National Parks Scraping Project

Welcome

This website was created by Gunnar Griffith and Elijah Barnes as part of our Data Science Process Final Project.

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Project Overview

This project explores long-term attendance trends across U.S. National Parks. It combines data from official APIs and custom web scraping to build an updated, reproducible dataset.

• A reproducible Python package: nationalparksdata
• A full data pipeline for generating updated annual datasets
• Interactive visual analysis through a Streamlit application

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Resources

GitHub Repository

Access the full source code and documentation here:
GitHub Repository

Python Package

We built a pip-installable package called nationalparksdata that allows users to reproduce and update the dataset annually.

A full tutorial for installation and usage is included in the repository.

Interactive App

We developed a Streamlit application to visualize park attendance trends and explore the dataset interactively.

Written Report

Link to the written report summarizing our findings and methodology.
Written Report

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Date Last Updated

April 22, 2026