Subset data rows
Usage
all_rows()
filter_rows(..., .by = NULL)
max_rows(order_by, n, by = NULL, with_ties = TRUE, na_rm = FALSE)
min_rows(order_by, n, by = NULL, with_ties = TRUE, na_rm = FALSE)
first_rows(n, by = NULL)
last_rows(n, by = NULL)
sample_rows(n, by = NULL)
Arguments
- ...
<
data-masking
> Expressions that return a logical value, and are defined in terms of the variables in.data
. If multiple expressions are included, they are combined with the&
operator. Only rows for which all conditions evaluate toTRUE
are kept.- .by, by
-
<
tidy-select
> Optionally, a selection of columns to group by for just this operation, functioning as an alternative togroup_by()
. For details and examples, see ?dplyr_by. - order_by
<
data-masking
> Variable or function of variables to order by. To order by multiple variables, wrap them in a data frame or tibble.- n
The number of rows to select. If not are supplied,
n = 1
will be used. Ifn
is greater than the number of rows in the group, the result will be silently truncated to the group size.A negative value of
n
will be subtracted from the group size. For example,n = -2
with a group of 5 rows will select 5 - 2 = 3 rows.- with_ties
Should ties be kept together? The default,
TRUE
, may return more rows than you request. UseFALSE
to ignore ties, and return the firstn
rows.- na_rm
Should missing values in
order_by
be removed from the result? IfFALSE
,NA
values are sorted to the end (like indplyr::arrange()
), so they will only be included if there are insufficient non-missing values to reachn
.
Examples
# Highlight all animals
animals %>%
tidyplot(x = weight, y = size) %>%
add_data_points() %>%
add_data_points(data = all_rows(),
color = "red", shape = 1, size = 3)
# Highlight 3 animals with the highest weight
animals %>%
tidyplot(x = weight, y = size) %>%
add_data_points() %>%
add_data_points(data = max_rows(weight, n = 3),
color = "red", shape = 1, size = 3)
# Highlight 3 animals with the lowest weight
animals %>%
tidyplot(x = weight, y = size) %>%
add_data_points() %>%
add_data_points(data = min_rows(weight, n = 3),
color = "red", shape = 1, size = 3)
# Highlight the first 3 animals in the dataset
animals %>%
tidyplot(x = weight, y = size) %>%
add_data_points() %>%
add_data_points(data = first_rows(n = 3),
color = "red", shape = 1, size = 3)
# Highlight the last 3 animals in the dataset
animals %>%
tidyplot(x = weight, y = size) %>%
add_data_points() %>%
add_data_points(data = last_rows(n = 3),
color = "red", shape = 1, size = 3)
# Highlight 3 random animals
animals %>%
tidyplot(x = weight, y = size) %>%
add_data_points() %>%
add_data_points(data = sample_rows(n = 3),
color = "red", shape = 1, size = 3)