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How to find the counts of categories in categorical columns in an R data frame?
If we have two categorical columns in an R data frame then we can find the frequency/count of each category with respect to each category in the other column. This will help us to compare the frequencies for all categories. To find the counts of categories, we can use table function as shown in the below examples.
Example1
Consider the below data frame −
x1<−sample(c("Child","Teen","Adult","Old"),20,replace=TRUE)
x2<−sample(c("Unemployed","Employed"),20,replace=TRUE)
df1<−data.frame(x1,x2)
df1Output
x1 x2 1 Old Unemployed 2 Child Unemployed 3 Adult Employed 4 Adult Unemployed 5 Adult Employed 6 Teen Employed 7 Old Employed 8 Child Unemployed 9 Child Employed 10 Adult Unemployed 11 Child Unemployed 12 Old Employed 13 Child Unemployed 14 Child Employed 15 Teen Employed 16 Adult Employed 17 Adult Unemployed 18 Old Employed 19 Adult Unemployed 20 Child Employed
Finding the counts of categories in both columns of df1 −
Example
table(df1$x1,df1$x2)
Output
Employed Unemployed Adult 3 4 Child 3 4 Old 3 1 Teen 2 0
Example2
y1<−sample(c("Married","Unmarried"),20,replace=TRUE)
y2<−sample(c("Satisfied","Not-Satisfied"),20,replace=TRUE)
df2<−data.frame(y1,y2)
df2Output
y1 y2 1 Married Not-Satisfied 2 Unmarried Not-Satisfied 3 Married Not-Satisfied 4 Unmarried Not-Satisfied 5 Married Satisfied 6 Married Not-Satisfied 7 Unmarried Satisfied 8 Married Satisfied 9 Unmarried Not-Satisfied 10 Unmarried Not-Satisfied 11 Unmarried Not-Satisfied 12 Unmarried Not-Satisfied 13 Married Satisfied 14 Married Satisfied 15 Married Satisfied 16 Married Not-Satisfied 17 Married Satisfied 18 Unmarried Satisfied 19 Married Satisfied 20 Married Satisfied
Finding the counts of categories in both columns of df2 −
Example
table(df2$y1,df2$y2)
Output
Not−Satisfied Satisfied Married 4 8 Unmarried 6 2
Updated on: 09-Feb-2021
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