Data Analysis App

📌 Overview

This is a Streamlit-based Data Analysis App that allows users to upload, explore, analyze, and visualize datasets easily. The app provides multiple functionalities, including:

• Uploading datasets
• Exploring data (shape, columns, statistics, missing values, etc.)
• Viewing value counts of categorical variables
• Performing group-by operations
• Generating various visualizations (line chart, bar chart, scatter plot, etc.)

🚀 Features

✅ Upload Data: Supports CSV file uploads for analysis. ✅ Explore Data: Displays dataset structure, summary statistics, and missing values. ✅ Value Counts: Shows frequency distribution of categorical columns. ✅ Group By: Performs aggregation operations on selected columns. ✅ Visualizations: Generates multiple chart types using Matplotlib and Plotly.

---

🏗️ Project Structure

📂 DataXplorer
│── main.py                 # Main entry point of the app
│── data_upload.py          # Handles file upload functionality
│── data_exploration.py     # Displays dataset structure and stats
│── value_counts.py         # Shows frequency distribution of categorical data
│── group_by.py             # Performs group-by and aggregation operations
│── visualizations.py       # Generates different types of charts
│── requirements.txt        # Lists required Python dependencies
│── README.md               # Project documentation

---

🛠️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/Danyal-Rana/DataXplorer.git
cd DataXplorer

2️⃣ Create Virtual Environment (Optional but Recommended)

python -m venv venv
source venv/bin/activate  # On macOS/Linux
venv\Scripts\activate     # On Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run the App

streamlit run main.py

---

📊 Usage Guide

1️⃣ Open the app in a browser once Streamlit starts. 2️⃣ Navigate using the sidebar to upload and analyze data. 3️⃣ Select options to explore, group, or visualize data. 4️⃣ Generate plots using different charting options.

---

📦 Dependencies

The app requires the following Python libraries:

• streamlit
• pandas
• matplotlib
• plotly

All dependencies are listed in requirements.txt.

---

📜 License

This project is open-source under the MIT License.

---

🤝 Contributing

1. Fork the repository.
2. Create a new branch (feature/your-feature-name).
3. Commit your changes and push to your branch.
4. Open a Pull Request.

---

📞 Contact

For any issues or suggestions, feel free to reach out!

📧 Email: [email protected]
🔗 GitHub: Danyal Rana