📊 Data Analyzer

---

🧠 Overview

Data Analyzer is an interactive web app built with Streamlit that lets users upload CSV datasets, explore insights, visualize patterns, and download cleaned data — all in one place.

🎯 Ideal for students, data beginners, and analysts who want quick insights without writing a single line of code!

---

🚀 Features

✅ Upload CSV files easily
✅ View dataset summary (rows, columns, datatypes, and missing values)
✅ Clean missing data (drop or fill)
✅ Generate visualizations (line, bar, scatter, histogram, heatmap, etc.)
✅ Correlation and statistical insights
✅ Download cleaned or analyzed dataset

---

🧰 Tech Stack

Category	Tools
💻 Language	Python
🧱 Framework	Streamlit
📊 Libraries	Pandas, NumPy, Matplotlib, Seaborn
☁️ Hosting	Streamlit Cloud

---

🌐 Live Demo

🎯 Try it now: Data Analyzer App

---

🖼️ Preview

Here’s a look at the Data Analyzer interface 👇

Data Preview	Data Summary	Visualization

---

⚙️ Installation Guide

Run the following commands to set it up locally 👇

# Clone the repository
git clone https://github.com/Akashram2007/Data-Analyzer.git

# Navigate to project folder
cd Data-Analyzer

# Install required packages
pip install -r requirements.txt

# Start the Streamlit app
streamlit run app.py

---

📁 Folder Structure

Data-Analyzer/
│
├── app.py
├── requirements.txt
├── README.md
├── Data Preview.png
├── Data Summary.png
└── Data Visualization.png

---

💡 Future Enhancements

🚧 Add user authentication
🚧 Include advanced visualizations (boxplots, pairplots, etc.)
🚧 Add machine learning insights

---

🧑‍💻 Author

Akash R
📧 akashgram0103@gmail.com
🔗 LinkedIn
🔗 GitHub

---

⭐ Support

If you find this project useful, don’t forget to give it a ⭐ star on GitHub — it helps a lot!