Running Analytics is a small project to generate some analysis through graphical plotting packages (seaborn and matplotlib) in python of activities recorded for users in the strava fitness tracking app. Some potential use cases for these scripts and plots could be for improved training, informed reflection of progress acquired in historical data, and generating cool art.
All of these scripts will utilize the Anaconda software suite, particularly Jupyter Notebooks, to run python for analysis. Additionally the setup will require interacting with the Strava API. This will require generating an API key and some setup, however is fairly straightforward and described in the steps below.
Requirements for the software and other tools to build, test and push
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Clone this repository
- If you need help cloning, check out Github's documentation here: Cloning a Repository
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Visit the link above and download anaconda software suite for your machine
- Once installed, open the jupyter package by searching for Jupyter in the installed directory
- Confirm you can run python code through a simple hello world print statemnent. Cells can be run in a modular sense with the play button at the top or by the keyboard shortcut (cntrl-entr)
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Generate the API key for your account through strava to access your personal data and querying
- Hat tip to anyone whose code is used
- Inspiration
- etc