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data.table provides a high-performance version ofbase R'sdata.frame with syntax and feature enhancements for ease of use, convenience and programming speed.

Thedata.table project uses acustom governance agreementand is fiscally sponsored byNumFOCUS. Consider makingatax-deductible donation to help the projectpay for developer time, professional services, travel, workshops, and a variety of other needs.

• concise syntax: fast to type, fast to read
• fast speed
• memory efficient
• careful API lifecycle management
• community
• feature rich

• fast and friendly delimitedfile reader:?fread, see alsoconvenience features forsmall data
• fast and feature rich delimitedfile writer:?fwrite
• low-levelparallelism: many common operations are internally parallelized to use multiple CPU threads
• fast and scalable aggregations; e.g. 100GB in RAM (seebenchmarks on up totwo billion rows)
• fast and feature rich joins:ordered joins (e.g. rolling forwards, backwards, nearest and limited staleness),overlapping range joins (similar toIRanges::findOverlaps),non-equi joins (i.e. joins using operators>, >=, <, <=),aggregate on join (by=.EACHI),update on join
• fast add/update/delete columnsby reference by group using no copies at all
• fast and feature richreshaping data:?dcast (pivot/wider/spread) and?melt (unpivot/longer/gather)
• any R function from any R package can be used in queries not just the subset of functions made available by a database backend, also columns of typelist are supported
• hasno dependencies at all other than base R itself, for simpler production/maintenance
• the R dependency isas old as possible for as long as possible, dated April 2014, and we continuously test against that version; e.g. v1.11.0 released on 5 May 2018 bumped the dependency up from 5 year old R 3.0.0 to 4 year old R 3.1.0

install.packages("data.table")# latest development version (only if newer available)data.table::update_dev_pkg()# latest development version (force install)install.packages("data.table",repos="https://rdatatable.gitlab.io/data.table")

Seethe Installation wiki for more details.

Usedata.table subset[ operator the same way you would usedata.frame one, but...

• no need to prefix each column withDT$ (likesubset() andwith() but built-in)
• any R expression using any package is allowed inj argument, not just list of columns
• extra argumentby to computej expression by group

library(data.table)DT= as.data.table(iris)# FROM[WHERE, SELECT, GROUP BY]# DT  [i,     j,      by]DT[Petal.Width>1.0, mean(Petal.Length),by=Species]#      Species       V1#1: versicolor 4.362791#2:  virginica 5.552000

• Introduction to data.table vignette
• Getting started wiki page
• Examples produced byexample(data.table)

data.table is widely used by the R community. It is being directly used by hundreds of CRAN and Bioconductor packages, and indirectly by thousands. It is one of thetop most starred R packages on GitHub, and was highly rated by theDepsy project. If you need help, thedata.table community is active onStackOverflow.

A list of packages that significantly support, extend, or make use ofdata.table can be found in theSeal of Approval document.

• click theWatch button at the top and right of GitHub project page
• readNEWS file
• follow#rdatatable and ther_data_table account on X/Twitter
• follow#rdatatable and ther_data_table account on fosstodon
• follow thedata.table community page on LinkedIn
• watch recentPresentations
• read recentArticles
• read posts onThe Raft

Guidelines for filing issues / pull requests:Contribution Guidelines.