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With the explosion in fitness tracker popularity, runners all of the world are collecting data with gadgets (smartphones, watches, etc.) to keep themselves motivated. They look for answers to questions like: * How fast, long, and intense was my run today? * Have I succeeded with my training goals? * Am I progressing? * What were my best achievements? * How do I perform compared to others? I exported seven years worth of my training data from [Runkeeper](https://runkeeper.com/). The data is a CSV file where each row is a single training activity. In this project, you'll create import, clean, and analyze my data to answer the above questions. You can then apply the same strategy to your training data if you wish!
- 1Obtain and review raw data
- 2Data preprocessing
- 3Dealing with missing values
- 4Plot running data
- 5Running statistics
- 6Visualization with averages
- 7Did I reach my goals?
- 8Am I progressing?
- 9Training intensity
- 10Detailed summary report
- 11Fun facts
Andrii managed IT teams where he used data to guide his decisions. Before that, he received a Masters in Physics and studied the mathematical modeling of physical processes. He is passionate about Python, data visualization, and running with his dog.
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Lloyds Banking Group
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