How to run a frequency table in R for a set of variables like you would say FREQUENCIES var1 TO var10 in SPSS?

I'm trying to run a set of frequency tables in R without having to write the code for every single variable. For example, using the mtcars data in SPSS I would so something like:

FREQUENCIES mpg TO vs

And it would give me the 8 frequency tables for the variables between mpg and vs. I'm trying to get this effect in R using the summarytools function freq or the sjPlot function view_df. I can do it using freq but you have to list the names of all of the variables instead of using a command like TO. And I can do it using view_df but you have to know the column positions of the variables (I have thousands of variables so that's not going to work). Please take a look at what I've got below.

#####USING FREQ IN SUMMARY TOOLS
library(summarytools)

freq(mtcars[ ,c("mpg", "cyl", "disp", "hp", "drat", "wt", "qsec", "vs")])  #works fine, but I don't want to have to list the names of all of the variables 

#####USING VIEW_DF IN SJPLOT
library(sjPlot)
view_df(mtcars[, c(1:8)],     #I want to be able to say c(mpg:vs)
        show.na = TRUE, 
        show.type = TRUE, 
        show.frq = TRUE, 
        show.prc = TRUE, 
        show.string.values = TRUE, 
        show.id = TRUE)

####A FEW EXTRA STEPS USING THE EXPSS PACKAGE

I know you can use the %to% in the expss package. I've got my own data and variable names here, sorry!

# table with counts
counts = calculate(olbm_na_A, cro(mdset(S06_01_NA %to% S06_99_NA), list("Count")))

# table with percents
percents = calculate(olbm_na_A, cro_cpct(mdset(S06_01_NA %to% S06_99_NA), list("Column, %")))

# combine tables
expss_output_viewer() 
(counts %merge% percents)

I expect to have it print out a sequence of frequency tables. I want to be able to use some command that basically means var1 to var10. I can't figure out how do this TO command. I expect it varies by what package you're using.

Solution

There is a fre function in the expss package:

library(expss)
data(mtcars)
mtcars = apply_labels(mtcars,
                      mpg = "Miles/(US) gallon",
                      cyl = "Number of cylinders",
                      disp = "Displacement (cu.in.)",
                      hp = "Gross horsepower",
                      drat = "Rear axle ratio",
                      wt = "Weight (lb/1000)",
                      qsec = "1/4 mile time",
                      vs = "Engine",
                      vs = c("V-engine" = 0,
                             "Straight engine" = 1),
                      am = "Transmission",
                      am = c("Automatic" = 0,
                             "Manual"=1),
                      gear = "Number of forward gears",
                      carb = "Number of carburetors"
)

# as.list is needed to process data.frame as several variables rather than multiple response
calculate(mtcars, fre(as.list(vs %to% carb)))

Generally speaking, you can use %to% inside calculate with any other function from any package. %to% simply returns data.frame, e.g vs %to% carb is identical to mtcars[, c("vs", "am", "gear", "carb")].

Example with sjPlot:

library(sjPlot)
calc(mtcars, view_df(vs %to% carb))