone [https://github.com/Abdurrehman2003/data-sweeper.git](https://github.com/Abdurrehman2003/data-sweeper.git)
cd data-sweeper
```

2. **Create a Virtual Environment (Recommended):**

```bash
python -m venv venv
```

3. **Activate the Virtual Environment:**

* **Windows:**

```bash
venv\Scripts\activate
```

* **macOS/Linux:**

```bash
source venv/bin/activate
```

4. **Install Dependencies:**

```bash
pip install -r requirements.txt
```

5. **Run the App:**

```bash
streamlit run app.py
```

## Deployment

This app can be deployed on Vercel:

1. Push your code to a GitHub repository.
2. Create a Vercel account.
3. Import your GitHub repository into Vercel.
4. Vercel will automatically build and deploy your app.

## Contributing

Feel free to contribute to this project by submitting pull requests or opening issues.

## License

This project is licensed under the [MIT License](LICENSE)