Find Frequency of a String in R Data Frame using dplyr

When we have two or more categorical columns in an R data frame with strings as level of the categories or numbers as strings/integers then we can find the frequency of one based on another. This will help us to identify the cross-column frequencies and we can understand the distribution of one categorical based on another column. To do this with dplyr package, we can use filter function.

Example

 Live Demo

Consider the below data frame −

Group<−sample(1:5,20,replace=TRUE)
Standard<−sample(c("I","II","III"),20,replace=TRUE)
df1<−data.frame(Group,Standard)
df1

Output

Group Standard
1 3 III
2 5 III
3 5 I
4 3 I
5 2 II
6 4 II
7 3 III
8 2 I
9 1 II
10 4 III
11 3 II
12 4 III
13 4 III
14 4 III
15 4 III
16 4 III
17 5 III
18 3 II
19 5 III
20 1 III

Finding the frequency of Groups for Standards −

library(dplyr)
df1%>%filter(Standard=="I")%>%count(Group)

Output

Group n
1 2 1
2 3 1
3 5 1

Example

df1%>%filter(Standard=="II")%>%count(Group)

Output

Group n
1 1 1
2 2 1
3 3 2
4 4 1

Example

df1%>%filter(Standard=="III")%>%count(Group)

Output

Group n
1 1 1
2 3 2
3 4 6
4 5 3

Let’s have a look at another example −

 Live Demo

Class<−sample(c("First","Second","Third"),20,replace=TRUE)
Gender<−sample(c("Male","Female"),20,replace=TRUE)
df2<−data.frame(Gender,Class)
df2

Output

Gender Class
1 Female Third
2 Female First
3 Female Second
4 Male Third
5 Male Third
6 Female Second
7 Male First
8 Female Third
9 Female Second
10 Female Second
11 Female First
12 Female Second
13 Male First
14 Female Third
15 Female Third
16 Male Third
17 Male Third
18 Male Second
19 Female Second
20 Male Second
df2%>%filter(Class=="Third")%>%count(Gender)
Gender n
1 Female 4
2 Male 4
df2%>%filter(Class=="First")%>%count(Gender)
Gender n
1 Female 2
2 Male 2
df2%>%filter(Class=="Second")%>%count(Gender)
Gender n
1 Female 6
2 Male 2