Factor Analysis Tool

An interactive web application for exploratory factor analysis with varimax rotation, auto-labeled factors, and rich visualizations.

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About

Factor Analysis Tool is a Streamlit-based web application that allows users to upload datasets (CSV or Excel), select variables, and perform factor analysis with varimax rotation. The tool automatically labels factors based on their highest-loading variables, making results easy to interpret even for non-statisticians.

Key Features

• File Upload — Supports CSV and Excel (.xlsx/.xls) files, plus a built-in demo dataset
• Interactive Variable Selection — Checkbox-based UI with human-readable column names
• Varimax Rotation — Orthogonal rotation for clearer, more interpretable factor loadings
• Auto-Labeled Factors — Factors are automatically named by their top two loading variables
• Comprehensive Output — Variance explained, communalities, correlation matrix, and factor scores
• Visual Analytics — Tabbed visualizations: correlation matrix heatmap, factor loadings bar chart, scree plot, and factor scores scatter plot
• Dark Theme — Polished dark UI with teal accents and custom-styled charts

Tech Stack

Category	Technology
Frontend	Streamlit
Backend	Python 3.13
Analytics	scikit-learn, NumPy, Pandas, SciPy
Visualization	Matplotlib
Package Manager	uv

Architecture

┌─────────────────────────────────────────────┐
│              Streamlit UI                    │
│  ┌──────────┐  ┌────────────┐  ┌─────────┐ │
│  │  Sidebar  │  │  Checkbox  │  │ Charts  │ │
│  │ Upload /  │  │  Factor    │  │ Bar +   │ │
│  │ Theme     │  │  Selector  │  │ Scatter │ │
│  └──────────┘  └────────────┘  └─────────┘ │
├─────────────────────────────────────────────┤
│            Analysis Engine                   │
│  StandardScaler → FactorAnalysis → Varimax  │
│  → Loadings, Scores, Variance, Communality  │
├─────────────────────────────────────────────┤
│            Data Layer                        │
│  CSV / Excel Upload  │  Demo Dataset         │
└─────────────────────────────────────────────┘

Project Structure

factoranalysis/
├── app.py                 # Main Streamlit application
├── factoranalysis.py      # Reference factor analysis script
├── creditcarddata.csv     # Demo dataset
├── pyproject.toml         # Project configuration & dependencies
├── uv.lock                # Locked dependency versions
├── .python-version        # Python version (3.13)
└── .gitignore

Getting Started

Prerequisites

• Python 3.13+
• uv package manager

Installation

# Clone the repository
git clone https://github.com/alfredang/factoranalysi.git
cd factoranalysi

# Install dependencies
uv sync

Running the App

uv run streamlit run app.py

The app will open at http://localhost:8501.

Usage

1. Choose a data source — Upload your own CSV/Excel file or use the built-in demo dataset
2. Select factors — Check the variables you want to include in the analysis
3. Configure — Adjust the number of factors to extract
4. Run — Click "Run Factor Analysis" to see results
5. Interpret — Review factor loadings, variance explained, communalities, and visualizations

Contributing

Contributions are welcome!

1. Fork the repository
2. Create a feature branch (git checkout -b feature/my-feature)
3. Commit your changes (git commit -m 'Add my feature')
4. Push to the branch (git push origin feature/my-feature)
5. Open a Pull Request

Acknowledgements

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