Data Analysis and Visualization Tool This is a Python-based web application that allows users to upload datasets, analyze data, and create visualizations interactively. The tool is designed for ease of use and provides a simple interface to perform basic data analysis and generate visualizations.
Features Upload CSV Files: Users can upload datasets in CSV format. Data Analysis: Automatically generates summary statistics for the uploaded dataset. Visualization Options: Scatter Plots Bar Charts Histograms Interactive GUI: Intuitive interface built with Flask for smooth user interaction. Requirements To run this project, you need the following installed on your system:
Python 3.7 or higher pip (Python package installer) Python Libraries Install the required dependencies using the following command:
bash Copy Edit pip install -r requirements.txt Dependencies include:
Flask Pandas Matplotlib Seaborn Installation Clone the repository:
bash Copy Edit git clone https://github.com/your-username/data-visualization-tool.git cd data-visualization-tool Set up a virtual environment (optional but recommended):
bash Copy Edit python3 -m venv venv source venv/bin/activate # On Windows, use venv\Scripts\activate Install dependencies:
bash Copy Edit pip install -r requirements.txt Run the application:
bash Copy Edit python app.py Open your web browser and navigate to:
cpp Copy Edit http://127.0.0.1:5000 Usage Upload a Dataset: On the homepage, upload a CSV file. View Data Summary: After uploading, view basic summary statistics of the dataset. Generate Visualizations: Select the type of visualization and columns for the X and Y axes to create a chart. Folder Structure php Copy Edit Data-Visualization-Tool/ ├── app.py # Main application script ├── static/ # Static files (e.g., CSS, JavaScript) ├── templates/ # HTML templates ├── uploads/ # Directory for uploaded CSV files ├── requirements.txt # Python dependencies └── README.md # Project documentation Screenshots Homepage Upload a CSV file to get started.
Data Analysis View the summary of your dataset.
Visualization Generate beautiful charts based on your data.
Future Enhancements Add support for more visualization types (e.g., line plots, box plots). Implement data cleaning and preprocessing options. Allow users to download visualizations as images. Add machine learning model integration for predictive analysis. License This project is licensed under the MIT License. See the LICENSE file for more details.
Contributing Contributions are welcome! If you’d like to contribute, please fork the repository and submit a pull request.
Contact For any questions or feedback, please contact:
Name: Alvin Email: alvin@4codex.com GitHub: your-username