An example of using let
to wrap dplyr
expressions as functions.
library("dplyr")
library("replyr")
The desired task: write a function that takes a data frame with a specified numerical column and an optional grouping column, and returns a data frame with one row per group containing:
The dplyr
expression for such a table is easy when the column names are known, but complicated when they are not. We use wrapr::let
to write such a function without the use of lazyeval
or rlang
/tidyeval
.
sumstat_intervals = function(dframe, colname, groupcolname = NULL) {
mapping = list(COLNAME =colname,
GROUPCOLNAME = groupcolname)
let(alias = mapping,
{
if(!is.null(groupcolname)) {
dframe <- group_by(dframe, GROUPCOLNAME)
}
summarize(dframe,
sdlower = mean(COLNAME)-sd(COLNAME),
mean = mean(COLNAME),
sdupper = mean(COLNAME) + sd(COLNAME),
iqrlower = median(COLNAME)-0.5*IQR(COLNAME),
median = median(COLNAME),
iqrupper = median(COLNAME)+0.5*IQR(COLNAME))
})
}
We can test sumstat_intervals
on iris
:
sumstat_intervals(iris, "Sepal.Length")
# sdlower mean sdupper iqrlower median iqrupper
# 1 5.015267 5.843333 6.671399 5.15 5.8 6.45
sumstat_intervals(iris, "Sepal.Length", "Species")
# # A tibble: 3 x 7
# Species sdlower mean sdupper iqrlower median iqrupper
# <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 setosa 4.65 5.01 5.36 4.8 5 5.2
# 2 versicolor 5.42 5.94 6.45 5.55 5.9 6.25
# 3 virginica 5.95 6.59 7.22 6.16 6.5 6.84
sumstat_intervals(iris, "Petal.Length", "Species")
# # A tibble: 3 x 7
# Species sdlower mean sdupper iqrlower median iqrupper
# <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 setosa 1.29 1.46 1.64 1.41 1.5 1.59
# 2 versicolor 3.79 4.26 4.73 4.05 4.35 4.65
# 3 virginica 5.00 5.55 6.10 5.16 5.55 5.94