https://github.com/yashdhirajoza/data-automation-
https://github.com/yashdhirajoza/data-automation-
gssoc24 hackathon hackoberfest hacktoberfest-accepted
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/yashdhirajoza/data-automation-
- Owner: YashDhirajOza
- Created: 2024-06-02T06:22:10.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-19T19:51:16.000Z (8 months ago)
- Last Synced: 2025-05-07T17:14:26.633Z (about 2 months ago)
- Topics: gssoc24, hackathon, hackoberfest, hacktoberfest-accepted
- Language: Python
- Homepage:
- Size: 26.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
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README
# Data Analyzer
Data Analyzer is a Tkinter-based desktop application designed for analyzing CSV files. It allows users to load CSV files, generate detailed reports, and visualize data through histograms and regression plots. The application features a dark theme for better readability and a modern look.
## Features
- Load CSV files and display basic information about the dataset.
- Generate a detailed report including:
- Basic information about the dataset.
- The first 5 rows of the dataset.
- Basic statistics summary.
- Mean, median, and standard deviation of numerical columns.
- Count of missing values in each column.
- Correlation matrix.
- Save the generated report as a text file.
- Visualize data with histograms and regression plots.
- Dark theme for all application windows.
## Requirements
- Python 3.x
- pandas
- tkinter
- matplotlib
## Installation
1. Clone the repository:
```sh
git clone https://github.com/yourusername/data-analyzer.git
cd data-analyzer
```
2. Install the required packages:
```sh
pip install pandas matplotlib
```
## Usage
1. Run the application:
```sh
python data_analyzer.py
```
2. Use the GUI to:
- **Load CSV**: Load a CSV file for analysis.
- **Plot**: Open the plot window to generate histograms or regression plots.
- **Save Report**: Save the generated report as a text file.
### Plotting Data
In the plot window:
- Select the column for the X-axis.
- Select the column for the Y-axis (only for regression plots).
- Choose to plot a histogram or a regression plot.
## Code Overview
### `DataAnalyzerApp` Class
- `__init__(self, root)`: Initializes the main application window and configures the dark theme.
- `load_csv(self)`: Loads a CSV file and generates a report.
- `generate_report(self)`: Generates a detailed report of the loaded dataset.
- `display_report(self)`: Displays the generated report in the text widget.
- `save_report(self)`: Saves the generated report to a text file.
- `open_plot_window(self)`: Opens a new window for plotting data.
- `plot_histogram(self)`: Plots a histogram of the selected column.
- `plot_regression(self)`: Plots a regression plot of the selected columns.
- `display_plot(self, fig, window)`: Displays the plot in the plot window.
### Main Application
- The main application is initialized and run within the `if __name__ == "__main__":` block.
## Screenshots
_Add screenshots of the application here if available._
## Contributing
1. Fork the repository.
2. Create a new branch: `git checkout -b feature-name`.
3. Make your changes and commit them: `git commit -m 'Add feature'`.
4. Push to the branch: `git push origin feature-name`.
5. Submit a pull request.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.