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Version control repositories like CVS, Subversion or Git store rich evolution information about a software project. In this project, you'll be challenged to read in, clean up and visualize a real world Git repository dataset of the Linux kernel. With almost 700k commits and thousands of contributors (find out the exact number in this project ;-) ) there are some little data cleaning and wrangling challenges that you'll encounter. But you'll also gain insights about the development activities over the last 13 years. For this Project, you need to be familiar with Pandas `DataFrame`s, especially the `read_csv` and `groupby` functions, as well as working with time series data.
- 2Reading in the dataset
- 3Getting an overview
- 4Finding the TOP 10 contributors
- 5Wrangling the data
- 6Treating wrong timestamps
- 7Grouping commits per year
- 8Visualizing the history of Linux
Software Development Analyst
Markus Harrer is a software engineer who's passionate about improving the way we do software development. He specialized in analysis of software data to show the underlying problems of the symptoms we face on the surface. Markus shares his thoughts and experiences at @feststelltaste on Twitter and on his blog https://feststelltaste.de.
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