This Power BI dashboard provides a comprehensive analysis of your personal ParkRun journey, offering insights into your performance over time and across different locations.
The dashboard is organized into two main pages, each designed to give you a detailed view of your ParkRun statistics:
This page focuses on your running performance, allowing you to track your times and see how you've progressed.
Lifetime ParkRun Count: See the total number of ParkRuns you've completed.
Fastest Run Time: Discover your personal best time.
Average Run Time: Get an understanding of your typical performance.
Run Time Distribution: A box and whisker plot visualizes the spread and central tendency of your run times.
ParkRun Times by Date/Year: Track your run times over time with detailed views by date and year.
Event and Year Slicers: Easily filter your data to focus on specific events or years.
Example Output: 
Explore your ParkRun adventures geographically and analyze your performance at different courses.
Interactive Map of All ParkRun Locations Attended: Visualize all the different ParkRun events you've participated in on an interactive map.
Unique Location Count: See how many different ParkRun events you've run at.
Fastest Location: Identify the location where you achieved your fastest time.
Favorite (Most Popular) Location: Discover which ParkRun event you've attended the most.
Example Output: 
Getting started with your ParkRun Power BI Dashboard is straightforward! Just follow these steps to set up and visualize your data:
First, download the following three files from this GitHub page:
parkrun.csvparkrun.pbixparkrun_locations.json
Place all three files into the same folder on your computer.
The parkrun.pbix file is your Power BI dashboard. Simply open this file, and it'll load all the visualizations and data models.
The parkrun_locations.json file contains the geographical coordinates for all ParkRun locations, accurate as of June 16, 2025. This file is automatically parsed within Power BI (using Power Query), so you don't need to do anything with it. I'll periodically update this file to keep the location data current.
The parkrun.csv file is where your personal ParkRun results live. Since ParkRun doesn't offer API connectivity or allow web scraping, you'll need to manually update this file with your own data:
- Log in to your ParkRun account.
- Navigate to the "Results" tab.
- Click on "View stats for all parkruns by this parkrunner".
- Copy and paste the entire table (currently titled "All Results") directly into your
parkrun.csvfile.
Once you've updated the parkrun.csv file, simply refresh the data within your Power BI dashboard to see your latest statistics!
Ideally, with all your files in the same folder, you should be able to simply refresh the dashboard (using the Refresh button on the Power BI Home tab) to see your own data. If that's not working, here are a few things to double-check:
Ensure the parkrun_locations data table within Power BI's table layer matches the expected format, especially regarding its headers.
Confirm that your parkrun data table in Power BI has the correct headers and is up-to-date with your latest copied data from the ParkRun website.
For the dashboard to function correctly, these two data tables (entities) need to communicate. Verify that the following relationship is set up in the Model View:
- The 'Event' columns in both
parkrunandparkrun_locationsact as keys and should be linked. - There should be a many-to-one relationship from the
parkrunentity to theparkrun_locationsentity. This makes sense because each ParkRun location can have multiple runs associated with it.
You can manage these relationships using the Manage Relationships button on Power BI's Home ribbon.
Finally I have GitHub Issues open if you find any bugs you can escalate them to me, and GitHub Discussions are also open if you want to suggest new features
This dashboard was created using Microsoft PowerBI Version: 2.144.679.0 64-bit (June 2025)