
Albert Rapp
@rappa753
🎓 Math PhD student & freelancer 👨🏫 Bite-sized insights on dataviz, web dev & data science with R at https://3mw.albert-rapp.de/subscribe
你可能会喜欢
Even though I've kept this tweet streak going for quite some time, I'm focusing on a new platform now . I will stop tweeting as soon as my scheduled tweets are over. If you want to see more of my content, you can join me via the link in the thread below 👇
372 days of daily tweeting got me: ~ 9,300 new followers ~ 10,000,000 impressions Guess I have to do the same thing on the "business people" platform again 🤷 Come find me there as I'm going to use it for more in-depth content✌️

Looking for a great resource to get better at data wrangling with R?🤔 Check out the upcoming video course from @JoachimSchork 👀 Looks like it will cover everything from the basics to advanced tricks (even times & dates 🥳) Full course description at youtube.com/watch?v=hcGLjC…
youtube.com
YouTube
R Programming Online Course by Statistics Globe | Registration is...
Doing calculations with time data is hard. But it's considerably easier with {lubridate}. You can use its convenience functions to ✅ make dates ✅ add subtract arbitrary time spans ✅ find time lengths between two time points

The {lubridate} package gives you data wrangling superpowers. My favorite trick: Convert text dates into actual dates. Just specify the orders of day, month and year and `parse_date_time()` will do the rest. It can even handle a mix of formats.

United States 趋势
- 1. Knicks 28K posts
- 2. #AEWDynamite 16.6K posts
- 3. Embiid 9,823 posts
- 4. Maxey 4,197 posts
- 5. VJ Edgecombe 8,515 posts
- 6. #Survivor49 2,240 posts
- 7. Clippers 5,355 posts
- 8. Cavs 14.8K posts
- 9. Donovan Mitchell 2,634 posts
- 10. Brunson 6,339 posts
- 11. Sixers 12.1K posts
- 12. Jarrett Allen 1,051 posts
- 13. #NewYorkForever 2,778 posts
- 14. Pistons 5,411 posts
- 15. Hornets 9,073 posts
- 16. #SistasOnBET 1,595 posts
- 17. Lonzo 3,424 posts
- 18. #ChicagoFire 1,589 posts
- 19. Mobley 3,186 posts
- 20. Celtics 22.1K posts
Something went wrong.
Something went wrong.