README

These are the files for the book Learn to Code with Baseball.

If you're not familiar with Git or GitHub, no problem. Just click the Source code link under the latest release to download the files. This will download a file called ltcwbb-files-vX.X.X.zip, where X.X.X is the latest version.

When you unzip these (note in the book I've dropped the version number and renamed the directory just ltcwbb-files, which you can do too) you'll see four sub-directories: code, data, anki, solutions-to-excercises.

You don't have to do anything with these right now except know where you put them. For example, on my mac, I have them in my home directory:

/Users/nathanbraun/ltcwbb-files

If I were using Windows, it might look like this:

C:\Users\nathanbraun\ltcwbb-files

Set these aside for now and we'll pick them up in chapter 2.

Changelog

v0.4.2 (2021-06-17)

Fixed some scraping in book to match what was in the code (thanks Greg, Nick!)

Fixed typo in exercise 3.3.2 and made changed LAA -> ANA in teams.csv (thanks Lennart and Tim!)

Fixed a few typos + stray football references (thanks Brooks, Mark!)

v0.4.1 (2021-06-16)

Updated visualization section + associated homework problems to use Seaborn 0.11.x (September 2020), which added a new displot function. This means making our distribution plots change from, say:

g = (sns.FacetGrid(df)
     .map(sns.kdeplot, 'mpg', shade=True))

To:

g = sns.displot(df, x='mph', kind='kde', fill=True)

It also opens up some new possibilities (e.g. with plotting empirical CDFs) that I might discuss in a future update.

v0.3.0

Add this changelog, bundle files in an github release vs including with SendOwl.