complete {tidyr} | R Documentation |
Turns implicit missing values into explicit missing values.
This is a wrapper around expand()
,
left_join()
and replace_na
that's
useful for completing missing combinations of data.
complete(data, ..., fill = list())
data |
A data frame |
... |
Specification of columns to expand. To find all unique combinations of x, y and z, including those not
found in the data, supply each variable as a separate argument.
To find only the combinations that occur in the data, use nest:
You can combine the two forms. For example,
To fill in values that are missing altogether, use expressions like
|
fill |
A named list that for each variable supplies a single value to
use instead of |
complete_
for a version that uses regular evaluation
and is suitable for programming with.
library(dplyr) df <- data_frame( group = c(1:2, 1), item_id = c(1:2, 2), item_name = c("a", "b", "b"), value1 = 1:3, value2 = 4:6 ) df %>% complete(group, nesting(item_id, item_name)) # You can also choose to fill in missing values df %>% complete(group, nesting(item_id, item_name), fill = list(value1 = 0))