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An introduction to Python for non-programmers using inflammation data.

This lesson teaches novice programmers to write modular code to perform data analysisusing Python. The emphasis, however, is on teaching language-agnostic principles ofprogramming such as automation with loops and encapsulation with functions,seeBest Practices for Scientific Computing andGood enough practices in scientific computing to learn more.

The example used in this lesson analyses a set of 12 files with simulated inflammationdata collected from a trial for a new treatment for arthritis. Learners are shownhow it is better to automate analysis using functions instead of repeating analysissteps manually.

The rendered version of the lesson is available at:https://swcarpentry.github.io/python-novice-inflammation/.

This lesson is also available inR andMATLAB.

We welcome all contributions to improve the lesson!Maintainers will do their best to help you if you have any questions, concerns,or experience any difficulties along the way.

We'd like to ask you to familiarize yourself with ourContribution Guideand have a look at themore detailed guidelines on proper formatting,ways to render the lesson locally, and even how to write new episodes!

Lesson maintainers areToan Phung andIndraneel Chakraborty.

A list of contributors to the lesson can be found inAUTHORS.

Instructional material from this lesson is made available under theCreative Commons Attribution (CC BY 4.0) license. Except whereotherwise noted, example programs and software included as part of this lesson are made availableunder theMIT license. For more information, seeLICENSE.md.

To cite this lesson, please consult withCITATION.

Software Carpentry is a volunteer project that teaches basic computing skills to researchers since1998. More information about Software Carpentry can be foundhere.

The Carpentries is a registered 501(c)3 non-profit organisation based in Delaware, USA. We are a global communityteaching foundational computational and data science skills to researchers in academia,industry and government. More information can be foundhere.