rdatatable

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: statisticsglobe.com/data-table-r-p… #DataScience #R #RStats #Rpackage #StatisticalAnalysis

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

A bag of new features coming in #rdatatable. My fav ones are let (an alias for `:=`(...)) and by=.I for row-wise operation. #unreleased-data-table-v1-14-3-in-development-" target="_blank" rel="nofollow noopener">rdatatable.gitlab.io/data.table/new…

I wish every tutorial was like this! Not only really clear but also explains the thoughts behind the design of the #rdatatable package. cran.r-project.org/web/packages/d…

@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

@ggkuhnle @PaulMainwood If you want speed, learning to use the data.table package in #rstats is a good option too. See also these benchmarks: h2oai.github.io/db-benchmark/ #rdatatable

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

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]

@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

Dear #rdatatable team, thanks for making this possible!

Hi @MattDowle, I made an introduction a few days ago to the #rdatatable framework using some real world data. This is here (#1" target="_blank" rel="nofollow noopener">presentations.utilitr.org/ateliers/datat…). This might interest some of your (French speaking) datatable folks. Associated book chapter here: book.utilitr.org/datatable.html #RStats

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

@MyKo101AB @anthonystevend @rstatstweet Per the @Rdatatable benchmarks at h2oai.github.io/db-benchmark/ (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?

@ckhead @grant_mcdermott @michael_chirico Some less known features of #Rdatatable like non-equi joins & rolling joins The unequalled joy of non-equi joins: selbydavid.com/2021/02/13/joi… non-equi merge in data.table and epidemiology: scitilab.com/post_data/non_… R – Data.Table Rolling Joins: gormanalysis.com/blog/r-data-ta… #Rstats

@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.

#rstats #rdatatable there's an open FR for a functional wrapper to [ that's more pipe-friendly -- please weigh in here: github.com/Rdatatable/dat…

@antoine_fabri One of the reason I like #rdatatable 😉

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

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)!