Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Convert a numeric column to binary factor based on a condition in R data frame
To convert a numeric column to binary factor based on a condition in R data frame, we can use factor function along with ifelse function.
For Example, if we have a data frame called df that contains a numerical column say Num and we want to convert it to a binary factor if Num is less than 100 then it will be Minor otherwise Major then we can use the below given command −
df$Num_Factor<-factor(ifelse(df$Num_Factor<100,"Minor","Major"))
Example 1
Following snippet creates a sample data frame −
x<-sample(1:50,20) df1<-data.frame(x) df1
The following dataframe is created
x 1 4 2 13 3 50 4 19 5 43 6 42 7 18 8 17 9 27 10 23 11 31 12 37 13 5 14 28 15 1 16 6 17 30 18 35 19 22 20 10
To convert x into a factor column on the above created data frame, add the following code to the above snippet −
x<-sample(1:50,20) df1<-data.frame(x) df1$x_Factor<-factor(ifelse(df1$x<25,"Low","High")) df1
Output
If you execute all the above given snippets as a single program, it generates the following Output −
x x_Factor 1 4 Low 2 13 Low 3 50 High 4 19 Low 5 43 High 6 42 High 7 18 Low 8 17 Low 9 27 High 10 23 Low 11 31 High 12 37 High 13 5 Low 14 28 High 15 1 Low 16 6 Low 17 30 High 18 35 High 19 22 Low 20 10 Low
Example 2
Following snippet creates a sample data frame −
y<-round(rnorm(20,1,0.25),1) df2<-data.frame(y) df2
The following dataframe is created
y 1 1.4 2 0.9 3 1.0 4 0.6 5 1.1 6 0.7 7 0.9 8 1.2 9 0.8 10 1.1 11 0.7 12 0.4 13 1.1 14 0.8 15 1.1 16 0.7 17 1.7 18 0.8 19 1.1 20 0.6
To convert y into a factor column on the above created data frame, add the following code to the above snippet −
y<-round(rnorm(20,1,0.25),1) df2<-data.frame(y) df2$y_Factor<-factor(ifelse(df2$y<1,"Rejected","Accepted")) df2
Output
If you execute all the above given snippets as a single program, it generates the following Output −
y y_Factor
1 1.4 Accepted
2 0.9 Rejected
3 1.0 Accepted
4 0.6 Rejected
5 1.1 Accepted
6 0.7 Rejected
7 0.9 Rejected
8 1.2 Accepted
9 0.8 Rejected
10 1.1 Accepted
11 0.7 Rejected
12 0.4 Rejected
13 1.1 Accepted
14 0.8 Rejected
15 1.1 Accepted
16 0.7 Rejected
17 1.7 Accepted
18 0.8 Rejected
19 1.1 Accepted
20 0.6 Rejected
3K+ Views
