2

I have two columns in a data frame that represent addresses. I need to melt the two and recast as a single column and am having trouble wrapping my head around reshape2. Example:

          A                     B
    123 address st        122 address st
    125 address st        124 address st 
    127 address st        126 address st

and I need this as the output 

          C
    122 address st
    123 address st 
    125 address st
    124 address st
    127 address st
    126 address st

edit: Let me be a little more specific: order does not matter and there are a great deal of columns in the data frame I am working within, not just the two that need to be merged. It would be great if a new, seperate data frame could be created that is a single column with all the data from address column 1 (A) and address column 2 (B). The addresses (obviously) need to be preserved in their current form. Some answers given have been mashing the data together in a way that does solve this issue.

Connor M
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3 Answers3

2

You can try

data.frame(C=c(t(df)), stringsAsFactors=FALSE)
 #             C
 #1 123 address st
 #2 122 address st
 #3 125 address st
 #4 124 address st
 #5 127 address st
 #6 126 address st
akrun
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1

Melting and recasting will also preserve which column the original data came from. This is useful if you still need that information, but not as a seperate column. For example:

library(reshape2)
A <- c('123 address st', '125 address st', '127 address st')
B <- c('122 address st', '124 address st', '126 address st')
DF <- data.frame(A, B, stringsAsFactors = FALSE)
DF2 <- melt(data = DF, value.name = 'C', measure.vars = c('A', 'B'))

Will return

> DF
               A              B
1 123 address st 122 address st
2 125 address st 124 address st
3 127 address st 126 address st

> DF2
  variable              C
1        A 123 address st
2        A 125 address st
3        A 127 address st
4        B 122 address st
5        B 124 address st
6        B 126 address st

If you need it sorted, you can use the dplyr pacakge for that rather easily:

library(dplyr)
arrange(DF2, C)

Returns:

  variable              C
1        B 122 address st
2        A 123 address st
3        B 124 address st
4        A 125 address st
5        B 126 address st
6        A 127 address st

And if you want to remove that pesky variable column, you can also use dplyer. Using it's magrittr-based piping functionality:

> DF3 <- select(DF2, C) %>% arrange(C)
> DF3
               C
1 122 address st
2 123 address st
3 124 address st
4 125 address st
5 126 address st
6 127 address st
Avraham
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0

It may be easier than you think. Do you need to stack the columns?

df2 = data.frame(C=rbind(df$A, df$B))
vpipkt
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