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What is running-heatmap?

moresamwilson/running-heatmap — explained in plain English

Analysis updated 2026-05-18

315Jupyter NotebookAudience · generalComplexity · 2/5Setup · easy

In one sentence

A Jupyter notebook that turns your downloaded Strava running data into an interactive multi layer heatmap of your routes.

Mindmap

mindmap
  root((repo))
    What it does
      Strava data heatmap
      Multi layer map
      No API needed
    Tech stack
      Python
      Jupyter Notebook
    Use cases
      Visualize pace by route
      Explore unrun streets
      Compare heart rate
    Audience
      Runners
      Cyclists

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Visualize which routes you run fastest using a pace layer heatmap

USE CASE 2

See which streets in your neighborhood you have never explored

USE CASE 3

Compare heart rate and elevation gain across your recorded runs

What is it built with?

PythonJupyter Notebook

How does it compare?

moresamwilson/running-heatmapkrishnaik06/text-summarization-nlp-projectnvidia/cuopt-examples
Stars315198452
LanguageJupyter NotebookJupyter NotebookJupyter Notebook
Last pushed2024-08-17
MaintenanceStale
Setup difficultyeasyhardmoderate
Complexity2/54/53/5
Audiencegeneraldeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 30min

Requires manually downloading your data export zip from your Strava account settings.

So what is it?

Running Heatmap is a Jupyter Notebook project that turns your Strava running data into an interactive map showing where and how you've run. The problem it solves is that Strava's own heatmap only shows frequency, this tool gives you multiple layers to explore: how often you've run each path, your average pace on each segment, your average heart rate, and how steep the terrain is. You don't need to connect to any API. Instead, you download a zip file of your own data directly from Strava (through their account settings), unzip it, and run the notebook. It processes all your recorded GPS tracks and produces a single self-contained HTML file you can open in any browser. The map lets you switch between six visual layers, frequency on a linear or log scale, pace, heart rate, and two gradient views showing steepness and direction of hills. You would use this if you're a runner or cyclist with historical Strava data and want to visualize your activity patterns in more depth than Strava provides, for example, to see which routes you tend to run faster, where you spend the most time, or which streets in your neighborhood you've never explored. The notebook is written in Python and caches the GPS data after the first parse so re-running with different date filters is fast.

Copy-paste prompts

Prompt 1
Walk me through exporting my Strava data and running it through this notebook
Prompt 2
Explain the difference between the linear and log frequency heatmap layers
Prompt 3
Help me modify the notebook to filter runs by a specific date range
Prompt 4
Show me how the notebook caches parsed GPS data for faster re-runs

Frequently asked questions

What is running-heatmap?

A Jupyter notebook that turns your downloaded Strava running data into an interactive multi layer heatmap of your routes.

What language is running-heatmap written in?

Mainly Jupyter Notebook. The stack also includes Python, Jupyter Notebook.

How hard is running-heatmap to set up?

Setup difficulty is rated easy, with roughly 30min to a first successful run.

Who is running-heatmap for?

Mainly general.

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