Likely you mean to be using favstats. Each of these computes the
mean, standard deviation, quartiles, sample size and number of missing values for a numeric vector,
but favstats can take a formula describing how these summary statistics
should be aggregated across various subsets of the data.
Usage
fav_stats(x, ..., na.rm = TRUE, type = 7)
Arguments
x
numeric vector
...
additional arguments (currently ignored)
na.rm
boolean indicating whether missing data should be ignored
type
an integer between 1 and 9 selecting one of the nine quantile algorithms detailed
in the documentation for quantile
# NOT RUN {fav_stats(1:10)
fav_stats(faithful$eruptions)
favstats(Sepal.Length ~ Species, data=iris) # Note: this is favstats() rather than fav_stats()# }