Package index • dplyr

Data frame verbs

Rows

Verbs that principally operate on rows.

arrange(): Order rows using column values

distinct(): Keep distinct/unique rows

filter(): Keep rows that match a condition

slice() slice_head() slice_tail() slice_min() slice_max() slice_sample(): Subset rows using their positions

Columns

Verbs that principally operate on columns.

glimpse: Get a glimpse of your data

mutate(): Create, modify, and delete columns

pull(): Extract a single column

relocate(): Change column order

rename() rename_with(): Rename columns

select(): Keep or drop columns using their names and types

Groups

Verbs that principally operate on groups of rows.

count() tally() add_count() add_tally(): Count the observations in each group

group_by() ungroup(): Group by one or more variables

dplyr_by: Per-operation grouping with .by/by

rowwise(): Group input by rows

summarise() summarize(): Summarise each group down to one row

reframe() experimental: Transform each group to an arbitrary number of rows

n() cur_group() cur_group_id() cur_group_rows() cur_column(): Information about the "current" group or variable

Data frames

Verbs that principally operate on pairs of data frames.

bind_cols(): Bind multiple data frames by column

bind_rows(): Bind multiple data frames by row

intersect() union() union_all() setdiff() setequal() symdiff(): Set operations

inner_join() left_join() right_join() full_join(): Mutating joins

nest_join(): Nest join

semi_join() anti_join(): Filtering joins

cross_join(): Cross join

join_by(): Join specifications

rows_insert() rows_append() rows_update() rows_patch() rows_upsert() rows_delete(): Manipulate individual rows

Multiple columns

Pair these functions with mutate(), summarise(), filter(), and group_by() to operate on multiple columns simultaneously.

across() if_any() if_all(): Apply a function (or functions) across multiple columns

c_across(): Combine values from multiple columns

pick(): Select a subset of columns

Vector functions

Unlike other dplyr functions, these functions work on individual vectors, not data frames.

between(): Detect where values fall in a specified range

case_match(): A general vectorised switch()

case_when(): A general vectorised if-else

coalesce(): Find the first non-missing element

consecutive_id(): Generate a unique identifier for consecutive combinations

cumall() cumany() cummean(): Cumulative versions of any, all, and mean

desc(): Descending order

if_else(): Vectorised if-else

lag() lead(): Compute lagged or leading values

n_distinct(): Count unique combinations

na_if(): Convert values to NA

near(): Compare two numeric vectors

nth() first() last(): Extract the first, last, or nth value from a vector

ntile(): Bucket a numeric vector into n groups

order_by(): A helper function for ordering window function output

percent_rank() cume_dist(): Proportional ranking functions

recode() recode_factor() superseded: Recode values

row_number() min_rank() dense_rank(): Integer ranking functions

Built in datasets

band_members band_instruments band_instruments2: Band membership

starwars: Starwars characters

storms: Storm tracks data

Grouping helpers

This (mostly) experimental family of functions are used to manipulate groups in various ways.

group_cols(): Select grouping variables

group_map() group_modify() group_walk() experimental: Apply a function to each group

group_trim() experimental: Trim grouping structure

Superseded

Superseded functions have been replaced by new approaches that we believe to be superior, but we don’t want to force you to change until you’re ready, so the existing functions will stay around for several years.

sample_n() sample_frac() superseded: Sample n rows from a table

top_n() top_frac() superseded: Select top (or bottom) n rows (by value)

scoped superseded: Operate on a selection of variables

all_vars() any_vars() superseded: Apply predicate to all variables

vars() superseded: Select variables

with_groups() superseded: Perform an operation with temporary groups

Remote tables

auto_copy(): Copy tables to same source, if necessary

compute() collect() collapse(): Force computation of a database query

copy_to(): Copy a local data frame to a remote src

ident(): Flag a character vector as SQL identifiers

explain() show_query(): Explain details of a tbl

tbl() is.tbl(): Create a table from a data source

sql(): SQL escaping.