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(): 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_when() replace_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_values() replace_values(): Recode and replace 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.

all_vars() any_vars() superseded: Apply predicate to all variables
case_match() superseded: A general vectorised switch()
recode() recode_factor() superseded: Recode values
sample_n() sample_frac() superseded: Sample n rows from a table
scoped superseded: Operate on a selection of variables
top_n() top_frac() superseded: Select top (or bottom) n rows (by value)
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.