count() lets you quickly count the unique values of one or more variables: df df count() is paired with tally(), a lower-level helper that is equivalent to df switching the summary from n = n() to n = sum(wt).

add_count() are add_tally() are equivalents to count() and tally() but use mutate() instead of summarise() so that they add a new column with group-wise counts.

count(
x,
...,
wt = NULL,
sort = FALSE,
name = NULL,
.drop = group_by_drop_default(x)
)

x,
...,
wt = NULL,
sort = FALSE,
name = NULL,
.drop = group_by_drop_default(x)
)

# S3 method for default
x,
...,
wt = NULL,
sort = FALSE,
name = NULL,
.drop = group_by_drop_default(x)
)

# S3 method for Seurat
x,
...,
wt = NULL,
sort = FALSE,
name = NULL,
.drop = group_by_drop_default(x)
)

## Arguments

x

A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr).

...

<[data-masking][dplyr_data_masking]> Variables to group by.

wt

<[data-masking][dplyr_data_masking]> Frequency weights. Can be NULL or a variable:

* If NULL (the default), counts the number of rows in each group. * If a variable, computes sum(wt) for each group.

sort

If TRUE, will show the largest groups at the top.

name

The name of the new column in the output.

If omitted, it will default to n. If there's already a column called n, it will error, and require you to specify the name.

.drop

For count(): if FALSE will include counts for empty groups (i.e. for levels of factors that don't exist in the data). Deprecated in add_count() since it didn't actually affect the output.

## Value

An object of the same type as .data. count() and add_count() group transiently, so the output has the same groups as the input.

## Examples


%>% = magrittr::%>%
data("pbmc_small")
pbmc_small %>%  count(groups)
#> tidyseurat says: A data frame is returned for independent data analysis.
#> # A tibble: 2 × 2
#>   groups     n
#>   <chr>  <int>
#> 1 g1        44
#> 2 g2        36

`