What I learned: Python for Data Journalists

Last night, I finished up a free online course on using the Python programming language for data journalism. I was so excited when I saw someone tweet about this course, and extra excited when I saw it was being taught by Ben Welsh, the Los Angeles Times data desk editor.

The course was fantastic because it walked you through the very basics of data analysis with Python using public data about campaign contributions to several propositions on the Nov. 2016 ballot in the state of California, and by the end of the class, I’d published an analysis of the proposition to get rid of the death penalty in California to GitHub.

I’ve taken multiple semester-long programming courses in school that weren’t nearly as productive — those classes focused on Java, which just isn’t the language people are using to do the kind of work I wanted to do. This course also was so much less intimidating than in-person ones I’d taken, and maybe that’s the beauty of taking an online course, where there are no mansplaining lab partners and no comparing myself people who were just getting it more easily than I did.

I’m particularly excited about learning how to publish Jupyter Notebooks to GitHub — I’d seen this end-product on GitHub before and had no idea how people got their work to show up like that.  But look! I did it too:

A screengrab of my published analysis. Click through if you wanna see it. Critiques welcome.

I’m so thankful that Ben and the Knight Center were able to offer this course for free — I learned so much, and I’m excited to keep learning.

Do you know of any good sources of public data I should look at to keep working these Python analysis skills? Tweet at me.

I believe the course is closed now, but the “textbook” (which includes really helpful video lectures) is here, if you wanted to work through it on your own.

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