Remove rows which have all NA's, apart from the first column

Question

I have a data.table which was formed by taking the differences between two panel observations using:

tab <- tab[,
   lapply(.SD, function(x) x - shift(x)), 
   by = A, 
   .SDcols = (sapply(tab, is.numeric))
  ]

tab = data.table(A = c(1, 1, 2, 2), B = c(NA, 2, NA, 1), C = c(NA, NA, NA, 2), D=c(NA, 3, NA, 2))
tab
    A  B  C  D
1:  1  NA NA NA
2:  1  2  NA 3
3:  2  NA NA NA
4:  2  1  2  2

I would like to use this answer:

tab <- tab [!Reduce(`&`, lapply(tab , is.na))]

to remove rows 1 and 3, but this does not work because the first column is not NA. How can I adapt the code to solve this?

Desired outcome:

    A  B  C  D
1:  1  2  NA 3
2:  2  1  2  2

@Cath Because there is no data.table answer in the target. I don't have to check into whether the dupe target itself is nested to another one — akrun, Jul 03 '19 at 15:19

score 2 · Answer 1 · answered Jul 03 '19 at 14:09

2

tab[tab[, rowSums(!is.na(.SD)) > 1, .SDcols = -1]]

answered Jul 03 '19 at 14:09

s_baldur

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score 0 · Accepted Answer · edited Jul 03 '19 at 14:23

0

In this case we can specify the columns in .SDcols

tab[tab [, !Reduce(`&`, lapply(.SD , is.na)), .SDcols = 2:ncol(tab)]]

edited Jul 03 '19 at 14:23

Cath

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answered Jul 03 '19 at 14:07

akrun

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Remove rows which have all NA's, apart from the first column

2 Answers2

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