rdatatable

Rdatatable tweets. Appreciation account by an independent user. #rstats Logos:

[Joachim Schork @JoachimSchork]

Hey, I've published an extensive introduction to the data.table package in the R programming language. The tutorial was created in collaboration with @AWolwer: https://t.co/SltmGGLBHC

#DataScience #R #RStats #Rpackage #StatisticalAnalysis

[rdatatable @rdatatable]

They specifically mention data.table as required skill for the job! 🤓

[Christian Mongeau @chrmongeau]

Are you a good statistician and R programmer?

FAO of the United Nations is looking for consultants with a strong background in the R statistical programming language.

Details: https://t.co/0P5rzc84zS

Send your CV before July 31st.

#RStats @RStatsJobsBot @rdatatable @tidyverse

[Eyayaw Beze @eyayaw]

A bag of new features coming in #rdatatable. My fav ones are let (an alias for `:=`(...)) and by=.I for row-wise operation.
https://t.co/iKJDgw61qc

[Raphael Bednarsky @R_Bednarsky]

I wish every tutorial was like this! Not only really clear but also explains the thoughts behind the design of the #rdatatable package.
https://t.co/hBTatDincc

[gjc1131 @gjc11311]

@AmeliaMN Hi. Looking for an alternative to DataCamp with course material on data.table (more than a brief intro). I find that most of the things listed in these threads is tidyverse oriented. We tend to use base r and data.table and the survey package where I work. Thanks for any help

[Jaap Walhout | mastodon.social/@jaapwalhout @jaap_w]

@ggkuhnle @PaulMainwood If you want speed, learning to use the data.table package in #rstats is a good option too. See also these benchmarks: https://t.co/vjvhCYgVgh
#rdatatable

[Tony 💉😷🌐💻🥋 Greenberg @BayesicTony]

This looks awesome. I am a big @rdatatable user, too.

[Nick HK @nickchk]

One thing I really like about data.table is how easy it makes conditional operations

"Update just part of the data":
dt[condition, variable := calculation]

"Do a conditional calculation and apply broadly"
dt[, growth_since_january := value/mean(value[month==1]), by = group]

[Dirk Eddelbuettel @eddelbuettel]

@101Programming And if you want to really go for pole position:

library(data.table)
df.all <- rbindlist(lapply(v.filename, fread))
print(df.all)

/cc @rdatatable

[Matthias Gomolka @matthiasgomolka]

Dear #rdatatable team, thanks for making this possible!

[Lino Galiana @LinoGaliana]

Hi @MattDowle, I made an introduction a few days ago to the #rdatatable framework using some real world data. This is here (https://t.co/VLxOKTXyc8).
This might interest some of your (French speaking) datatable folks. Associated book chapter here: https://t.co/1PJQb1wnOM #RStats

[Dirk Eddelbuettel @eddelbuettel]

Public data, public health -- so below is some public code too. The @rdatatable and #ggplot2 combination makes it a breeze. #rstats for the win

[Dirk Eddelbuettel @eddelbuettel]

@MyKo101AB @anthonystevend @rstatstweet Per the @Rdatatable benchmarks at https://t.co/W9blb19qQi (which includes a 'join' problem likely close to your merge issue) you are probably unlikely to beat `data.table` just by going to #Python or #Rcpp. Maybe profile a little and then discuss with team @Rdatatable?

[Kar Chua @kar9222]

@ckhead @grant_mcdermott @michael_chirico Some less known features of #Rdatatable like non-equi joins & rolling joins

The unequalled joy of non-equi joins: https://t.co/zpPJxmbw40

non-equi merge in data.table and epidemiology: https://t.co/1JQa0BiazZ

R – Data.Table Rolling Joins: https://t.co/a7kTwaNxW5

#Rstats

[Adam Altmejd @adamaltmejd]

@grant_mcdermott Love the feeling of succesfully writing nested non-equi join with by = .EACHI, and it runs in seconds on tens of millions of observations. <3 data.table.

[Michael Chirico @michael_chirico]

#rstats #rdatatable there's an open FR for a functional wrapper to [ that's more pipe-friendly -- please weigh in here:

https://t.co/EjAdi65RRd

[Victor Perrier @_pvictorr]

@antoine_fabri One of the reason I like #rdatatable 😉

[Keith Head @ckhead]

@Basile_G @Stata data.table::fread() is the best CSV reader ever.

[Patrick Plötz @PatrickPlotz]

Need to say it again today, best #rstats packages ever:
1. data.table
2. data.table
3 ggplot2

data.table reduced the runtime of my code from 9 hours to five seconds today! Thank you, @MattDowle (and also @hadleywickham of course for ggplot2)!