Complete a data frame with missing combinations of data.

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())
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: expand(df, nesting(x, y, z)).

You can combine the two forms. For example, expand(df, nesting(school_id, student_id), date) would produce a row for every student for each date.

To fill in values that are missing altogether, use expressions like year = 2010:2020 or year = full_seq(year).

A named list that for each variable supplies a single value to use instead of NA for missing combinations.

If you supply fill, these values will also replace existing explicit missing values in the data set.

See Also

complete_ for a version that uses regular evaluation and is suitable for programming with.

  • complete
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))
Documentation reproduced from package tidyr, version 0.5.1, License: MIT + file LICENSE

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