The #rstats community has given me so much, and I give back enthusiastically! I love this stuff. It's easy to talk and teach about stuff you love ❤️❤️❤️ But you're right, this community is just the best, most generous group ✨

Ok, that's it. Just a story about how much I love R, how much I miss teaching, my love for stats, and my amazing friend on her PhD journey 😌 I hope you spent your weekend doing things that feel magical, too!! 🪄✨
8/8

We've used this in student exercises (using #rstat R) before...
.. embarrassing that Swiss official news casts on the Sechseläuten use this yearly being seemingly serious about its predictive power ... horrifying me every year.

and then .. you did / didn't make it available?

Government spreadsheets sometimes add asterisks next to a few numbers in a large data set. Why worry about that when I can handle it automatically?
x <- c("10.1", "74%", "23*")
as.numeric(x)
[1] 10.1 NA NA
Warning message:
NAs introduced by coercion
readr::parse_number(x)
[1] 10.1 74.0 23.0

I see; never had the need, but more importantly, the question only involved number strings .. hence why should the answer be about something more complicated... ... but never mind.

"When a clown moves into a castle, he doesn't become a king. The castle becomes a circus" - Turkish proverb

Sorry.. a "typo" -- as.numeric("0.01") of course

is this just joking around? `as.character("0.01")` works from the base of base R ..

i love Andrew Heiss but that’s not his creation; Michael Friendly @datavisfriendly.bsky.social has plots along these lines in Chapter 8 of Discrete Data Analysis in R