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:

   git clone https://github.com/yourusername/data-analyzer.git
   cd data-analyzer

2. Install the required packages:

   pip install pandas matplotlib

Usage

1. Run the application:

   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 file for details.