Last week's data on Adoptable Dogs: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-12-17

This week's Christmas Music data: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-12-24

SPOILER WARNING, you may not want to read below before listening to the episode.

Twas the first Tidy Tuesday, in 2018.
And my R data options were getting quite lean.
I'd plotted gas mileage by displacement and cyls,
I'd tired of iris; from diamonds, no thrills.

My columns were features, my rows observations.
My plots weren't quite perfect (they lacked annotations).
But I'd learned all I could from Garrett and Hadley,
What I needed was data, and I needed it badly.

Then R4DS Online Learning Community
Announced a new R practice opportunity!
They'd post a new dataset once every week
And, most importantly, 'twould be unique!

The goal was for learners from novice to whiz
To use that new data for their own dataviz.
And whether those vizes were bars, lines, or maps
We'd share our R code (on github, perhaps).

We'd try out new packages, practice and play,
Then share in a tweet hashtag TidyTuesday.
And the rstats community would add their advice.
With new tips and tricks (don't worry, they're nice)!

So I started to read tweets by @thomas_mock
And I waited each Monday (around 2 o'clock).
Then I'd download the new dataset csv,
And read Thomas's tweet to see what it might be.

"Here's comics! Here's Star Wars! Here's US tuition!"
"Here's how NFL players are paid by position!"
"Here's video games! Here's Roman bloodlines!"
"Here's UFO sightings! And ratings of wine!"

And my plots? They improved! With new themes and palettes.
And Thomas kept posting brand new datasets.
I heard Thomas proclaim as he tweeted his tweet,
"It's Tidy Tuesday, y'all! Now go code something neat!"