I\'m trying to divide each number within a data frame with 16 columns by a specific number for each column. The numbers are stored as a data frame with 1-16 corresponding to
You could use transform
mx2 <- transform(mx,
X131.478.1=X131.478.1/sf["X131.478.1",1],
X131.478.2=X131.478.2/sf["X131.478.2",1],
etc
)
Quite a bit to type with 16 columns, but it should work.
This is nothing but element-wise matrix multiplication:
mat <- matrix(c(4,2,2,6,7,6, 93,73,88,86,58,65, 123,103,96,128,46,57), nrow=3, byrow=T)
vec = c(1.0660880,0.9104053,0.8642545,0.9611866,0.9711406,1.0560121)
mat %o% 1/vec
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 3.752035 2.080761 1.876018 6.242284 6.566062 6.242284
[2,] 102.152305 75.169342 96.660246 88.555663 63.707889 66.931606
[3,] 142.319190 97.536761 111.078392 121.210732 53.225063 53.976654
To do that we used the outer-product approach, since directly trying mat %*% 1/vec
gives an error on non-conformable arguments
because they have different shapes.
Or look at the many posts on https://stackoverflow.com/search?q=%5Br%5D+multiply+matrix+by+vector
Just for variety, you could also use mapply
mx <- structure(list(X131.478.1 = c(4L, 93L, 123L), X131.478.2 = c(2L,
73L, 103L), X131.NSC.1 = c(2L, 88L, 96L), X131.NSC.2 = c(6L,
86L, 128L), X166.478.1 = c(7L, 58L, 46L), X166.478.2 = c(6L,
65L, 57L)), .Names = c("X131.478.1", "X131.478.2", "X131.NSC.1",
"X131.NSC.2", "X166.478.1", "X166.478.2"), class = "data.frame", row.names = c("1/2-SBSRNA4",
"A1BG", "A1BG-AS1"))
sf <- structure(list(V1 = c(1.066088, 0.9104053, 0.8642545, 0.9611866,
0.9711406, 1.0560121)), .Names = "V1", row.names = c("X131.478.1",
"X131.478.2", "X131.NSC.1", "X131.NSC.2", "X166.478.1", "X166.478.2"
), class = "data.frame")
mapply(function(x, y) x * y, mx, t(sf))
X131.478.1 X131.478.2 X131.NSC.1 X131.NSC.2 X166.478.1 X166.478.2
[1,] 4.264352 1.820811 1.728509 5.76712 6.797984 6.336073
[2,] 99.146184 66.459587 76.054396 82.66205 56.326155 68.640787
[3,] 131.128824 93.771746 82.968432 123.03188 44.672468 60.192690
But for this I think Josh's answer is better... and Gavin's is even better!
Suppose we have a dataframe, df
:
> df
a b c
1 1 3 100
2 2 4 110
And we want to divide through each row by the same vector, vec
:
> vec <- df[1,]
> vec
a b c
1 1 3 100
Then we can use mapply
as follows:
> mapply('/', df, vec)
a b c
[1,] 1 1.000000 1.0
[2,] 2 1.333333 1.1
sweep
is useful for these sorts of operations, but it requires a matrix as input. As such, convert your data frame to a matrix, do the operation and then convert back. For example, some dummy data where we divide each element in respective columns of matrix mat
by the corresponding value in the vector vec
:
mat <- matrix(1:25, ncol = 5)
vec <- seq(2, by = 2, length = 5)
sweep(mat, 2, vec, `/`)
In use we have:
> mat
[,1] [,2] [,3] [,4] [,5]
[1,] 1 6 11 16 21
[2,] 2 7 12 17 22
[3,] 3 8 13 18 23
[4,] 4 9 14 19 24
[5,] 5 10 15 20 25
> vec
[1] 2 4 6 8 10
> sweep(mat, 2, vec, `/`)
[,1] [,2] [,3] [,4] [,5]
[1,] 0.5 1.50 1.833333 2.000 2.1
[2,] 1.0 1.75 2.000000 2.125 2.2
[3,] 1.5 2.00 2.166667 2.250 2.3
[4,] 2.0 2.25 2.333333 2.375 2.4
[5,] 2.5 2.50 2.500000 2.500 2.5
> mat[,1] / vec[1]
[1] 0.5 1.0 1.5 2.0 2.5
To convert from a data frame use as.matrix(df)
or data.matrix(df)
, and as.data.frame(mat)
for the reverse.