Tidy Verbs for Fast Data Manipulation
Add percentage to counts in data.frame
Arrange entries in data.frame
Save a data.frame as a fst table
Bind multiple data frames by row
Compute TF–IDF Using data.table with Optional Counting and Grouping
Get the column name of the max/min number each row
Complete a data frame with missing combinations of data
Count observations by group
Cumulative mean
Select distinct/unique rows in data.frame
Short cut to data.table
Fast creation of dummy variables
Filter entries in data.frame
Read and write fst files
Parse,inspect and extract data.table from fst file
Group by variable(s) and implement operations
Data manipulation within groups
Read a fst file by chunks
Impute missing values with mean, median or mode
Join tables
Fast lead/lag for vectors
Pivot data from wide to long
Dump, replace and fill missing values in data.frame
Conditional update of columns in data.table
Mutate columns in data.frame
Nest and unnest
Extract the nth value from a vector
Nice printing of report the Space Allocated for an Object
Count pairs of items within a group
Load or unload R package(s)
Set global printing method for data.table
Pull out a single variable
Recode number or strings
Objects exported from other packages
Change column order
Rename column in data.frame
Fast value replacement in data frame
Round a number and make it show zeros
Tools for working with row names
Sample rows randomly from a table
Select column from data.frame
Separate a character column into two columns using a regular expressio...
Set operations for data frames
Subset rows using their positions
Case insensitive table joining like SQL
Summarise columns to single values
Convenient print of time taken
Efficient transpose of data.frame
Conversion between tidy table and named matrix
"Uncount" a data frame
Unite multiple columns into one by pasting strings together
Use UTF-8 for character encoding in a data frame
Pivot data from long to wide
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.
Useful links