Normalize each row of data.table
This seems like it should be easy, but I can't find an answer :(. I'm trying to normalize each row of a data_table like this:
normalize <- function(x) {
s = sum(x)
if (s>0) {
return(x/s)
} else {
return 0
}
}
How do I call this function on every row of a data.table and get a normalized data.table back? I can do a for loop, but that's surely not the right way, and apply(data, 1, normalize) will, as I understand, convert my data.table to a matrix which will be a big performance hit.
Here's one way to avoid coercing to a matrix:
cols = names(DT)
DT[, s := Reduce("+",.SD)]
DT[s > 0, (cols) := lapply(.SD,"/",s), .SDcols = cols]
DT[s <= 0, (cols) := 0]
DT[, s := NULL]
This is what I would do if there was a good reason to use a data.table over a matrix (in a later step).
Considering this example data set (next time, please provide an example data set yourself)
set.seed(123)
DT <- data.table(x = rnorm(10), y = rnorm(10), z = rnorm(10))
I would try avoiding by row operations and vecotrize using rowSums , something like the following
DT[, names(DT) := {temp = rowSums(.SD) ; (.SD / temp) * (temp > 0)}]
DT
# x y z
# 1: 0.0000000 0.0000000 0.0000000
# 2: 0.0000000 0.0000000 0.0000000
# 3: 1.6697906 0.4293327 -1.0991233
# 4: 0.0000000 0.0000000 0.0000000
# 5: 0.0000000 0.0000000 0.0000000
# 6: 0.9447911 0.9843707 -0.9291618
# 7: 0.2565558 0.2771142 0.4663301
# 8: 0.0000000 0.0000000 0.0000000
# 9: 0.0000000 0.0000000 0.0000000
# 10: -1.3289000 -1.4097961 3.7386962
The reason I've created temp is in order to avoid running rowSums(.SD) twice. The *(temp > 0) part is basically your if and else statement. It returns a logical vector of TRUE/FALSE which then converted to 1/0 and then multiplied against (.SD/temp)
Here's what I came up with. First you need to edit your function (I believe), so that it returns rep(0, length(x)) instead of just 0 .
set.seed(123); DT <- data.table(x=rnorm(1e3), y=rnorm(1e3), z=rnorm(1e3))
> DT
x y z
1: -0.56047565 -0.99579872 -0.5116037
2: -0.23017749 -1.03995504 0.2369379
3: 1.55870831 -0.01798024 -0.5415892
4: 0.07050839 -0.13217513 1.2192276
5: 0.12928774 -2.54934277 0.1741359
---
996: -0.08997520 0.07664366 1.0609662
997: 1.07051604 0.25516476 -0.4455056
998: -1.35110039 0.27744682 -0.4291802
999: -0.52261670 0.53685602 1.1890118
1000: -0.24919068 -0.46048557 0.8342941
> DT[, c('x', 'y', 'z') := as.list(normalize(c(x, y, z))), by=1:nrow(DT)]
> DT
x y z
1: 0.00000000 0.00000000 0.0000000
2: 0.00000000 0.00000000 0.0000000
3: 1.56005167 -0.01799574 -0.5420559
4: 0.06091117 -0.11418417 1.0532730
5: 0.00000000 0.00000000 0.0000000
---
996: -0.08588413 0.07315877 1.0127254
997: 1.21625341 0.28990225 -0.5061557
998: 0.00000000 0.00000000 0.0000000
999: -0.43433718 0.44617122 0.9881660
1000: -1.99963905 -3.69518205 6.6948211
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