Assume that i have two variables. See Dummy data below:
Out of 250 records:
SEX
Male : 100
Female : 150
HAIR
Short : 110
Long : 140
The code i currently use is provided below, For each variable a different table is created:
sexTable <- table(myDataSet$Sex)
hairTable <- table(myDataSet$Hair)
View(sexTable):
|------------------|------------------|
| Level | Frequency |
|------------------|------------------|
| Male | 100 |
| Female | 150 |
|------------------|------------------|
View(hairTable)
|------------------|------------------|
| Level | Frequency |
|------------------|------------------|
| Short | 110 |
| Long | 140 |
|------------------|------------------|
My question is how to merge the two tables in R that will have the following format As well as to calculate the percentage of frequency for each group of levels:
|---------------------|------------------|------------------|
| Variables | Level | Frequency |
|---------------------|------------------|------------------|
| Sex(N=250) | Male | 100 (40%) |
| | Female | 150 (60%) |
| Hair(N=250) | Short | 110 (44%) |
| | Long | 140 (56%) |
|---------------------|------------------|------------------|
We can use bind_rows after converting to data.frame
library(dplyr)
bind_rows(list(sex = as.data.frame(sexTable),
Hair = as.data.frame(hairTable)), .id = 'Variables')
Using a reproducible example
tbl1 <- table(mtcars$cyl)
tbl2 <- table(mtcars$vs)
bind_rows(list(sex = as.data.frame(tbl1),
Hair = as.data.frame(tbl2)), .id = 'Variables')%>%
mutate(Variables = replace(Variables, duplicated(Variables), ""))
If we also need the percentages
dat1 <- transform(as.data.frame(tbl1),
Freq = sprintf('%d (%0.2f%%)', Freq, as.numeric(prop.table(tbl1) * 100)))
dat2 <- transform(as.data.frame(tbl2),
Freq = sprintf('%d (%0.2f%%)', Freq, as.numeric(prop.table(tbl2) * 100)))
bind_rows(list(sex = dat1, Hair = dat2, .id = 'Variables')