Comparison of DataFrames

Compare basic features of RedAmber with Python pandas, R Tidyverse and Julia DataFrames.

Select columns (variables)

Features	RedAmber	Tidyverse	pandas	DataFrames.jl
Select columns as a dataframe	pick, drop, []	dplyr::select, dplyr::select_if	[], loc[], iloc[], drop, select_dtypes	[], select
Select a column as a vector	[], v	dplyr::pull, [, x]	[], loc[], iloc[]	[!, :x]
Move columns to a new position	pick, []	relocate	[], reindex, loc[], iloc[]	select,transform

Features	RedAmber	Tidyverse	pandas	DataFrames.jl
Select rows that meet logical criteria as a dataframe	slice, remove, []	dplyr::filter	[], filter, query, loc[]	filter
Select rows by position as a dataframe	slice, remove, []	dplyr::slice	iloc[], drop	subset
Move rows to a new position	slice, []	dplyr::filter, dplyr::slice	reindex, loc[], iloc[]	permute

Features	RedAmber	Tidyverse	pandas	DataFrames.jl
Update existing columns	assign	dplyr::mutate	assign, []=	mapcols
Create new columns	assign, assign_left	dplyr::mutate	apply	insertcols,.+
Compute new columns, drop others	new	transmute	(dfply:)transmute	transform,insertcols,mapcols
Rename columns	rename	dplyr::rename, dplyr::rename_with, purrr::set_names	rename, set_axis	rename
Sort dataframe	sort	dplyr::arrange	sort_values	sort

Features	RedAmber	Tidyverse	pandas	DataFrames.jl
Gather columns into rows (create a longer dataframe)	to_long	tidyr::pivot_longer	melt	stack
Spread rows into columns (create a wider dataframe)	to_wide	tidyr::pivot_wider	pivot	unstack
transpose a wide dataframe	transpose	transpose, t	transpose, T	permutedims

Features	RedAmber	Tidyverse	pandas	DataFrames.jl
Grouping	group, group.summarize	dplyr::group_by %>% dplyr::summarise	groupby.agg	combine,groupby

Features	RedAmber	Tidyverse	pandas	DataFrames.jl
Combine additional columns	merge, bind_cols	dplyr::bind_cols	concat	combine
Combine additional rows	concatenate, concat, bind_rows	dplyr::bind_rows	concat	transform
Join right to left, leaving only the matching rows	inner_join, join	dplyr::inner_join	merge	innerjoin
Join right to left, leaving all rows	full_join, outer_join, join	dplyr::full_join	merge	outerjoin
Join matching values to left from right	left_join, join	dplyr::left_join	merge	leftjoin
Join matching values from left to right	right_join, join	dplyr::right_join	merge	rightjoin
Return rows of left that have a match in right	semi_join, join	dplyr::semi_join	[isin]	semijoin
Return rows of left that do not have a match in right	anti_join, join	dplyr::anti_join	[isin]	antijoin
Collect rows that appear in left or right	union	dplyr::union	merge
Collect rows that appear in both left and right	intersect	dplyr::intersect	merge
Collect rows that appear in left but not right	difference, setdiff	dplyr::setdiff	merge