How to generate a frequency table in R with with cumulative frequency and relative frequency

Question

I'm new with R. I need to generate a simple Frequency Table (as in books) with cumulative frequency and relative frequency.

So I want to generate from some simple data like

> x [1] 17 17 17 17 17 17 17 17 16 16 16 16 16 18 18 18 10 12 17 17 17 17 17 17 17 17 16 16 16 16 16 18 18 18 10 [36] 12 15 19 20 22 20 19 19 19 

a table like:

            frequency  cumulative   relative (9.99,11.7]    2            2       0.04545455 (11.7,13.4]    2            4       0.04545455 (13.4,15.1]    1            5       0.02272727 (15.1,16.9]   10           15       0.22727273 (16.9,18.6]   22           37       0.50000000 (18.6,20.3]    6           43       0.13636364 (20.3,22]      1           44       0.02272727 

I know it should be simple, but I don't know how.

I got some results using this code:

factorx <- factor(cut(x, breaks=nclass.Sturges(x))) as.matrix(table(factorx)) 

Answer 1

You're close! There are a few functions that will make this easy for you, namely cumsum() and prop.table(). Here's how I'd probably put this together. I make some random data, but the point is the same:

#Fake data x <- sample(10:20, 44, TRUE) #Your code factorx <- factor(cut(x, breaks=nclass.Sturges(x))) #Tabulate and turn into data.frame xout <- as.data.frame(table(factorx)) #Add cumFreq and proportions xout <- transform(xout, cumFreq = cumsum(Freq), relative = prop.table(Freq)) #-----       factorx Freq cumFreq   relative 1 (9.99,11.4]   11      11 0.25000000 2 (11.4,12.9]    3      14 0.06818182 3 (12.9,14.3]   11      25 0.25000000 4 (14.3,15.7]    2      27 0.04545455 5 (15.7,17.1]    6      33 0.13636364 6 (17.1,18.6]    3      36 0.06818182 7   (18.6,20]    8      44 0.18181818 

Answer 2

The base functions table, cumsum and prop.table should get you there:

 cbind( Freq=table(x), Cumul=cumsum(table(x)), relative=prop.table(table(x)))    Freq Cumul   relative 10    2     2 0.04545455 12    2     4 0.04545455 15    1     5 0.02272727 16   10    15 0.22727273 17   16    31 0.36363636 18    6    37 0.13636364 19    4    41 0.09090909 20    2    43 0.04545455 22    1    44 0.02272727 

With cbind and naming of the columns to your liking this should be pretty easy for you in the future. The output from the table function is a matrix, so this result is also a matrix. If this were being done on something big it would be more efficient todo this:

tbl <- table(x) cbind( Freq=tbl, Cumul=cumsum(tbl), relative=prop.table(tbl))