POTUS Economic Scorecard
  • Scorecard
  • About

About

Overview

POTUS Economic Scorecard is an interactive Shiny application that allows users to compare economic performance metrics across different presidential administrations. The app provides visual representations of various economic indicators, including:

  • S&P 500
  • Dow Jones Industrial Average
  • NASDAQ
  • Unemployment Rate
  • Inflation Rate

The app is a static web page that runs entirely in your web browser using shinylive, so it can take a bit to load.

The app is best viewed in landscape mode on a mobile device.

Features

  • Multiple Economic Indicators: Compare performance using S&P 500, Dow Jones, NASDAQ, Unemployment Rate, and Inflation Rate.
  • Flexible Reference Points: Choose between “Inauguration Day” or “Day Before Election” as your reference point.
  • Party Filtering: Filter presidents by political party.
  • Customizable Time Period: Adjust the number of days to display for comparison.
  • Data Export: Download the plot or raw data for your own analysis

How It Works

Historical economic data is downloaded daily and stored in the app GitHub repository. The app loads this data and calculates performance metrics relative to your chosen reference date. For market indices (S&P 500, Dow Jones, NASDAQ), performance is shown as percent change from the reference date. For economic indicators (Unemployment Rate, Inflation Rate), absolute values are displayed.

Data Sources

  • Market data (S&P 500, Dow Jones, NASDAQ) is sourced from Yahoo Finance
  • Economic indicators are sourced from FRED (Federal Reserve Economic Data)

Technology

This application is built using:

  • R Shiny for the interactive web application.
  • shinylive for browser-based execution without a server.
  • Quarto for website publishing.
  • plotly for interactive visualizations.

Local Deployment

To run the app locally:

  1. Clone the repository:

    git clone https://github.com/jhelvy/potus-econ-scorecard.git
    cd potus-econ-scorecard
  2. Open the project in RStudio or run from the R console:

    library(shiny)
    runApp()

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

License

This project is licensed under a CC-BY-SA-4.0 license - see the LICENSE file for details.

 
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