summarise_dt {tidyfst}

Summarise columns to single values

Description

Summarise group of values into one value for each group. If there is only one group, then only one value would be returned. The summarise function should always return a single value.

Usage

summarise_dt(.data, ..., by = NULL)

summarize_dt(.data, ..., by = NULL)

summarise_when(.data, when, ..., by = NULL)

summarize_when(.data, when, ..., by = NULL)

summarise_vars(.data, .cols = NULL, .func, ..., by)

summarize_vars(.data, .cols = NULL, .func, ..., by)

Arguments

.data

data.frame

...

List of variables or name-value pairs of summary/modifications functions for summarise_dt.Additional parameters to be passed to parameter '.func' in summarise_vars.

by

unquoted name of grouping variable of list of unquoted names of grouping variables. For details see data.table

when

An object which can be coerced to logical mode

.cols

Columns to be summarised.

.func

Function to be run within each column, should return a value or vectors with same length.

Details

summarise_vars could complete summarise on specific columns.

Value

data.table

See Also

summarise

Examples

iris %>% summarise_dt(avg = mean(Sepal.Length))
iris %>% summarise_dt(avg = mean(Sepal.Length),by = Species)
mtcars %>% summarise_dt(avg = mean(hp),by = .(cyl,vs))

# the data.table way
mtcars %>% summarise_dt(cyl_n = .N, by = .(cyl, vs)) # `.` is short for list

iris %>% summarise_vars(is.numeric,min)
iris %>% summarise_vars(-is.factor,min)
iris %>% summarise_vars(1:4,min)

iris %>% summarise_vars(is.numeric,min,by ="Species")
mtcars %>% summarise_vars(is.numeric,mean,by = c("vs", "am"))

# use multiple functions on multiple columns
iris %>%
  summarise_vars(is.numeric,.func = list(mean,sd,median))
iris %>%
  summarise_vars(is.numeric,.func = list(mean,sd,median),by = Species)