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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
miss_case_pct miss_case_prop miss_prop_summary() miss_case_summary miss_case_table miss_summary miss_var_pct miss_var_prop miss_var_run miss_var_span miss_var_summary miss_var_table
miss_prop_summary()
# NOT RUN { miss_var_table(airquality) library(dplyr) airquality %>% group_by(Month) %>% miss_var_table() # }
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