View source: R/miss-x-summary.R
miss_var_summary | R Documentation |
Provide a summary for each variable of the number, percent missings, and cumulative sum of missings of the order of the variables. By default, it orders by the most missings in each variable.
miss_var_summary(data, order = FALSE, add_cumsum = FALSE, digits, ...)
data |
a data.frame |
order |
a logical indicating whether to order the result by |
add_cumsum |
logical indicating whether or not to add the cumulative sum of missings to the data. This can be useful when exploring patterns of nonresponse. These are calculated as the cumulative sum of the missings in the variables as they are first presented to the function. |
digits |
how many digits to display in |
... |
extra arguments |
a tibble of the percent of missing data in each variable
n_miss_cumsum
is calculated as the cumulative sum of missings in the
variables in the order that they are given in the data when entering
the function
pct_miss_case()
prop_miss_case()
pct_miss_var()
prop_miss_var()
pct_complete_case()
prop_complete_case()
pct_complete_var()
prop_complete_var()
miss_prop_summary()
miss_case_summary()
miss_case_table()
miss_summary()
miss_var_prop()
miss_var_run()
miss_var_span()
miss_var_summary()
miss_var_table()
n_complete()
n_complete_row()
n_miss()
n_miss_row()
pct_complete()
pct_miss()
prop_complete()
prop_complete_row()
prop_miss()
miss_var_summary(airquality)
miss_var_summary(oceanbuoys, order = TRUE)
## Not run:
# works with group_by from dplyr
library(dplyr)
airquality %>%
group_by(Month) %>%
miss_var_summary()
## End(Not run)
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