ahh thanks!
New Fellows (and others):
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San Diego sounds wonderful. Iâm 99% sure Iâll be there 
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See you there!
Agreed: you can either use sqldf, or data.table can do most SQL-esque tasks very efficiently
But yes, R and SQL more of complements than substitutes
This is a crutch for sql users that is much slower than other data munging methods in R.
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Thanks!
I prefer dplyrâŚ
Me too. I find it relatively intuitive as someone who worked extensively in SQL prior to R.
data.table is faster & doesnât have the same dependency overhead that dplyr has with the tidyverse.
Yeah itâs pretty easy to a lot of manipulations.
I actually find it more intuitive than sql as a person coming from sql. I also find it more powerful. If you want a cumulative total use cumsum(), if you want to crosstab a column use pivot_wider()âŚetc.
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I just realized I can throw out all my exam 9 materials!!!
Time to do that, I have accumulated quite a lot in the past three years.
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You can send them to me if theyâre not trashed yet 
But if throwing them out gives you that satisfaction then please go ahead haha.
I use dplyr frequently, and just explored using data.table for some calculation that I wanted to speed up. The speed of data.table is really impressive, I might try to get used to it and start using it rather than dplyr. It doesnât matter on smaller datasets, but once you get into the hundreds of thousands to millions of rows, the speed of data.table really shows.
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There is also a package called dtplyr which letâs you use dplyr syntax but uses data.table as the execution engine.
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Thatâs awesome, thanks for the tip.
any idea of when the exam statistics will be released?
Still crickets on the exam statistics front.
I think it will be above 50%.
wondering what the pass ratio was but still no exam statistics yetâŚ