DataVizX is a web application that allows users to explore and visualize their data in an Interactive manner. With a sleek and modern user interface, DataVizX makes data visualization a breeze, whether you're a data analyst, a business professional, or just someone who loves playing with data.

• Upload CSV files: Easily upload your data in CSV format to get started.
• Choose your visualization: DataVizX offers a variety of visualization options, including Bar Charts, Pie Charts, Scatter Plots, Line Graphs, and Correlation Matrices.
• Stunning Visuals: DataVizX uses Plotly and Plotly Express to generate interactive and eye-catching visualizations that bring your data to life.
• Responsive and User-Friendly: The web app is designed to be responsive and user-friendly, ensuring a seamless experience on various devices.

To get started with DataVizX, follow these simple steps:

1. Clone this repository to your local machine.
2. Install the required Python packages using pip install -r requirements.txt.
3. Run the app with python app.py.
4. Open your web browser and go to http://localhost:5000 to access the DataVizX web app.

1. Upload your CSV data file using the provided file input.
2. Select the type of visualization you want to create.
3. Click on the respective button to generate the stunning visualization.
4. Enjoy exploring and analyzing your data with DataVizX!

Here's an example of how you can use DataVizX:

1. Upload a CSV file containing historical stock data for various companies.
2. Choose the "Correlation Matrix" visualization type and click on it.
3. DataVizX will generate a beautiful correlation matrix, allowing you to see how the stock prices of all companies are correlated.

• Flask: A lightweight and powerful web framework for Python.
• Pandas: A versatile data manipulation library for Python.
• Plotly and Plotly Express: Interactive graphing libraries for Python.
• HTML and CSS: For the web app's user interface and styling.

Contributions to DataVizX are welcome! If you have any ideas for improvements or new features, feel free to open an issue or submit a pull request.

This project is licensed under the MIT License - see the LICENSE file for details.