Fragments of Data Cleaning Chapter

This PR adds the first few sections of the Data Cleaning chapter. Specifically,

01-intro.md containing a brief overview and learning objectives.
02-reshaping-data.md discussing long and wide data and transposition.
03-tidying-data.md discussing row and column filtering, summary statistics, grouping, sorting, etc.
Makefile that builds html versions of the markdown documents including execution. We won't need this to present the course, but it's a nice sanity check that the code in the notebooks actually runs.
requirements.in and requirements.txt which specified the versions of various python packages to avoid runtime environment drift.
.github/workflows/python-markdown.yml which sets up a python environment and executes the notebooks in CI. I may need a few iterations to get it to build; sorry about the inbox noise.

A few notes:

I've stuck the files in a folder for the chapter to keep things organized and used .md extensions because the content isn't R. I don't know if that messes with the ottr build?
Thought I'd get your input on the first few sections of the chapter before committing to the remaining sections. All input welcome!
I've omitted the "What is Tidy Data?" section because it's not Python-specific and already well covered in the existing course.

datatrail-jhu / python