Description Usage Arguments Value Useful functions Backend variations Tidy data See Also Examples
summarise()
is typically used on grouped data created by group_by()
.
The output will have one row for each group.
1 2 3 |
.data |
A tbl. All main verbs are S3 generics and provide methods
for |
... |
Name-value pairs of summary functions. The name will be the
name of the variable in the result. The value should be an expression
that returns a single value like These arguments are automatically quoted and
evaluated in the context of the data
frame. They support unquoting and
splicing. See |
An object of the same class as .data
. One grouping level will
be dropped.
Center: mean()
, median()
Spread: sd()
, IQR()
, mad()
Range: min()
, max()
, quantile()
Position: first()
, last()
, nth()
,
Count: n()
, n_distinct()
Logical: any()
, all()
Data frames are the only backend that supports creating a variable and using it in the same summary. See examples for more details.
When applied to a data frame, row names are silently dropped. To preserve,
convert to an explicit variable with tibble::rownames_to_column()
.
Other single table verbs: arrange
,
filter
, mutate
,
select
, slice
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # A summary applied to ungrouped tbl returns a single row
mtcars %>%
summarise(mean = mean(disp), n = n())
# Usually, you'll want to group first
mtcars %>%
group_by(cyl) %>%
summarise(mean = mean(disp), n = n())
# Each summary call removes one grouping level (since that group
# is now just a single row)
mtcars %>%
group_by(cyl, vs) %>%
summarise(cyl_n = n()) %>%
group_vars()
# Note that with data frames, newly created summaries immediately
# overwrite existing variables
mtcars %>%
group_by(cyl) %>%
summarise(disp = mean(disp), sd = sd(disp))
|
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