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Convert the values in a column into row names in an existing data frame

I would like to convert the values in a column of an existing data frame into row names. Is is possible to do this without exporting the data frame and then reimporting it with a row.names = call?

For example I would like to convert:

 > samp 
     names Var.1 Var.2 Var.3
 1     A     1     5     0
 2     B     2     4     1
 3     C     3     3     2
 4     D     4     2     3
 5     E     5     1     4

Into:

> samp.with.rownames 
     Var.1 Var.2 Var.3
A     1     5     0
B     2     4     1
C     3     3     2
D     4     2     3
E     5     1     4

This should do:

samp2 <- samp[,-1]
rownames(samp2) <- samp[,1]

So in short, no there is no alternative to reassigning.

Edit: Correcting myself, one can also do it in place: assign rowname attributes, then remove column:

R> df<-data.frame(a=letters[1:10], b=1:10, c=LETTERS[1:10])
R> rownames(df) <- df[,1]
R> df[,1] <- NULL
R> df
   b c
a  1 A
b  2 B
c  3 C
d  4 D
e  5 E
f  6 F
g  7 G
h  8 H
i  9 I
j 10 J
R> 

As of 2016 you can also use the tidyverse .

library(tidyverse)
samp %>% remove_rownames %>% column_to_rownames(var="names")

一行

> samp.with.rownames <- data.frame(samp[,-1], row.names=samp[,1])

You can execute this in 2 simple statements:

row.names(samp) <- samp$names
samp[1] <- NULL

It looks like the one-liner got even simpler along the line (currently using R 3.5.3):

# generate original data.frame
df <- data.frame(a = letters[1:10], b = 1:10, c = LETTERS[1:10])
# use first column for row names
df <- data.frame(df, row.names = 1)

The column used for row names is removed automatically.

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