🚀 AI Data Analyst Pro

An advanced AI-powered data analytics web app built with Streamlit and Google Gemini API. Upload any CSV or Excel dataset and unlock full exploratory analysis, forecasting, clustering, outlier detection, storytelling, and PDF export — all in plain English.

---

🖥️ Live Demo

Deploy free on Streamlit Cloud — see setup instructions below.

---

✨ Features

Tab	Feature
💬 Chat & AI	Natural language → exact chart (Gemini picks columns automatically) + suggested follow-up questions
📈 Interactive Charts	Histogram, Scatter, Line, Box, Bar with color grouping + Correlation Heatmap
📊 Auto Visualizations	Auto-generated distribution, outlier, missing value, and category charts
🔴 Outlier Detection	Isolation Forest ML — highlights anomalous rows, per-column box plots, downloadable outlier CSV
🔮 Forecasting	Linear regression trend forecasting on any numeric column with forecast table
🧩 Clustering	KMeans auto-grouping — scatter by cluster, pie chart, cluster stats, downloadable result
🔬 EDA	Column health report, skewness/kurtosis, scatter matrix (pairplot), normal curve overlay, missing heatmap
📖 Storytelling	Gemini writes a full narrative (4 styles) — Overview, Trends, Findings, Red Flags, Recommendations
📥 Export	Cleaned CSV, Chat history TXT, Stats TXT, PDF report with pinned charts embedded

---

🛠️ Tech Stack

Layer	Technology
Frontend	Streamlit
AI / LLM	Google Gemini 2.5 Flash
Data Processing	Pandas, NumPy
Visualization	Plotly
Machine Learning	Scikit-learn (IsolationForest, KMeans, LinearRegression)
PDF Generation	ReportLab
Language	Python 3.10+

---

⚙️ Setup & Run Locally

1. Clone the repository

git clone https://github.com/YOUR_USERNAME/ai-data-analyst-pro.git
cd ai-data-analyst-pro

2. Install dependencies

pip install -r requirements.txt

3. Get your free Gemini API key

• Go to aistudio.google.com
• Sign in with Google → Create API Key → Copy it

4. Run the app

streamlit run app.py

5. Open in browser

http://localhost:8501

---

🌐 Deploy Free on Streamlit Cloud

1. Push this repo to GitHub
2. Go to share.streamlit.io
3. Connect your GitHub account → Select this repo
4. Set main file path as app.py
5. Click Deploy — you get a public URL instantly!

⚠️ Do NOT hardcode your API key. Enter it in the sidebar at runtime.

---

📁 Project Structure

ai-data-analyst-pro/
├── app.py              # Main Streamlit application (1200+ lines)
├── requirements.txt    # Python dependencies
├── sample_data.csv     # Sample dataset to test the app
├── .gitignore          # Files to exclude from GitHub
└── README.md           # This file

---

🚀 How to Use

1. Enter your Gemini API key in the sidebar
2. Upload a CSV or Excel file (or use sample_data.csv)
3. Explore each tab:
   • Chat — ask "show me salary distribution" → AI picks the right chart automatically
   • EDA — get full column health report, pairplot, skewness analysis
   • Outliers — click Run Outlier Detection → see anomalous rows highlighted
   • Forecast — pick any numeric column → predict future values
   • Clustering — set K → auto-group rows into clusters
   • Storytelling — click Generate Story → get a full narrative about your data
   • Export — pin charts → generate PDF report with charts embedded

---

📸 Screenshots

Add screenshots of your app here after deploying.

---

👤 Author

Thalari Gresu Raju
B.Tech – Artificial Intelligence & Machine Learning
Vignan's Lara Institute of Technology and Science, JNTUK
📧 talarigresuraju@gmail.com

---

📄 License

MIT License — free to use, modify, and distribute.

---

⭐ If this project helped you, give it a star!

"# AI-Data-Analyst-Pro"