I am using expss package for analysis in R.
I use cro_mean_sd_n() to give the mean and standard deviation.
Can I call another function to find the mode?
And other possibilities mean, median, mode, sum, N in a single table.
You can use arbitrary function with cro_fun:
library(expss)
data(mtcars)
mtcars = apply_labels(mtcars,
mpg = "Miles/(US) gallon",
cyl = "Number of cylinders",
vs = "Engine",
vs = num_lab("
0 V-engine
1 Straight engine
"),
am = "Transmission",
am = num_lab("
0 Automatic
1 Manual
")
)
# by now there is no built-in 'mode' function so we define our own
w_mode = function(x, weight = NULL){
if(is.null(weight)){
curr_freq = data.table(x = x)[, list(count = .N), by = x]
} else {
curr_freq = data.table(x = x, weight = weight)[, list(count = sum(weight, na.rm = TRUE)), by = x]
}
curr_freq[["x"]][which.max(curr_freq[["count"]])]
}
# caclulate statistics
calc_cro_fun(mtcars, list(mpg, cyl),
col_vars = list(total(), am),
fun = combine_functions("Mean" = w_mean,
"Median" = w_median,
"Mode" = w_mode,
"Sum" = w_sum,
"N" = valid_n)
)
# | | | #Total | Transmission | |
# | | | | Automatic | Manual |
# | ------------------- | ------- | ------ | ------------ | ------ |
# | Miles/(US) gallon | Mean | 20.1 | 17.1 | 24.4 |
# | | Median | 19.2 | 17.3 | 22.8 |
# | | Mode | 21.0 | 19.2 | 21.0 |
# | | Sum | 642.9 | 325.8 | 317.1 |
# | | N | 32.0 | 19.0 | 13.0 |
# | Number of cylinders | Mean | 6.2 | 6.9 | 5.1 |
# | | Median | 6.0 | 8.0 | 4.0 |
# | | Mode | 8.0 | 8.0 | 4.0 |
# | | Sum | 198.0 | 132.0 | 66.0 |
# | | N | 32.0 | 19.0 | 13.0 |
# we can reposition statistics with argument 'method' in 'combine_functions'
calc_cro_fun(mtcars, list(mpg, cyl),
col_vars = list(total(), am),
fun = combine_functions("Mean" = w_mean,
"Median" = w_median,
"Mode" = w_mode,
"Sum" = w_sum,
"N" = valid_n,
method = list
)
)
# | | #Total | | | | | Transmission | | | | | | | | | |
# | | Mean | Median | Mode | Sum | N | Automatic | | | | | Manual | | | | |
# | | | | | | | Mean | Median | Mode | Sum | N | Mean | Median | Mode | Sum | N |
# | ------------------- | ------ | ------ | ---- | ----- | -- | ------------ | ------ | ---- | ----- | -- | ------ | ------ | ---- | ----- | -- |
# | Miles/(US) gallon | 20.1 | 19.2 | 21 | 642.9 | 32 | 17.1 | 17.3 | 19.2 | 325.8 | 19 | 24.4 | 22.8 | 21 | 317.1 | 13 |
# | Number of cylinders | 6.2 | 6.0 | 8 | 198.0 | 32 | 6.9 | 8.0 | 8.0 | 132.0 | 19 | 5.1 | 4.0 | 4 | 66.0 | 13 |
You can also use sum, mean and etc from base R instead of w_* functions if you don't need weights support.