Provide a tidy table of the number of variables with 0, 1, 2, up to n, missing values and the proportion of the number of variables those variables make up.
miss_var_table(data)
a dataframe
a dataframe
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()
# NOT RUN {
miss_var_table(airquality)
library(dplyr)
airquality %>%
group_by(Month) %>%
miss_var_table()
# }
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