Why does assignment to reference (:=) give different results when running code say two or three times within data.table format?

strauss Published at Dev

strauss

I thank all of you for your precious time. I would like to have a table with the first column with no lag, the second column with one lag down, the third column with two lags down, etc., as in the picture. I have code that actually does the job but only if you run the code once. If you run the code two or three times you will notice that additional shifts (lags) occur. I would be very grateful if any of you could help me get the same result no matter how many times the code is run.

Screenshot:

library(dplyr)
library(data.table)
d <- structure(list(inv = c(20, 18, 46, 28, 10, 17, 96, 37), c = c(1, 0.999735, 0.912009, 0.596777, 
  0.293534, 0.122216, 0.046563, 0.016929)), row.names = c(NA, -8L), class = c("tbl_df", "tbl", "data.frame"))
G <- matrix(d$inv)
W <- matrix(d$c)
K <- cbind(W%x%t(G))
dtK <- data.table(K)
z <-  dtK[, names(dtK) := Map(shift, .SD, seq_along(.SD)-1L, fill = 0), .SDcols = names(dtK)]
z

Ian Campbell

The := operator assigns by reference within the dtK object.

That means the original dtK object is changed regardless of whether you assign it to z or not.

Try running just the following and seeing what happens:

dtK[, names(dtK) := Map(shift, .SD, seq_along(.SD)-1L, fill = 0), .SDcols = names(dtK)]
dtK
         V1        V2        V3        V4       V5       V6       V7 V8
1: 20.00000  0.000000  0.000000  0.000000  0.00000  0.00000  0.00000  0
2: 19.99470 18.000000  0.000000  0.000000  0.00000  0.00000  0.00000  0
3: 18.24018 17.995230 46.000000  0.000000  0.00000  0.00000  0.00000  0
4: 11.93554 16.416162 45.987810 28.000000  0.00000  0.00000  0.00000  0
5:  5.87068 10.741986 41.952414 27.992580 10.00000  0.00000  0.00000  0
6:  2.44432  5.283612 27.451742 25.536252  9.99735 17.00000  0.00000  0
7:  0.93126  2.199888 13.502564 16.709756  9.12009 16.99550 96.00000  0
8:  0.33858  0.838134  5.621936  8.218952  5.96777 15.50415 95.97456 37

One way out of this problem is to make a copy with copy:

dtK <- data.table(K)
z <- copy(dtK)[, names(dtK) := Map(shift, .SD, seq_along(.SD)-1L, fill = 0), .SDcols = names(dtK)]
dtK
         V1        V2        V3        V4       V5        V6        V7        V8
1: 20.00000 18.000000 46.000000 28.000000 10.00000 17.000000 96.000000 37.000000
2: 19.99470 17.995230 45.987810 27.992580  9.99735 16.995495 95.974560 36.990195
3: 18.24018 16.416162 41.952414 25.536252  9.12009 15.504153 87.552864 33.744333
4: 11.93554 10.741986 27.451742 16.709756  5.96777 10.145209 57.290592 22.080749
5:  5.87068  5.283612 13.502564  8.218952  2.93534  4.990078 28.179264 10.860758
6:  2.44432  2.199888  5.621936  3.422048  1.22216  2.077672 11.732736  4.521992
7:  0.93126  0.838134  2.141898  1.303764  0.46563  0.791571  4.470048  1.722831
8:  0.33858  0.304722  0.778734  0.474012  0.16929  0.287793  1.625184  0.626373

Check out vignette("datatable-reference-semantics") for more.

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Please contact [email protected] to delete if infringement.

edited at2020-12-15

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Why does assignment to reference (:=) give different results when running code say two or three times within data.table format?

Why does assignment to reference (:=) give different results when running code say two or three times within data.table format?

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