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How to create table of two factor columns in an R data frame?
To create table of two factor columns in an R data frame, we can use table function and with function.
For Example, if we have a data frame called df that contains two factor columns say F1 and F2 then we can create table of these two columns by using the below command −
with(df,table(F1,F2))
Example 1
Following snippet creates a sample data frame −
Group<-sample(c("G1","G2","G3"),20,replace=TRUE)
Class<-sample(c("First","Second","Third"),20,replace=TRUE)
df1<-data.frame(Group,Class)
df1The following dataframe is created
Group Class 1 G1 First 2 G2 First 3 G3 First 4 G2 First 5 G1 Second 6 G2 Second 7 G3 Second 8 G3 Third 9 G2 First 10 G1 Third 11 G1 Second 12 G3 Second 13 G1 Second 14 G1 Third 15 G2 Second 16 G1 Second 17 G3 Third 18 G1 Second 19 G3 First 20 G1 Third
To create table of column Group and Class on the above created data frame, add the following code to the above snippet −
Group<-sample(c("G1","G2","G3"),20,replace=TRUE)
Class<-sample(c("First","Second","Third"),20,replace=TRUE)
df1<-data.frame(Group,Class)
with(df1,table(Group,Class))Output
If you execute all the above given snippets as a single program, it generates the following Output −
Class Group First Second Third G1 1 5 3 G2 3 2 0 G3 2 2 2
Example 2
Following snippet creates a sample data frame −
Gender<-sample(c("Male","Female"),20,replace=TRUE)
Sal_Group<-sample(c("<=10K","10K and <=20K","=20K"),20,replace=TRUE)
df2<-data.frame(Gender,Sal_Group)
df2The following dataframe is created
Gender Sal_Group 1 Male =20K 2 Male <=10K 3 Female <=10K 4 Male 10K and <=20K 5 Male <=10K 6 Female <=10K 7 Female 10K and <=20K 8 Female 10K and <=20K 9 Female =20K 10 Male =20K 11 Female 10K and <=20K 12 Male <=10K 13 Male =20K 14 Male =20K 15 Female 10K and <=20K 16 Male 10K and <=20K 17 Female <=10K 18 Female <=10K 19 Male =20K 20 Female 10K and <=20K
To create table of column Gender and Sal_Group on the above created data frame, add the following code to the above snippet −
Gender<-sample(c("Male","Female"),20,replace=TRUE)
Sal_Group<-sample(c("<=10K","10K and <=20K","=20K"),20,replace=TRUE)
df2<-data.frame(Gender,Sal_Group)
with(df2,table(Gender,Sal_Group))Output
If you execute all the above given snippets as a single program, it generates the following Output −
Sal_Group Gender <=10K =20K 10K and <=20K Female 4 1 5 Male 3 5 2
Example 3
Following snippet creates a sample data frame −
Category<-sample(c("C1","C2","C3","C4"),20,replace=TRUE)
Sample<-sample(1:4,20,replace=TRUE)
df3<-data.frame(Category,Sample)
df3The following dataframe is created
Category Sample 1 C4 4 2 C2 3 3 C2 3 4 C1 3 5 C3 4 6 C1 4 7 C2 1 8 C1 1 9 C1 1 10 C1 2 11 C4 3 12 C1 3 13 C4 2 14 C1 3 15 C4 2 16 C3 4 17 C1 3 18 C2 4 19 C1 2 20 C1 2
To create table of column Category and Sample on the above created data frame, add the following code to the above snippet −
Category<-sample(c("C1","C2","C3","C4"),20,replace=TRUE)
Sample<-sample(1:4,20,replace=TRUE)
df3<-data.frame(Category,Sample)
with(df3,table(Category,Sample))Output
If you execute all the above given snippets as a single program, it generates the following Output −
Sample
Category 1 2 3 4
C1 2 3 4 1
C2 1 0 2 1
C3 0 0 0 2
C4 0 2 1 1
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