Package: dtplyr 1.3.1.9000

Hadley Wickham

dtplyr: Data Table Back-End for 'dplyr'

Provides a data.table backend for 'dplyr'. The goal of 'dtplyr' is to allow you to write 'dplyr' code that is automatically translated to the equivalent, but usually much faster, data.table code.

Authors:Hadley Wickham [cre, aut], Maximilian Girlich [aut], Mark Fairbanks [aut], Ryan Dickerson [aut], Posit Software, PBC [cph, fnd]

dtplyr_1.3.1.9000.tar.gz
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dtplyr.pdf |dtplyr.html✨
dtplyr/json (API)
NEWS

# Install 'dtplyr' in R:
install.packages('dtplyr', repos = c('https://fastverse.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tidyverse/dtplyr/issues

On CRAN:

datatabledplyr

16.43 score 669 stars 141 packages 2.5k scripts 585k downloads 2 exports 17 dependencies

Last updated 3 months agofrom:0fa0d0459d. Checks:OK: 5 NOTE: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-winNOTENov 04 2024
R-4.5-linuxNOTENov 04 2024
R-4.4-winOKNov 04 2024
R-4.4-macOKNov 04 2024
R-4.3-winOKNov 04 2024
R-4.3-macOKNov 04 2024

Exports:.datatable.awarelazy_dt

Dependencies:clidata.tabledplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

Translation

Rendered fromtranslation.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2023-02-27
Started: 2019-06-25

Readme and manuals

Help Manual

Help pageTopics
Arrange rows by column valuesarrange.dtplyr_step
Force computation of a lazy data.tableas.data.frame.dtplyr_step as.data.table.dtplyr_step as_tibble.dtplyr_step collect.dtplyr_step compute.dtplyr_step
Complete a data frame with missing combinations of datacomplete.dtplyr_step
Count observations by groupcount.dtplyr_step
Subset distinct/unique rowsdistinct.dtplyr_step
Drop rows containing missing valuesdrop_na.dtplyr_step
Expand data frame to include all possible combinations of values.expand.dtplyr_step
Fill in missing values with previous or next valuefill.dtplyr_step
Subset rows using column valuesfilter.dtplyr_step
Group and ungroupgroup_by.dtplyr_step ungroup.dtplyr_step
Apply a function to each groupgroup_map.dtplyr_step group_modify.dtplyr_step
Subset first or last rowshead.dtplyr_step tail.dtplyr_step
Set operationsintersect.dtplyr_step setdiff.dtplyr_step union.dtplyr_step union_all.dtplyr_step
Create a "lazy" data.table for use with dplyr verbsgrouped_dt lazy_dt tbl_dt
Join data tablesleft_join.dtplyr_step
Create and modify columnsmutate.dtplyr_step
Nestnest.dtplyr_step
Pivot data from wide to longpivot_longer.dtplyr_step
Pivot data from long to widepivot_wider.dtplyr_step
Summarise each group to one rowreframe.dtplyr_step
Relocate variables using their namesrelocate.dtplyr_step
Rename columns using their namesrename.dtplyr_step rename_with.dtplyr_step
Replace NAs with specified valuesreplace_na.dtplyr_step
Subset columns using their namesselect.dtplyr_step
Separate a character column into multiple columns with a regular expression or numeric locationsseparate.dtplyr_step
Subset rows using their positionsslice.dtplyr_step slice_head.dtplyr_step slice_max.dtplyr_step slice_min.dtplyr_step slice_tail.dtplyr_step
Summarise each group to one rowsummarise.dtplyr_step
Create new columns, dropping oldtransmute.dtplyr_step
Unite multiple columns into one by pasting strings together.unite.dtplyr_step