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Replace numerical column values based on character column values in R data frame.
To replace numerical column values based on character column values in R data frame, we can use subsetting with single square brackets and %in% operator and the value will be assigned with <-.
To understand how it can be done check out the Examples given below −
Example 1
Following snippet creates a sample data frame −
Class<-sample(c("First","Second","Third"),20,replace=TRUE)
Score<-sample(1:100,20)
df1<-data.frame(Class,Score)
df1The following dataframe is created
Class Score 1 Second 25 2 First 11 3 Second 63 4 Third 77 5 Third 62 6 Third 26 7 First 83 8 Third 57 9 First 15 10 Third 16 11 Second 7 12 First 87 13 First 35 14 First 91 15 First 40 16 Second 60 17 Second 81 18 Second 75 19 Second 56 20 Second 32
To replace values corresponding to “Third” in Class to 35 in Score on the above created data frame, add the following code to the above snippet −
Class<-sample(c("First","Second","Third"),20,replace=TRUE)
Score<-sample(1:100,20)
df1<-data.frame(Class,Score)
df1$Score[df1$Class %in% "Third"]<-35
df1Output
If you execute all the above given snippets as a single program, it generates the following Output −
Class Score 1 Second 25 2 First 11 3 Second 63 4 Third 35 5 Third 35 6 Third 35 7 First 83 8 Third 35 9 First 15 10 Third 35 11 Second 7 12 First 87 13 First 35 14 First 91 15 First 40 16 Second 60 17 Second 81 18 Second 75 19 Second 56 20 Second 32
Example 2
Following snippet creates a sample data frame −
Country<-sample(c("UK","UK","USA","Japan","India"),20,replace=TRUE)
Ranks<-sample(1:5,20,replace=TRUE)
df2<-data.frame(Country,Ranks)
df2The following dataframe is created
Country Ranks 1 Japan 3 2 Japan 3 3 India 2 4 India 3 5 Japan 2 6 UK 1 7 Japan 5 8 UK 5 9 UK 1 10 UK 4 11 India 4 12 USA 1 13 UK 2 14 UK 5 15 USA 1 16 Japan 3 17 UK 1 18 India 4 19 Japan 3 20 Japan 5
To replace values corresponding to “India” and “Japan” in Country to 3 in Ranks on the above created data frame, add the following code to the above snippet −
Country<-sample(c("UK","UK","USA","Japan","India"),20,replace=TRUE)
Ranks<-sample(1:5,20,replace=TRUE)
df2<-data.frame(Country,Ranks)
df2$Ranks[df2$Country %in% c("India","Japan")]<-3
df2Output
If you execute all the above given snippets as a single program, it generates the following Output −
Country Ranks 1 Japan 3 2 Japan 3 3 India 3 4 India 3 5 Japan 3 6 UK 1 7 Japan 3 8 UK 5 9 UK 1 10 UK 4 11 India 3 12 USA 1 13 UK 2 14 UK 5 15 USA 1 16 Japan 3 17 UK 1 18 India 3 19 Japan 3 20 Japan 3
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