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san000-1/
pcatry

Name: pcatry
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license: mit title: PCA Finance Dashboard emoji: 📊 colorFrom: blue colorTo: indigo sdk: streamlit sdk_version: "1.32.0" app_file: pca.py pinned: false tags:

PCA Finance Dashboard

Author: ssjs

Overview

This project is an interactive Streamlit dashboard for exploring Principal Component Analysis (PCA) on financial return series.
You can either generate synthetic returns or upload your own CSV of asset returns and inspect:

Scree plot and variance explained
PCA biplot (scores and loadings)
Loading heatmap
Top contributors to the first principal component
Equal-weight portfolio factor exposure

Requirements

Python 3.9+ (3.10 or 3.11 recommended)
The following Python packages:
- streamlit
- pandas
- numpy
- scikit-learn
- plotly

You can install them with:

pip install streamlit pandas numpy scikit-learn plotly

How to Run the Dashboard

Open a terminal (PowerShell, Command Prompt, or any shell).
Change directory into the folder that contains pca.py:

cd "C:\Users\sharm\Downloads\New folder"
Run the Streamlit app:

streamlit run pca.py
After a few seconds Streamlit will print a local URL, for example:

Local URL: http://localhost:8501
Open that URL in your browser to use the dashboard.

Notes

If the default port (8501) is already in use, you can choose another one, e.g.:

streamlit run pca.py --server.port 8505
For reproducible synthetic data, you can adjust the random seed in the sidebar.

san000-1/pcatry