CODEWITHSUNDEEP
rdata.table
Crops
Crops

Reputation: 5154

Insert a row of NAs after each group of data using data.table

I am trying to add a row of NAs after each group of data in R.

A similar question has been asked earlier. Insert a blank row after each group of data.

The accepted answer works fine in this case too as follows.

group <- c("a","b","b","c","c","c","d","d","d","d")
xvalue <- c(16:25)
yvalue <- c(1:10)
df <- data.frame(cbind(group,xvalue,yvalue))
df_new <- as.data.frame(lapply(df, as.character), stringsAsFactors = FALSE)
head(do.call(rbind, by(df_new, df$group, rbind, NA)), -1 )
     group xvalue yvalue
a.1      a     16      1
a.2   <NA>   <NA>   <NA>
b.2      b     17      2
b.3      b     18      3
b.31  <NA>   <NA>   <NA>
c.4      c     19      4
c.5      c     20      5
c.6      c     21      6
c.41  <NA>   <NA>   <NA>
d.7      d     22      7
d.8      d     23      8
d.9      d     24      9
d.10     d     25     10

How can I speed this up using data.table for a large data.frame?

Upvotes: 8

Views: 1864

Answers (2)

akrun
akrun

Reputation: 887108

You could try

df$group <- as.character(df$group)
setDT(df)[, .SD[1:(.N+1)], by=group][is.na(xvalue), group:=NA][!.N]
#     group xvalue yvalue
#1:     a     16      1
#2:    NA     NA     NA
#3:     b     17      2
#4:     b     18      3
#5:    NA     NA     NA
#6:     c     19      4
#7:     c     20      5
#8:     c     21      6
#9:    NA     NA     NA
#10:    d     22      7
#11:    d     23      8
#12:    d     24      9
#13:    d     25     10

Or as suggested by @David Arenburg

 setDT(df)[, indx := group][, .SD[1:(.N+1)], indx][,indx := NULL][!.N]

Or

 setDT(df)[df[,.I[1:(.N+1)], group]$V1][!.N]

Or it could be further simplified based on @eddi's comments

 setDT(df)[df[, c(.I, NA), group]$V1][!.N]

Upvotes: 10

Arun
Arun

Reputation: 118799

One way I could think of is to construct a vector first as follows:

foo <- function(x) {
    o = order(rep.int(seq_along(x), 2L))
    c(x, rep.int(NA, length(x)))[o]
}
join_values = head(foo(unique(df_new$group)), -1L)
# [1] "a" NA  "b" NA  "c" NA  "d"

And then setkey() and join.

setkey(setDT(df_new), group)
df_new[.(join_values), allow.cartesian=TRUE]
#     group xvalue yvalue
#  1:     a     16      1
#  2:    NA     NA     NA
#  3:     b     17      2
#  4:     b     18      3
#  5:    NA     NA     NA
#  6:     c     19      4
#  7:     c     20      5
#  8:     c     21      6
#  9:    NA     NA     NA
# 10:     d     22      7
# 11:     d     23      8
# 12:     d     24      9
# 13:     d     25     10

Upvotes: 5

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