Skip to content
R's data.table package extends data.frame:
C R Batchfile Other
Branch: master
Clone or download
Latest commit 1d33704 Nov 19, 2019

README.md

data.table

CRAN status Travis build status AppVeyor build status Codecov test coverage GitLab CI build status downloads depsy CRAN usage BioC usage indirect usage

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


26 December 2019
Efficiency in data processing: data.table basics - Jan Gorecki, Mumbai R@IISA 2019


Why data.table?

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

Features

  • fast and friendly delimited file reader: ?fread, see also convenience features for small data
  • fast and feature rich delimited file writer: ?fwrite
  • low-level parallelism: many common operations are internally parallelized to use multiple CPU threads
  • fast and scalable aggregations; e.g. 100GB in RAM (see benchmarks on up to two billion rows)
  • fast and feature rich joins: ordered joins (e.g. rolling forwards, backwards, nearest and limited staleness), overlapping range joins (similar to IRanges::findOverlaps), non-equi joins (i.e. joins using operators >, >=, <, <=), aggregate on join (by=.EACHI), update on join
  • fast add/update/delete columns by reference by group using no copies at all
  • fast and feature rich reshaping 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 type list are supported
  • has no dependencies at all other than base R itself, for simpler production/maintenance
  • the R dependency is as old as possible for as long as possible 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

Installation

install.packages("data.table")

# latest development version:
data.table::update.dev.pkg()

See the Installation wiki for more details.

Usage

Use data.table subset [ operator the same way you would use data.frame one, but...

  • no need to prefix each column with DT$ (like subset() and with() but built-in)
  • any R expression using any package is allowed in j argument, not just list of columns
  • extra argument by to compute j 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

Getting started

Cheatsheets

Community

data.table is widely used by the R community. As of July 2019, it was used by over 680 CRAN and Bioconductor packages and was the 9th most starred R package on GitHub. If you need help, the data.table community is active StackOverflow, with nearly 9,000 questions.

Stay up-to-date

Contributing

Guidelines for filing issues / pull requests: Contribution Guidelines.

You can’t perform that action at this time.