0

I'm struggling to replace some of the values in a column in R. In my dataframe, there are more than 100000 rows; however, I'm simplifying things here. Let's consider this imaginary data frame:

ID<-c("Rick","Anna","Sarah","Mike","Kim","Garrett","Tom")
Age<-c(31,23,26,43,32,41,22)
df1<-cbind(ID,Age)

ID        Age

Rick      31
Anna      23
Sarah     26
Mike      43
Kim       32
Garrett   41
Tom       22

However, some of age information in this data frame is wrong and df2 has the correct information for age.

ID<-c("Rick","Tom")
Age<-c(35,23)
df2<-cbind(ID,Age)

ID      Age
Rick    35
Tom     23

My question is, how can I take the correct values in df2 and supply them to df1?

I have tried the solutions in other similar situations on stackoverflow including:

df1$Age<-df2$Age[df1$ID %in% df2$ID]
df1$Age<-df2$Age[match(df1$ID, df2$ID]

These codes take the values in df2 and returns NAs for IDs that are not available in df2.

I need suggestions, please.

user6813867
  • 1
  • 3
  • The solution presented in the suggested link doesn't apply to my problem. I still need suggestions. – user6813867 Nov 29 '16 at 10:17
  • I have found the answer in this link: http://stackoverflow.com/questions/32239581/replacing-values-in-a-column-with-another-column-r – user6813867 Nov 30 '16 at 07:49

0 Answers0