This package is considered a duplicate. The official version of this package is found at:https://hope-data-science.r-universe.dev/tidyft

Package: tidyft 0.9.20

Tian-Yuan Huang

tidyft: Fast and Memory Efficient Data Operations in Tidy Syntax

Tidy syntax for 'data.table', using modification by reference whenever possible. This toolkit is designed for big data analysis in high-performance desktop or laptop computers. The syntax of the package is similar or identical to 'tidyverse'. It is user friendly, memory efficient and time saving. For more information, check its ancestor package 'tidyfst'.

Authors:Tian-Yuan Huang [aut, cre]

tidyft_0.9.20.tar.gz
tidyft_0.9.20.zip(r-4.7)tidyft_0.9.20.zip(r-4.6)tidyft_0.9.20.zip(r-4.5)
tidyft_0.9.20.tgz(r-4.6-any)tidyft_0.9.20.tgz(r-4.5-any)
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tidyft_0.9.20.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tidyft/json (API)

# Install 'tidyft' in R:

install.packages('tidyft', repos = c('https://fastverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hope-data-science/tidyft/issues

Pkgdown/docs site:https://hope-data-science.github.io

On CRAN:

5.69 score 35 stars 28 scripts 331 downloads 88 exports 12 dependencies

Last updated from:6cdfcd20c6. Checks:9 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	170
source / vignettes	OK	186
linux-release-x86_64	OK	166
macos-release-arm64	OK	102
macos-oldrel-arm64	OK	88
windows-devel	OK	82
windows-release	OK	104
windows-oldrel	OK	90
wasm-release	OK	119

Exports:%>%add_count anti_join arrange as_fst as.data.table chop CJ complete copy count cummean data.table delete_na df_mat distinct drop_na dummy export_fst fcoalesce fill filter filter_fst fread full_join fwrite group_by group_exe groups import_fst inner_join lag lead left_join longer mat_df mutate mutate_vars mutate_when nest nth object_size parse_fst pull rbindlist read_csv relocate rename replace_vars right_join rleid rleidv rowwise_mutate rowwise_summarise select select_dt select_fst select_mix select_vars semi_join separate setDT setnames shift_fill slice slice_fst slice_head slice_max slice_min slice_sample slice_tail squeeze summarise summarise_vars summarise_when summary_fst sys_time_print tables transmute transpose unchop uncount ungroup uniqueN unite unnest utf8_encoding wider

Dependencies:cli data.table fst fstcore glue lifecycle magrittr Rcpp rlang stringi stringr vctrs

Fastest data operations with least memory in tidy syntax

Why tidyft? | The philosophy of tidyft | Working with fst | Performance | Session Information

Rendered fromIntroduction.Rmdusingknitr::rmarkdown

Last update: 2024-09-23
Started: 2020-04-10

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Arrange entries in data.frame	arrange
Save a data.frame as a fst table	as_fst
Complete a data frame with missing combinations of data	complete
Count observations by group	add_count count
Cumulative mean	cummean
Select distinct/unique rows in data.table	distinct
Drop or delete data by rows or columns	delete_na drop_na
Fast creation of dummy variables	dummy
Read and write fst files	export_fst import_fst
Fill in missing values with previous or next value	fill shift_fill
Filter entries in data.frame	filter
Parse,inspect and extract data.table from fst file	filter_fst fst parse_fst select_fst slice_fst summary_fst
Group by one or more variables	groups group_by group_exe ungroup
Join tables	anti_join full_join inner_join left_join right_join semi_join
Fast lead/lag for vectors	lag lead
Pivot data between long and wide	longer wider
Conversion between tidy table and named matrix	df_mat mat_df
Create or transform variables	mutate mutate_vars mutate_when transmute
Nest and unnest	chop nest squeeze unchop unnest
Extract the nth value from a vector	nth
Nice printing of report the Space Allocated for an Object	object_size
Pull out a single variable	pull
Convenient file reader	read_csv
Change column order	relocate
Fast value replacement in data frame	replace_vars
Computation by rows	rowwise_mutate rowwise_summarise
Select/rename variables by name	rename select select_dt select_mix select_vars
Separate a character column into two columns using a regular expression separator	separate
Subset rows using their positions	slice slice_head slice_max slice_min slice_sample slice_tail
Summarise columns to single values	summarise summarise_vars summarise_when
Convenient print of time taken	sys_time_print
"Uncount" a data frame	uncount
Unite multiple columns into one by pasting strings together	unite
Use UTF-8 for character encoding in a data frame	utf8_encoding