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
How to change row values based on column values in an R data frame?
Changing row values based on column values means that we want to change the row values for a particular column if the column values satisfy a certain condition. For example, if we have a data frame called df that contains a column say x and we want to set all the values in x to 5 if they are greater than 5 then it can be done as df[df$x>5,]<-5.
Example1
Consider the below data frame −
> x1<-rpois(20,1) > x2<-rpois(20,5) > df1<-data.frame(x1,x2) > df1
Output
x1 x2 1 3 10 2 3 3 3 1 8 4 2 4 5 1 7 6 1 4 7 2 4 8 0 9 9 2 10 10 2 6 11 1 4 12 1 7 13 1 4 14 1 5 15 2 2 16 4 3 17 3 4 18 0 1 19 0 1 20 0 7
Changing values in x1 to 2 if they are greater than 2 −
> df1[df1$x1>2,]<-2 > df1
Output
x1 x2 1 2 2 2 2 2 3 1 8 4 2 4 5 1 7 6 1 4 7 2 4 8 0 9 9 2 10 10 2 6 11 1 4 12 1 7 13 1 4 14 1 5 15 2 2 16 2 2 17 2 2 18 0 1 19 0 1 20 0 7
Example2
> y1<-rnorm(20,5,1) > y2<-rnorm(20,5,0.3) > df2<-data.frame(y1,y2) > df2
Output
y1 y2 1 4.826729 5.433352 2 3.530581 5.266034 3 5.811061 4.582195 4 5.620806 5.745011 5 4.799159 5.323772 6 5.287042 5.111730 7 5.128602 5.192648 8 4.372339 5.014256 9 5.078192 5.175813 10 4.392499 5.231547 11 4.983643 5.390611 12 4.168723 4.620990 13 2.691008 4.932305 14 3.715511 4.455306 15 3.674058 5.136752 16 5.439690 5.082509 17 6.393444 4.139432 18 5.220288 5.201459 19 4.695000 4.960111 20 5.925427 5.013475
Changing values in y1 to 3 if they are greater than 3 −
> df2[df2$y1>3,]<-3 > df2
Output
y1 y2 1 3.000000 3.000000 2 3.000000 3.000000 3 3.000000 3.000000 4 3.000000 3.000000 5 3.000000 3.000000 6 3.000000 3.000000 7 3.000000 3.000000 8 3.000000 3.000000 9 3.000000 3.000000 10 3.000000 3.000000 11 3.000000 3.000000 12 3.000000 3.000000 13 2.691008 4.932305 14 3.000000 3.000000 15 3.000000 3.000000 16 3.000000 3.000000 17 3.000000 3.000000 18 3.000000 3.000000 19 3.000000 3.000000 20 3.000000 3.000000
Updated on: 05-Mar-2021
358 Views
Advertisements