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I have time series data outputted from a lapply and would like to cbind them together starting from their respective start date. Here I set an example of 5 random generated time series starting from random generated dates.

set.seed(123)
d <- lapply(1:5,function(x) ts(rnorm(runif(1,5,20),0,10),start = floor(c(runif(1,2019,2020),runif(1,1,12))),frequency = 12))

I tried cbind, cbindna/cbind.na (package 'qpcR'), data.frame, cbind2, etc... I can not find the appropriate tool for this. Using a for loop filling the empty spaces seems silly. My desired output image:

Desired output

Darren Tsai
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Matthew Camilleri
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    Do you want to `cbind` (first elements get concatenated then second, etc) or do you want to `merge` by date? Your post says `cbind` but your desired output appears to be a merge/join. – emilliman5 Jul 06 '22 at 14:15

1 Answers1

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You just need cbind() from base. Use do.call() because d is a list.

d2 <- do.call(cbind, setNames(d, paste0('t', 1:length(d))))
Output
                 t1         t2         t3          t4         t5
Feb 2019         NA   3.598138         NA          NA         NA
Mar 2019         NA   4.007715         NA          NA  -2.416898
Apr 2019         NA   1.106827         NA          NA  -4.682005
May 2019         NA  -5.558411  -8.185157          NA  -7.729782
Jun 2019         NA  17.869131   6.849361          NA  21.499193
Jul 2019         NA   4.978505  -3.200564          NA -13.343536
Aug 2019         NA -19.666172 -13.115224          NA   4.958705
Sep 2019         NA   7.013559  -5.996083          NA  12.339762
Oct 2019   8.005543  -4.727914  -1.294107          NA   6.343621
Nov 2019  11.902066 -10.678237   8.867361 -12.6539635   4.120223
Dec 2019 -16.895557  -2.179749  -1.513960  21.6895597   7.935853
Jan 2020  12.394959 -10.260044   3.297912  12.0796200  -1.524106
Feb 2020  -1.089660  -7.288912 -32.273228 -11.2310858  -2.288958
Mar 2020  -1.172420  -6.250393  -7.717918  -4.0288484  -9.007918
Apr 2020   1.830826 -16.866933   2.865486  -4.6665535         NA
May 2020  12.805549         NA -12.205120   7.7996512         NA
Jun 2020 -17.272706         NA         NA  -0.8336907         NA
Jul 2020         NA         NA         NA   2.5331851         NA
Aug 2020         NA         NA         NA  -0.2854676         NA
Sep 2020         NA         NA         NA  -0.4287046         NA
Oct 2020         NA         NA         NA  13.6860228         NA
Nov 2020         NA         NA         NA  -2.2577099         NA
Dec 2020         NA         NA         NA  15.1647060         NA
Jan 2021         NA         NA         NA -15.4875280         NA
Feb 2021         NA         NA         NA   5.8461375         NA

The output is still a ts object.

class(d2)
# [1] "mts"    "ts"     "matrix"
Darren Tsai
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