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tidyfst (version 0.8.8)

Tidy Verbs for Fast Data Manipulation

Description

A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.

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Install

install.packages('tidyfst')

Monthly Downloads

677

Version

0.8.8

License

MIT + file LICENSE

Issues

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Maintainer

Tian-Yuan Huang

Last Published

March 14th, 2020

Functions in tidyfst (0.8.8)

in_dt

Short cut to data.table
cummean

Cumulative mean
count_dt

Count observations by group
fst

Parse,inspect and extract data.table from fst file
all_dt

Wise mutate or summarise with "all-at-if"
filter_dt

Filter entries in data.frame
distinct_dt

Select distinct/unique rows in data.frame
complete_dt

Complete a data frame with missing combinations of data
dummy_dt

Fast creation of dummy variables
arrange_dt

Arrange entries in data.frame
group_dt

Data manipulation within groups
t_dt

Efficient transpose of data.frame
pull_dt

Pull out a single variable
nth

Extract the nth value from a vector
lead_dt

Fast lead/lag for vectors
top_dt

Select top (or bottom) n rows (by value)
longer_dt

Pivot data from wide to long
mutate_when

Conditional update of columns in data.table
nest_dt

Nest and unnest
set_dt

Fast operations of data.table by reference
left_join_dt

Join table by common keys
select_dt

Select column from data.frame
separate_dt

Separate a character column into two columns using a regular expression separator
export_fst

Read and write fst files
unite_dt

Unite multiple columns into one by pasting strings together
rename_dt

Rename column in data.frame
slice_dt

Slice rows in data.frame
summarise_dt

Summarise columns to single values
sys_time_print

Convenient print of time taken
reexports

Objects exported from other packages
wider_dt

Pivot data from long to wide
sample_dt

Sample n rows from a table
group_by_dt

Group by variable(s) and implement operations
mutate_dt

Mutate columns in data.frame
drop_na_dt

Dump, replace and fill missing values in data.frame
uncount_dt

"Uncount" a data frame
relocate_dt

Change column order