AI Data Analyst

An interactive AI-powered data analysis web application built using Python, Streamlit, Pandas, and Plotly.

This project allows users to upload CSV datasets, automatically inspect the data, generate KPIs, and create interactive visualizations — all through a modern dashboard interface.

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Features

CSV Upload System

• Upload CSV datasets directly from the browser
• Automatic file reading with encoding handling
• Responsive dataset preview

Automatic Dataset Analysis

The application automatically detects:

• Number of rows and columns
• Column data types
• Missing values
• Duplicate rows
• Numeric columns
• Summary statistics

KPI Dashboard

Automatically generated KPI cards including:

• Total Rows
• Total Columns
• Missing Values
• Duplicate Rows
• Numeric Columns

Automatic Visualizations

Interactive charts generated dynamically using Plotly:

• Histogram
• Bar Chart
• Pie Chart

Modern UI

• Dark theme dashboard
• Hero banner section
• Responsive layout
• Interactive visualizations

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Tech Stack

Technology	Purpose
Python	Core programming language
Streamlit	Web application framework
Pandas	Data analysis and processing
Plotly	Interactive visualizations
Openpyxl	Excel file support

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Project Structure

AI_Data_Analyst/
│
├── app.py
├── requirements.txt
├── README.md
│
├── assets/
│   └── banner.jpg
│
└── .streamlit/
    └── config.toml

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Installation

Clone Repository

git clone https://github.com/your-username/AI_Data_Analyst.git

Move Into Project Folder

cd AI_Data_Analyst

Install Dependencies

pip install -r requirements.txt

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Run The Application

streamlit run app.py

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Streamlit Cloud Deployment

This project can be deployed easily using Streamlit Community Cloud.

Deployment Steps

1. Push project to GitHub
2. Login to Streamlit Cloud
3. Connect GitHub repository
4. Select app.py
5. Deploy application

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Current Functionalities

• CSV Upload
• Data Preview
• Dataset Inspection
• KPI Dashboard
• Interactive Charts
• Responsive UI

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Future Improvements

Planned features for future versions:

• AI-generated business insights
• Natural language queries
• Chat-based analytics assistant
• Advanced filtering system
• Downloadable reports
• Automated chart recommendations
• Machine learning integration
• API-based AI integration
• Multi-file support

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Learning Goals Behind This Project

This project is designed to improve skills in:

• Python programming
• Data analysis
• Dashboard development
• Streamlit application building
• Data visualization
• Business intelligence concepts
• AI-powered analytics systems

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Author

Shivam Thakur

📬 Connect With Me

• 💼 LinkedIn: https://www.linkedin.com/in/shivam-thakur-55b167406/
• 📧 Email: dataanalyst.shivamthakur@gmail.com

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License

This project is open-source and available for learning and educational purposes.