Compute vector of counts, proportions, or percents for each unique value (and NA if there
is missing data) in a vector.
counts(x, ...)
# S3 method for class 'factor'
counts(x, ..., format = c("count", "proportion", "percent"))
# Default S3 method
counts(x, ..., format = c("count", "proportion", "percent"))
# S3 method for class 'formula'
counts(x, data, ..., format = "count")
props(x, ..., format = "proportion")
percs(x, ..., format = "percent")if (require(mosaicData)) {
props(HELPrct$substance)
# numeric version tallies missing values as well
props(HELPmiss$link)
# Formula version omits missing data with warning (by default)
props( ~ link, data = HELPmiss) # omit NAs with warning
props( ~ link, data = HELPmiss, na.action = na.pass) # no warning; tally NAs
props( ~ link, data = HELPmiss, na.action = na.omit) # no warning, omit NAs
props( ~ substance | sex, data = HELPrct)
props( ~ substance | sex, data = HELPrct, format = "percent")
percs( ~ substance | sex, data = HELPrct)
counts( ~ substance | sex, data = HELPrct)
df_stats( ~ substance | sex, data = HELPrct, props, counts)
df_stats( ~ substance | sex, data = HELPmiss, props, na.action = na.pass)
}
#> Warning: Excluding 23 rows due to missing data [df_stats()].
#> response sex prop_alcohol prop_cocaine prop_heroin prop_missing
#> 1 substance male 0.4122563 0.3203343 0.2674095 0.000000000
#> 2 substance female 0.3333333 0.3693694 0.2882883 0.009009009