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indexing into a data.frame using another data.frame that also contains values for replacement

3 messages · Alice Wines, Berend Hasselman, Dennis Murphy

Original
Alice Wines
# 
Hello all,

     I have a quandry I have been scratching my head about for a
while. I've searched the manual and the web and have not been able to
find an acceptable result, so I am hoping for some help.

     I have two data frames and I want to index into the first using
the second, and replace the specific values I have indexed with more
values from the second data.frame. I can do this using a loop, but I
wanted a quicker solution with no loops involved.

Although my data set is much larger than this, a small example of what
I am trying to do is as follows:

df1 <- data.frame(rows=c("A","B","C", "B", "C", "A"),
columns=c("21_2", "22_2", "23_2", "21_2", "22_2", "23_2"),
values=c(3.3, 2.5, 67.2, 44.3, 53, 66))
df2 <- data.frame(matrix(rep(NA, length(df1$values)),nrow=3, ncol=3))
names(df2) <- c("21_2", "22_2", "23_2")
row.names(df2) <- c("A", "B", "C")
rows columns values
1    A    21_2    3.3
2    B    22_2    2.5
3    C    23_2   67.2
4    B    21_2   44.3
5    C    22_2   53.0
6    A    23_2   66.0
21_2 22_2 23_2
A   NA   NA   NA
B   NA   NA   NA
C   NA   NA   NA


     Note that none of the same locations in df2 are specified twice
in df2, so I'm not worried about over-writing it.

    I have tried 'mapply' and 'replace', but apparently either they do
not work well for this or I don't understand how to use them properly
for this purpose. My understanding is that 'replace' needs a vector
input and that one cannot create a vector of vectors, so I couldn't
pass my indices to 'replace'.

     When I tried mapply, the code I used was something like what follows:

df3 <- mapply('[<-' , df2, paste(as.character(df1$rows),
as.character(df1$columns), sep=', '), df1$values)

but it yields the following strange result
21_2 22_2 23_2 <NA> <NA> <NA>
          NA   NA   NA   NA   NA   NA
          NA   NA   NA   NA   NA   NA
          NA   NA   NA   NA   NA   NA
A, 21_2  3.3  2.5 67.2 44.3   53   66


What I want to see is the following:
21_2   22_2  23_2
A   3.3    NA    66.0
B   44.3  2.5    NA
C   NA   53.0   67.2


     I will greatly appreciate any help that can be given as I am
completely bamboozled by this problem and although I found many useful
things in my search for an answer, I did not find out how to do this.

Thanks,

Alice
Berend Hasselman
#
Alice Wines wrote:
How about this (I have converted df2 into a matrix)

df2 <- matrix(rep(NA, length(df1$values)),nrow=3, ncol=3)
colnames(df2) <- c("21_2", "22_2", "23_2")
rownames(df2) <- c("A", "B", "C")

df2[cbind(df1$rows,df1$columns)] <- df1$values

# convert df2 to a data.frame

Berend--
View this message in context: http://r.789695.n4.nabble.com/indexing-into-a-data-frame-using-another-data-frame-that-also-contains-values-for-replacement-tp3487147p3487234.html
Sent from the R help mailing list archive at Nabble.com.
Dennis Murphy
# 
Hi:

Here are two possibilities:

 df1 <- data.frame(rows=c("A","B","C", "B", "C", "A"),
 columns=c("21_2", "22_2", "23_2", "21_2", "22_2", "23_2"),
 values=c(3.3, 2.5, 67.2, 44.3, 53, 66))

with(df1, xtabs(values ~ rows + columns))

    columns
rows 21_2 22_2 23_2
   A  3.3  0.0 66.0
   B 44.3  2.5  0.0
   C  0.0 53.0 67.2

library(reshape2)
dcast(df1, rows ~ columns)

Using values as value column: use value_var to override.
  rows 21_2 22_2 23_2
1    A  3.3   NA 66.0
2    B 44.3  2.5   NA
3    C   NA 53.0 67.2

HTH,
Dennis
On Sat, Apr 30, 2011 at 4:18 PM, Alice Wines <aabroadh at ncsu.edu> wrote: