Function reference • dplyr

All functions
`all_equal()` `all.equal(<tbl_df>)`	Flexible equality comparison for data frames
`all_vars()` `any_vars()`	Apply predicate to all variables
`arrange()`	Arrange rows by variables
`arrange_all()` `arrange_at()` `arrange_if()`	Arrange rows by a selection of variables
`as.table(<tbl_cube>)` `as.data.frame(<tbl_cube>)` `as_tibble(<tbl_cube>)`	Coerce a `tbl_cube` to other data structures
`as.tbl_cube()`	Coerce an existing data structure into a `tbl_cube`
`auto_copy()`	Copy tables to same source, if necessary
`band_members` `band_instruments` `band_instruments2`	Band membership
`between()`	Do values in a numeric vector fall in specified range?
`bind_rows()` `bind_cols()`	Efficiently bind multiple data frames by row and column
`case_when()`	A general vectorised if
`coalesce()`	Find first non-missing element
`combine()`	Combine vectors
`compute()` `collect()` `collapse()`	Force computation of a database query
`copy_to()`	Copy a local data frame to a remote src
`cumall()` `cumany()` `cummean()`	Cumulativate versions of any, all, and mean
`desc()`	Descending order
`distinct()`	Select distinct/unique rows
`distinct_all()` `distinct_at()` `distinct_if()`	Select distinct rows by a selection of variables
`do()`	Do anything
`dplyr-package`	dplyr: a grammar of data manipulation
`dr_dplyr()`	Dr Dplyr checks your installation for common problems.
`explain()` `show_query()`	Explain details of a tbl
`filter()`	Return rows with matching conditions
`filter_all()` `filter_if()` `filter_at()`	Filter within a selection of variables
`funs()`	Create a list of functions calls.
`group_by()` `ungroup()`	Group by one or more variables
`group_by_all()` `group_by_at()` `group_by_if()`	Group by a selection of variables
`group_by_drop_default()`	Default value for .drop argument of group_by
`group_cols()`	Select grouping variables
`group_rows()` `group_data()`	Grouping data
`group_map()` `group_modify()` `group_walk()`	Apply a function to each group
`group_keys()` `group_split()`	Split data frame by groups
`group_trim()`	Trim grouping structure
`groups()` `group_vars()`	Return grouping variables
`hybrid_call()`	Inspect how dplyr evaluates an expression
`ident()`	Flag a character vector as SQL identifiers
`if_else()`	Vectorised if
`inner_join()` `left_join()` `right_join()` `full_join()` `semi_join()` `nest_join()` `anti_join()`	Join two tbls together
`nest_join(<data.frame>)` `inner_join(<tbl_df>)` `nest_join(<tbl_df>)` `left_join(<tbl_df>)` `right_join(<tbl_df>)` `full_join(<tbl_df>)` `semi_join(<tbl_df>)` `anti_join(<tbl_df>)`	Join data frame tbls
`lead()` `lag()`	Lead and lag.
`mutate()` `transmute()`	Create or transform variables
`mutate_all()` `mutate_if()` `mutate_at()` `transmute_all()` `transmute_if()` `transmute_at()`	Mutate multiple columns
`n()`	The number of observations in the current group.
`n_distinct()`	Efficiently count the number of unique values in a set of vector
`na_if()`	Convert values to NA
`nasa`	NASA spatio-temporal data
`near()`	Compare two numeric vectors
`nth()` `first()` `last()`	Extract the first, last or nth value from a vector
`order_by()`	A helper function for ordering window function output
`pull()`	Pull out a single variable
`row_number()` `ntile()` `min_rank()` `dense_rank()` `percent_rank()` `cume_dist()`	Windowed rank functions.
`recode()` `recode_factor()`	Recode values
`rowwise()`	Group input by rows
`sample_n()` `sample_frac()`	Sample n rows from a table
`scoped`	Operate on a selection of variables
`select()` `rename()`	Select/rename variables by name
`select_all()` `rename_all()` `select_if()` `rename_if()` `select_at()` `rename_at()`	Select and rename a selection of variables
`select_vars()` `rename_vars()` `select_var()` `current_vars()`	Select variables
`intersect()` `union()` `union_all()` `setdiff()` `setequal()`	Set operations
`slice()`	Choose rows by position
`sql()`	SQL escaping.
`src_mysql()` `src_postgres()` `src_sqlite()`	Source for database backends
`starwars`	Starwars characters
`storms`	Storm tracks data
`summarise()` `summarize()`	Reduce multiple values down to a single value
`summarise_all()` `summarise_if()` `summarise_at()` `summarize_all()` `summarize_if()` `summarize_at()`	Summarise multiple columns
`tally()` `count()` `add_tally()` `add_count()`	Count/tally observations by group
`tbl()` `is.tbl()` `as.tbl()`	Create a table from a data source
`tbl_cube()`	A data cube tbl
`top_n()` `top_frac()`	Select top (or bottom) n rows (by value)
`vars()`	Select variables

Reference

All functions

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