Hello community of DQ!
So I’m in the process of optimizing my GitHub portfolio, using Vik’s blog post on how to share one’s projects, and while adding some of the earlier projects from Dataquest this question occurred to me:
Most of my projects are just simple story-telling with Data projects in .ipynb format (including those done on R), with no manual installation or running steps required on the viewer’s end, since the .ipynb files render automatically on GitHub.
In Vik’s blog post, he provides these links on his apartment finder and loan prediction projects as examples. In his README.md file, he extensively talks about installation, settings, configurations, deployment, and trouble-shooting, etc of his code.
My concern is that almost none of this applies to most of my projects. For instance here is my README.md for the Employee Exit Analysis project, and here’s the one for the SQL in R projects. As you can see most of what I’m doing is simply talking about my thought process and linking the graphs present in the main .ipynb files. I feel like I’m just repeating the “story-telling” that was already told in the .ipynb file. The actual .ipynb files contain all the full data story-telling info too of course, but my concern is that the length of the README.md might deter people from on the main .ipynb files to check out my code.
And then going back much earlier, this here is my very first guided project that made me fall in love with Dataquest, but the README.md file here just tells a shorter “story” with data that was told in the actual code. It’s just entirely text. It feels like I’m doing something very inoptimally.
Any help would be appreciated, and if anyone could comment on the rest of my GitHub (which at the moment is almost exclusively Dataquest projects!) that would be amazing too.