prop | R Documentation |
prop()
calculates the proportion of a value or category
in a variable. props()
does the same, but allows for
multiple logical conditions in one statement. It is similar
to mean()
with logical predicates, however, both
prop()
and props()
work with grouped data frames.
prop(data, ..., weights = NULL, na.rm = TRUE, digits = 4) props(data, ..., na.rm = TRUE, digits = 4)
data |
A data frame. May also be a grouped data frame (see 'Examples'). |
... |
One or more value pairs of comparisons (logical predicates). Put variable names the left-hand-side and values to match on the right hand side. Expressions may be quoted or unquoted. See 'Examples'. |
weights |
Vector of weights that will be applied to weight all observations.
Must be a vector of same length as the input vector. Default is
|
na.rm |
Logical, whether to remove NA values from the vector when the
proportion is calculated. |
digits |
Amount of digits for returned values. |
prop()
only allows one logical statement per comparison,
while props()
allows multiple logical statements per comparison.
However, prop()
supports weighting of variables before calculating
proportions, and comparisons may also be quoted. Hence, prop()
also processes comparisons, which are passed as character vector
(see 'Examples').
For one condition, a numeric value with the proportion of the values inside a vector. For more than one condition, a data frame with one column of conditions and one column with proportions. For grouped data frames, returns a data frame with one column per group with grouping categories, followed by one column with proportions per condition.
data(efc) # proportion of value 1 in e42dep prop(efc, e42dep == 1) # expression may also be completely quoted prop(efc, "e42dep == 1") # use "props()" for multiple logical statements props(efc, e17age > 70 & e17age < 80) # proportion of value 1 in e42dep, and all values greater # than 2 in e42dep, including missing values. will return a data frame prop(efc, e42dep == 1, e42dep > 2, na.rm = FALSE) # for factors or character vectors, use quoted or unquoted values library(sjmisc) # convert numeric to factor, using labels as factor levels efc$e16sex <- to_label(efc$e16sex) efc$n4pstu <- to_label(efc$n4pstu) # get proportion of female older persons prop(efc, e16sex == female) # get proportion of male older persons prop(efc, e16sex == "male") # "props()" needs quotes around non-numeric factor levels props(efc, e17age > 70 & e17age < 80, n4pstu == 'Care Level 1' | n4pstu == 'Care Level 3' ) # also works with pipe-chains library(dplyr) efc %>% prop(e17age > 70) efc %>% prop(e17age > 70, e16sex == 1) # and with group_by efc %>% group_by(e16sex) %>% prop(e42dep > 2) efc %>% select(e42dep, c161sex, c172code, e16sex) %>% group_by(c161sex, c172code) %>% prop(e42dep > 2, e16sex == 1) # same for "props()" efc %>% select(e42dep, c161sex, c172code, c12hour, n4pstu) %>% group_by(c161sex, c172code) %>% props( e42dep > 2, c12hour > 20 & c12hour < 40, n4pstu == 'Care Level 1' | n4pstu == 'Care Level 3' )
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