How to convert list of dates to POSIXlt objects? - r

I want to run the bfastts function (https://www.rdocumentation.org/packages/bfast/versions/1.5.7/topics/bfastts) on a series of dates formatted as dd-mm-yyyy and a series of values to convert them into a time series. For this function the dates need to be of "POSIXlt" type. However, when running the code
dv<-as.POSIXct.POSIXlt(dates, tz="")
I am getting the error
Error in as.POSIXct.POSIXlt(dates, tz = "") : invalid 'x' argument
When running
dv<-strftime(as.POSIXct.POSIXlt(dates, tz="")
The returned list seems to be empty. When inputting my date list without conversion into the bfastts I'm getting the error
Error in as.POSIXlt.default(dates) :
do not know how to convert 'dates' to class “POSIXlt”
I am not used to coding in R as I usually work in python. I've tried googling all three errors but I can't find a solution. Could any one provide me some pointers?
Edit:
dput(dates) gives me:
list(V1 = structure(c(19L, 57L, 31L, 59L, 33L, 34L, 4L, 7L, 40L,
12L, 50L, 56L, 3L, 37L, 6L, 39L, 46L, 17L, 43L, 55L, 30L, 2L,
36L, 38L, 11L, 21L, 49L, 24L, 27L, 10L, 45L, 14L, 1L, 18L, 47L,
54L, 29L, 32L, 8L, 42L, 9L, 16L, 44L, 48L, 23L, 51L, 52L, 26L,
35L, 5L, 15L, 20L, 22L, 25L, 53L, 28L, 58L, 41L, 13L), .Label = c("1-8-
2016", "11-5-2015", "11-7-2014", "12-10-2013", "12-2-2018", "12-8-2014",
"13-11-2013", "13-3-2017", "14-4-2017", "14-6-2016", "14-7-2015",
"15-12-2013", "15-2-2019", "16-7-2016", "17-4-2018", "17-6-2017",
"18-12-2014", "18-9-2016", "19-4-2013", "19-5-2018", "2-10-2015",
"20-6-2018", "20-8-2017", "21-12-2015", "22-7-2018", "23-10-2017",
"23-2-2016", "23-8-2018", "24-1-2017", "24-3-2015", "24-7-2013",
"25-2-2017", "25-8-2013", "26-9-2013", "27-1-2018", "27-5-2015",
"27-7-2014", "28-6-2015", "28-8-2014", "29-11-2013", "29-12-2018",
"29-3-2017", "3-1-2015", "3-7-2017", "30-6-2016", "31-10-2014",
"4-10-2016", "4-8-2017", "5-12-2015", "5-3-2014", "5-9-2017",
"7-10-2017", "7-8-2018", "8-1-2017", "8-3-2015", "8-5-2014",
"8-7-2013", "8-9-2018", "9-8-2013"), class = "factor"))


The problem is that dates is a list, but you actually want to access the first entry (V1) of it. Further you have to specify that the dates you are providing are in the format dd-mm-yyyy. This you can do with format = "%d-%m-%Y". Thus the following works:
as.POSIXlt(dates$V1, format = "%d-%m-%Y", tz="")
# [1] "2013-04-19 CEST" "2013-07-08 CEST" "2013-07-24 CEST" "2013-08-09 CEST"
# ...
Data
dates <- list(V1 = structure(c(19L, 57L, 31L, 59L, 33L, 34L, 4L, 7L, 40L,
12L, 50L, 56L, 3L, 37L, 6L, 39L, 46L, 17L, 43L, 55L, 30L, 2L,
36L, 38L, 11L, 21L, 49L, 24L, 27L, 10L, 45L, 14L, 1L, 18L, 47L,
54L, 29L, 32L, 8L, 42L, 9L, 16L, 44L, 48L, 23L, 51L, 52L, 26L,
35L, 5L, 15L, 20L, 22L, 25L, 53L, 28L, 58L, 41L, 13L),
.Label = c("1-8-2016", "11-5-2015", "11-7-2014", "12-10-2013", "12-2-2018", "12-8-2014",
"13-11-2013", "13-3-2017", "14-4-2017", "14-6-2016", "14-7-2015",
"15-12-2013", "15-2-2019", "16-7-2016", "17-4-2018", "17-6-2017",
"18-12-2014", "18-9-2016", "19-4-2013", "19-5-2018", "2-10-2015",
"20-6-2018", "20-8-2017", "21-12-2015", "22-7-2018", "23-10-2017",
"23-2-2016", "23-8-2018", "24-1-2017", "24-3-2015", "24-7-2013",
"25-2-2017", "25-8-2013", "26-9-2013", "27-1-2018", "27-5-2015",
"27-7-2014", "28-6-2015", "28-8-2014", "29-11-2013", "29-12-2018",
"29-3-2017", "3-1-2015", "3-7-2017", "30-6-2016", "31-10-2014",
"4-10-2016", "4-8-2017", "5-12-2015", "5-3-2014", "5-9-2017",
"7-10-2017", "7-8-2018", "8-1-2017", "8-3-2015", "8-5-2014",
"8-7-2013", "8-9-2018", "9-8-2013"), class = "factor"))

Related

Is there a way to reorder tip labels of a phylo object so that they are consistent with another phylo object?

I have two trees that I am trying to compare. One from mrbayes, another from Paup.
When I use read.nexus, the resulting phylo objects have differently ordered tip labels, despite the fact that both files have the same nexus taxa block.
I've reproduced these trees below:
library(ape)
#trees
t1 <- structure(list(edge = structure(c(29L, 30L, 30L, 30L, 30L, 31L,
31L, 32L, 32L, 33L, 34L, 35L, 35L, 35L, 34L, 36L, 37L, 38L, 38L,
38L, 38L, 37L, 39L, 40L, 40L, 39L, 39L, 39L, 39L, 36L, 36L, 36L,
36L, 33L, 31L, 31L, 31L, 31L, 29L, 30L, 1L, 2L, 3L, 31L, 4L,
32L, 5L, 33L, 34L, 35L, 6L, 7L, 8L, 36L, 37L, 38L, 9L, 10L, 11L,
12L, 39L, 40L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
23L, 24L, 25L, 26L, 27L, 28L), .Dim = c(39L, 2L)), Nnode = 12L,
tip.label = c("Metaspriggina", "Eptatretus", "Mordacia",
"Lasanius", "Phlebolepis", "Zenaspis", "Diademaspis", "Ukrainaspis",
"Tamiobatis", "Ischnacanthus", "Mesacanthus", "Tetanopsyrus",
"Mimipiscis", "Raynerius", "Diabolepis", "Guiyu", "Gavinia",
"Qingmenodus", "Kujdanowiaspis", "Cowralepis", "Jagorina",
"Macropetalichthys", "Polybranchiaspis", "Cyathaspis", "Irregulareaspis",
"Listraspis", "Unarkaspis", "Pikaia")), class = "phylo", order = "cladewise")
t2 <- structure(list(edge = structure(c(29L, 29L, 30L, 30L, 31L, 32L,
33L, 33L, 32L, 31L, 31L, 31L, 31L, 31L, 31L, 34L, 35L, 36L, 37L,
37L, 36L, 35L, 38L, 39L, 40L, 41L, 42L, 42L, 42L, 42L, 41L, 43L,
44L, 44L, 43L, 45L, 46L, 47L, 47L, 46L, 45L, 40L, 48L, 48L, 39L,
38L, 34L, 1L, 30L, 2L, 31L, 32L, 33L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 34L, 35L, 36L, 37L, 11L, 12L, 13L, 38L, 39L, 40L, 41L,
42L, 21L, 23L, 24L, 17L, 43L, 44L, 22L, 27L, 45L, 46L, 47L, 28L,
26L, 25L, 16L, 48L, 15L, 19L, 18L, 20L, 14L), .Dim = c(47L, 2L
)), Nnode = 20L, tip.label = c("Pikaia", "Metaspriggina", "Eptatretus",
"Mordacia", "Lasanius", "Phlebolepis", "Cyathaspis", "Irregulareaspis",
"Listraspis", "Unarkaspis", "Zenaspis", "Diademaspis", "Ukrainaspis",
"Polybranchiaspis", "Cowralepis", "Guiyu", "Ischnacanthus", "Jagorina",
"Kujdanowiaspis", "Macropetalichthys", "Mesacanthus", "Mimipiscis",
"Tamiobatis", "Tetanopsyrus", "Diabolepis", "Gavinia", "Raynerius",
"Qingmenodus")), class = "phylo", order = "cladewise")
#tip labels are the same
all.equal(sort(t1$tip.label), sort(t2$tip.label))
#[1] TRUE
#tip label order is different
all.equal(t1$tip.label, t2$tip.label)
#[1] "26 string mismatches"
Is there a way to reorder the tip labels of t1, so they are consistent with t2?

The solution depends very much on what you want to do with the trees. Most phylogenetic comparative methods use identical names in trees and correctly assign them. A simple match for the two trees can be found as:
match(match(t1$tip.label, t2$tip.label)
# [1] 2 3 4 5 6 11 12 13 23 17 21 24 22 27 25 16 26 28 19 15 18 20 14 7 8 9 10 1
To reorder the tree, you can use ladderize(t1), but that will only influence the plotting, not the tip label order. A nice, easy trick how to re-number the nodes and keep the tip labels in the ladderized display is to save the tree and load it again.
write.tree(ladderize(t1), file = "t1.tre")
t1 = read.tree("t1.tre")
However, your trees have different topologies, so matching the tip labels must be done with respect to the downstream analyses.
cophyloplot(ladderize(t1), ladderize(t2),
assoc = matrix(rep(t1$tip.label, 2), ncol = 2))

I think this is what you are after:
trees <- c(t1, t2)
trees <- .compressTipLabel(trees)
t2 <- trees[[2]]
all.equal(t1$tip.label, t2$tip.label)

Convert quarter character into date object in R

I have a dataset and a column in there with information on the "period" of the observations which is a character for quarters of year. The column looks like this:
> dput(df$Period)
structure(c(27L, 40L, 1L, 3L, 15L, 42L, 29L, 35L, 21L, 48L, 9L,
41L, 28L, 2L, 14L, 45L, 32L, 18L, 6L, 22L, 49L, 36L, 10L, 27L,
1L, 40L, 2L, 41L, 14L, 28L, 15L, 3L, 42L, 29L, 6L, 32L, 45L,
18L, 48L, 21L, 35L, 9L, 10L, 49L, 22L, 36L, 2L, 41L, 28L, 14L,
45L, 6L, 18L, 32L, 10L, 49L, 22L, 36L, 18L, 6L, 45L, 32L, 49L,
36L, 22L, 10L, 14L, 2L, 41L, 28L, 45L, 18L, 32L, 6L, 49L, 10L,
22L, 36L, 32L, 18L, 45L, 6L, 36L, 10L, 22L, 49L, 14L, 41L, 28L,
2L, 27L, 40L, 1L, 35L, 9L, 48L, 21L, 27L, 40L, 1L, 35L, 21L,
48L, 9L, 1L, 40L, 27L, 41L, 28L, 2L, 14L, 42L, 15L, 3L, 29L,
32L, 45L, 6L, 18L, 48L, 9L, 21L, 35L, 10L, 49L, 36L, 22L, 1L,
40L, 27L, 14L, 28L, 41L, 2L, 29L, 15L, 42L, 3L, 18L, 6L, 32L,
45L, 49L, 36L, 22L, 10L, 27L, 1L, 40L, 2L, 41L, 28L, 14L, 15L,
42L, 29L, 3L, 6L, 45L, 18L, 32L, 7L, 19L, 46L, 33L, 9L, 35L,
21L, 48L, 10L, 22L, 49L, 36L, 1L, 40L, 27L, 2L, 14L, 28L, 41L,
3L, 42L, 15L, 29L, 18L, 32L, 45L, 6L, 46L, 33L, 19L, 7L, 35L,
9L, 21L, 48L, 49L, 22L, 36L, 10L, 1L, 27L, 40L, 29L, 15L, 3L,
42L, 45L, 6L, 18L, 32L, 9L, 21L, 35L, 48L, 36L, 49L, 10L, 22L,
2L, 28L, 14L, 41L, 32L, 18L, 45L, 6L, 36L, 49L, 22L, 10L, 1L,
27L, 40L, 43L, 30L, 16L, 4L, 44L, 31L, 17L, 5L, 32L, 18L, 45L,
6L, 49L, 36L, 22L, 10L, 27L, 40L, 1L, 9L, 35L, 21L, 48L, 27L,
1L, 40L, 2L, 41L, 28L, 14L, 42L, 29L, 15L, 3L, 18L, 6L, 32L,
45L, 46L, 7L, 19L, 33L, 48L, 21L, 9L, 35L, 36L, 10L, 22L, 49L,
14L, 28L, 41L, 2L, 32L, 6L, 18L, 45L, 22L, 10L, 49L, 36L, 40L,
1L, 27L, 14L, 41L, 28L, 2L, 42L, 29L, 15L, 3L, 6L, 18L, 45L,
32L, 33L, 19L, 7L, 46L, 9L, 48L, 35L, 21L, 36L, 49L, 10L, 22L,
41L, 28L, 2L, 14L, 18L, 6L, 45L, 32L, 36L, 22L, 49L, 10L, 41L,
2L, 28L, 14L, 45L, 18L, 6L, 32L, 22L, 36L, 49L, 10L, 40L, 27L,
1L, 28L, 41L, 2L, 14L, 3L, 15L, 29L, 42L, 32L, 18L, 6L, 45L,
35L, 21L, 48L, 9L, 36L, 22L, 10L, 49L, 32L, 45L, 6L, 18L, 10L,
22L, 49L, 36L, 41L, 28L, 14L, 2L, 45L, 18L, 6L, 32L, 36L, 49L,
10L, 22L, 28L, 2L, 41L, 14L, 45L, 6L, 32L, 18L, 22L, 36L, 10L,
49L, 27L, 1L, 40L, 14L, 2L, 28L, 41L, 42L, 3L, 29L, 15L, 17L,
44L, 31L, 5L, 6L, 32L, 18L, 45L, 9L, 48L, 35L, 21L, 36L, 22L,
10L, 49L, 2L, 14L, 41L, 28L, 32L, 18L, 45L, 6L, 49L, 22L, 10L,
36L, 41L, 28L, 14L, 2L, 6L, 45L, 32L, 18L, 22L, 10L, 49L, 36L,
40L, 1L, 27L, 35L, 21L, 9L, 48L, 1L, 40L, 27L, 14L, 2L, 28L,
41L, 29L, 3L, 15L, 42L, 6L, 45L, 32L, 18L, 46L, 7L, 33L, 19L,
21L, 9L, 35L, 48L, 36L, 10L, 22L, 49L, 28L, 41L, 2L, 14L, 18L,
6L, 45L, 32L, 36L, 22L, 49L, 10L, 1L, 40L, 27L, 28L, 14L, 41L,
2L, 16L, 30L, 43L, 4L, 45L, 6L, 32L, 18L, 20L, 8L, 47L, 34L,
9L, 35L, 48L, 21L, 22L, 36L, 49L, 10L, 41L, 2L, 28L, 14L, 18L,
32L, 45L, 6L, 49L, 22L, 10L, 36L, 27L, 1L, 40L, 48L, 35L, 9L,
21L, 14L, 2L, 41L, 28L, 6L, 45L, 18L, 32L, 36L, 49L, 10L, 22L,
40L, 1L, 27L, 41L, 2L, 28L, 14L, 42L, 3L, 15L, 29L, 17L, 31L,
44L, 5L, 32L, 18L, 45L, 6L, 46L, 33L, 19L, 7L, 9L, 35L, 21L,
48L, 36L, 49L, 10L, 22L, 6L, 18L, 32L, 45L, 10L, 49L, 22L, 36L,
1L, 27L, 40L, 2L, 41L, 28L, 14L, 42L, 29L, 15L, 3L, 18L, 32L,
45L, 6L, 46L, 7L, 33L, 19L, 48L, 21L, 9L, 35L, 49L, 10L, 22L,
36L, 27L, 1L, 40L, 2L, 28L, 14L, 41L, 15L, 3L, 42L, 29L, 45L,
32L, 6L, 18L, 9L, 35L, 48L, 21L, 10L, 36L, 49L, 22L, 40L, 1L,
27L, 41L, 28L, 14L, 2L, 42L, 15L, 29L, 3L, 32L, 6L, 45L, 18L,
46L, 19L, 33L, 7L, 35L, 9L, 21L, 48L, 10L, 22L, 36L, 49L, 27L,
1L, 40L, 41L, 14L, 2L, 28L, 29L, 3L, 15L, 42L, 44L, 31L, 17L,
5L, 6L, 18L, 32L, 45L, 7L, 46L, 33L, 19L, 21L, 35L, 9L, 48L,
22L, 49L, 36L, 10L, 1L, 40L, 27L, 35L, 48L, 9L, 21L, 27L, 1L,
40L, 2L, 28L, 41L, 14L, 42L, 29L, 3L, 15L, 18L, 6L, 32L, 45L,
7L, 33L, 46L, 19L, 9L, 21L, 35L, 48L, 36L, 22L, 10L, 49L, 41L,
2L, 14L, 28L, 18L, 6L, 45L, 32L, 10L, 22L, 49L, 36L, 1L, 40L,
27L, 28L, 14L, 41L, 2L, 42L, 29L, 3L, 15L, 18L, 32L, 45L, 6L,
7L, 33L, 19L, 46L, 35L, 48L, 9L, 21L, 49L, 36L, 22L, 10L, 40L,
1L, 27L, 41L, 2L, 14L, 28L, 15L, 3L, 29L, 42L, 45L, 32L, 6L,
18L, 19L, 7L, 33L, 46L, 21L, 48L, 9L, 35L, 36L, 22L, 49L, 10L,
4L, 30L, 43L, 18L, 45L, 32L, 6L, 10L, 36L, 49L, 22L, 28L, 2L,
41L, 14L, 45L, 32L, 6L, 18L, 22L, 36L, 49L, 10L, 41L, 28L, 2L,
14L, 45L, 6L, 32L, 18L, 22L, 36L, 49L, 10L, 27L, 1L, 40L, 3L,
15L, 29L, 42L, 46L, 7L, 33L, 19L, 9L, 35L, 21L, 48L, 27L, 40L,
1L, 2L, 14L, 41L, 28L, 15L, 3L, 42L, 29L, 32L, 6L, 18L, 45L,
7L, 19L, 33L, 46L, 35L, 9L, 21L, 48L, 36L, 49L, 22L, 10L, 6L,
45L, 18L, 32L, 22L, 36L, 49L, 10L, 45L, 32L, 18L, 6L, 10L, 22L,
49L, 36L, 27L, 40L, 1L, 41L, 28L, 2L, 14L, 45L, 6L, 18L, 32L,
36L, 49L, 10L, 22L, 14L, 41L, 28L, 2L, 18L, 32L, 45L, 6L, 49L,
10L, 22L, 36L, 6L, 45L, 32L, 18L, 22L, 27L, 1L, 40L, 2L, 41L,
28L, 14L, 3L, 42L, 15L, 29L, 45L, 6L, 32L, 18L, 46L, 7L, 19L,
33L, 48L, 35L, 21L, 9L, 49L, 10L, 22L, 36L, 31L, 17L, 44L, 5L,
18L, 40L, 1L, 27L, 2L, 14L, 41L, 28L, 42L, 3L, 29L, 15L, 18L,
6L, 45L, 32L, 19L, 7L, 46L, 33L, 21L, 35L, 48L, 9L, 22L, 10L,
49L, 36L, 1L, 27L, 40L, 41L, 2L, 28L, 14L, 6L, 32L, 45L, 18L,
10L, 22L, 36L, 49L, 32L, 18L, 45L, 6L, 49L, 22L, 36L, 10L, 43L,
4L, 30L, 41L, 14L, 2L, 28L, 6L, 32L, 18L, 45L, 22L, 10L, 36L,
49L, 27L, 1L, 40L, 42L, 15L, 29L, 3L, 31L, 5L, 44L, 17L, 45L,
6L, 32L, 18L, 35L, 9L, 21L, 48L, 49L, 36L, 10L, 22L, 1L, 40L,
27L, 28L, 14L, 2L, 41L, 42L, 15L, 3L, 29L, 6L, 32L, 45L, 18L,
9L, 35L, 48L, 21L, 10L, 36L, 22L, 49L, 40L, 27L, 1L, 27L, 1L,
40L, 48L, 21L, 35L, 9L, 41L, 2L, 14L, 28L, 18L, 45L, 32L, 6L,
10L, 22L, 36L, 49L, 41L, 28L, 2L, 14L, 18L, 45L, 32L, 6L, 22L,
49L, 36L, 10L, 14L, 41L, 2L, 28L, 6L, 32L, 18L, 45L, 22L, 10L,
49L, 36L, 1L, 27L, 40L, 42L, 29L, 3L, 15L, 18L, 32L, 6L, 45L,
19L, 46L, 7L, 33L, 9L, 35L, 48L, 21L, 22L, 10L, 36L, 49L, 1L,
27L, 40L, 28L, 2L, 41L, 14L, 3L, 42L, 15L, 29L, 17L, 44L, 31L,
5L, 45L, 18L, 6L, 32L, 46L, 7L, 33L, 19L, 35L, 21L, 9L, 48L,
10L, 36L, 49L, 22L, 2L, 41L, 28L, 14L, 45L, 32L, 6L, 18L, 49L,
10L, 22L, 36L, 40L, 27L, 1L, 2L, 41L, 28L, 14L, 29L, 42L, 3L,
15L, 45L, 32L, 18L, 6L, 48L, 9L, 35L, 21L, 49L, 10L, 22L, 36L,
14L, 28L, 2L, 41L, 18L, 45L, 32L, 6L, 49L, 10L, 36L, 22L, 27L,
40L, 1L, 41L, 14L, 2L, 28L, 29L, 15L, 3L, 42L, 32L, 6L, 18L,
45L, 9L, 35L, 21L, 48L, 10L, 22L, 36L, 49L, 3L, 15L, 42L, 29L,
40L, 27L, 1L, 48L, 35L, 9L, 21L, 14L, 2L, 41L, 28L, 45L, 32L,
6L, 18L, 49L, 10L, 36L, 22L, 18L, 45L, 32L, 6L, 36L, 22L, 49L,
10L, 18L, 2L, 41L, 28L, 14L, 32L, 45L, 18L, 6L, 36L, 49L, 22L,
10L, 2L, 28L, 14L, 41L, 32L, 6L, 18L, 45L, 22L, 36L, 49L, 10L,
45L, 18L, 32L, 6L, 10L, 36L, 49L, 22L, 32L, 18L, 6L, 45L, 49L,
10L, 22L, 36L, 41L, 14L, 28L, 2L, 18L, 6L, 45L, 32L, 36L, 22L,
10L, 49L, 40L, 27L, 1L, 45L, 32L, 18L, 6L, 49L, 10L, 36L, 22L,
40L, 27L, 1L, 2L, 41L, 28L, 14L, 29L, 3L, 42L, 15L, 18L, 6L,
45L, 32L, 33L, 19L, 46L, 7L, 21L, 9L, 48L, 35L, 49L, 10L, 36L,
22L, 28L, 2L, 41L, 14L, 17L, 44L, 31L, 5L, 18L, 32L, 45L, 6L,
10L, 49L, 36L, 22L, 27L, 40L, 1L, 27L, 1L, 40L, 41L, 28L, 14L,
2L, 42L, 15L, 29L, 3L, 5L, 17L, 31L, 44L, 45L, 32L, 6L, 18L,
46L, 7L, 33L, 19L, 48L, 9L, 21L, 35L, 49L, 10L, 36L, 27L, 1L,
40L, 48L, 9L, 21L, 35L, 40L, 1L, 27L, 2L, 28L, 14L, 41L, 42L,
3L, 29L, 15L, 6L, 32L, 45L, 18L, 46L, 33L, 19L, 7L, 48L, 9L,
21L, 35L, 10L, 22L, 36L, 49L, 2L, 14L, 28L, 41L, 45L, 6L, 32L,
18L, 10L, 49L, 22L, 36L, 14L, 41L, 2L, 28L, 18L, 45L, 6L, 32L,
10L, 49L, 22L, 36L, 40L, 1L, 27L, 42L, 15L, 3L, 29L, 45L, 18L,
6L, 32L, 7L, 33L, 19L, 46L, 21L, 9L, 48L, 35L, 36L, 10L, 22L,
49L, 40L, 1L, 27L, 3L, 29L, 15L, 42L, 46L, 19L, 33L, 7L, 48L,
21L, 9L, 35L, 41L, 14L, 28L, 2L, 32L, 18L, 6L, 45L, 49L, 36L,
22L, 10L, 28L, 2L, 41L, 14L, 6L, 32L, 45L, 18L, 36L, 10L, 22L,
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29L, 15L, 3L, 42L, 18L, 32L, 6L, 45L, 7L, 33L, 19L, 46L, 21L,
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32L, 45L, 6L, 19L, 7L, 33L, 46L, 9L, 35L, 21L, 48L, 49L, 22L,
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22L, 49L, 36L, 40L, 27L, 1L, 2L, 28L, 41L, 14L, 15L, 29L, 42L,
3L, 6L, 32L, 45L, 18L, 21L, 35L, 9L, 48L, 22L, 49L, 36L, 10L,
30L, 43L, 16L, 4L, 30L, 43L, 4L, 16L, 1L, 40L, 27L, 48L, 9L,
35L, 21L, 45L, 32L, 6L, 18L, 10L, 22L, 36L, 49L, 1L, 27L, 40L,
41L, 14L, 2L, 28L, 42L, 15L, 29L, 3L, 45L, 6L, 32L, 18L, 21L,
9L, 48L, 35L, 36L, 10L, 49L, 22L, 27L, 1L, 40L, 28L, 2L, 14L,
41L, 15L, 29L, 3L, 42L, 31L, 44L, 17L, 5L, 6L, 45L, 32L, 18L,
48L, 35L, 9L, 21L, 22L, 10L, 49L, 36L, 40L, 1L, 27L, 9L, 48L,
35L, 21L, 41L, 28L, 2L, 14L, 18L, 6L, 45L, 32L, 49L, 10L, 36L,
22L, 27L, 40L, 1L, 28L, 41L, 14L, 2L, 29L, 3L, 42L, 15L, 45L,
6L, 18L, 32L, 19L, 46L, 7L, 33L, 9L, 21L, 48L, 35L, 36L, 10L,
22L, 49L, 28L, 41L, 14L, 2L, 18L, 32L, 45L, 6L, 22L, 36L, 10L,
49L, 32L, 45L, 18L, 6L, 49L, 10L, 22L, 36L, 27L, 1L, 40L, 35L,
48L, 21L, 9L, 41L, 14L, 2L, 28L, 18L, 45L, 6L, 32L, 49L, 36L,
22L, 10L, 1L, 27L, 40L, 29L, 3L, 15L, 42L, 18L, 32L, 6L, 45L,
46L, 33L, 7L, 19L, 9L, 48L, 35L, 21L, 22L, 10L, 36L, 49L, 27L,
1L, 40L, 2L, 41L, 14L, 28L, 42L, 15L, 3L, 29L, 45L, 18L, 32L,
6L, 19L, 7L, 46L, 33L, 21L, 48L, 9L, 35L, 22L, 10L, 36L, 49L,
2L, 41L, 14L, 28L, 18L, 45L, 32L, 6L, 36L, 49L, 22L, 10L, 27L,
40L, 1L, 40L, 27L, 1L, 14L, 28L, 41L, 2L, 3L, 15L, 42L, 29L,
32L, 6L, 18L, 45L, 46L, 33L, 19L, 7L, 21L, 35L, 9L, 48L, 10L,
36L, 49L, 22L, 41L, 28L, 2L, 14L, 45L, 18L, 6L, 32L, 10L, 36L,
49L, 22L, 41L, 14L, 28L, 2L, 6L, 18L, 32L, 45L, 10L, 22L, 36L,
49L, 1L, 40L, 27L, 14L, 28L, 41L, 2L, 15L, 42L, 3L, 29L, 45L,
32L, 6L, 18L, 7L, 19L, 46L, 33L, 48L, 9L, 21L, 35L, 49L, 22L,
36L, 10L, 45L, 18L, 32L, 6L, 10L, 36L, 22L, 49L, 14L, 28L, 41L,
2L, 18L, 32L, 6L, 45L, 22L, 36L, 10L, 49L, 18L, 32L, 6L, 45L,
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40L, 1L, 9L, 21L, 48L, 35L, 18L, 32L, 45L, 6L, 22L, 10L, 49L,
36L, 28L, 2L, 14L, 41L, 6L, 32L, 45L, 18L, 10L, 49L, 22L, 36L,
2L, 14L, 41L, 28L, 18L, 32L, 6L, 45L, 36L, 10L, 49L, 22L, 2L,
28L, 14L, 41L, 32L, 6L, 18L, 45L, 10L, 49L, 22L, 36L, 40L, 27L,
1L, 14L, 41L, 2L, 28L, 29L, 3L, 15L, 42L, 6L, 45L, 32L, 18L,
46L, 7L, 33L, 19L, 35L, 21L, 9L, 48L, 36L, 10L, 22L, 49L, 40L,
1L, 27L, 41L, 14L, 28L, 2L, 3L, 29L, 42L, 15L, 18L, 32L, 6L,
45L, 7L, 33L, 19L, 46L, 9L, 21L, 48L, 35L, 22L, 10L, 49L, 36L,
2L, 14L, 41L, 28L, 45L, 6L, 18L, 32L, 22L, 49L, 36L, 10L, 45L,
18L, 32L, 6L, 49L, 10L, 36L, 22L, 1L, 27L, 40L, 14L, 41L, 28L,
2L, 15L, 3L, 29L, 42L, 32L, 18L, 45L, 6L, 7L, 46L, 33L, 19L,
48L, 9L, 21L, 35L, 49L, 36L, 10L, 22L, 40L, 1L, 27L, 9L, 35L,
48L, 21L, 45L, 32L, 18L, 6L, 22L, 10L, 36L, 49L, 18L, 2L, 14L,
28L, 41L, 6L, 18L, 32L, 45L, 22L, 49L, 36L, 10L, 27L, 1L, 40L,
41L, 28L, 2L, 14L, 3L, 15L, 42L, 29L, 6L, 32L, 18L, 45L, 7L,
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27L, 14L, 2L, 41L, 28L, 3L, 29L, 15L, 42L, 18L, 6L, 32L, 45L,
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15L, 3L, 32L, 18L, 45L, 6L, 21L, 35L, 9L, 48L, 36L, 10L, 49L,
22L, 28L, 2L, 41L, 14L, 18L, 32L, 6L, 45L, 49L, 10L, 36L, 22L,
6L, 45L, 18L, 32L, 22L, 49L, 36L, 10L, 45L, 6L, 18L, 32L, 22L,
49L, 36L, 10L, 31L, 5L, 17L, 44L, 1L, 27L, 40L, 28L, 2L, 41L,
14L, 42L, 29L, 15L, 3L, 45L, 18L, 32L, 6L, 46L, 7L, 19L, 33L,
48L, 21L, 35L, 9L, 36L, 10L, 49L, 22L, 14L, 28L, 41L, 2L, 32L,
6L, 18L, 45L, 36L, 10L, 49L, 22L, 1L, 27L, 40L, 42L, 3L, 15L,
29L, 19L, 7L, 46L, 33L, 48L, 21L, 9L, 35L, 6L, 18L, 32L, 45L,
22L, 49L, 36L, 10L, 1L, 27L, 40L, 28L, 14L, 41L, 2L, 42L, 15L,
29L, 3L, 45L, 18L, 32L, 6L, 21L, 9L, 48L, 35L, 10L, 22L, 36L,
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35L, 9L, 21L, 27L, 1L, 40L, 14L, 2L, 41L, 28L, 15L, 29L, 3L,
42L, 18L, 6L, 32L, 45L, 46L, 7L, 19L, 33L, 9L, 35L, 21L, 48L,
22L, 10L, 36L, 49L, 27L, 1L, 40L, 27L, 40L, 1L, 14L, 28L, 41L,
2L, 3L, 29L, 42L, 15L, 32L, 6L, 18L, 45L, 33L, 46L, 19L, 7L,
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14L, 28L, 3L, 15L, 29L, 42L, 18L, 45L, 32L, 6L, 33L, 46L, 7L,
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18L, 6L, 46L, 33L, 19L, 7L, 21L, 9L, 35L, 48L, 22L, 10L, 36L,
49L, 40L, 27L, 1L, 42L, 15L, 29L, 3L, 18L, 40L, 1L, 27L, 2L,
28L, 14L, 41L, 15L, 3L, 29L, 42L, 32L, 18L, 6L, 45L, 7L, 46L,
19L, 33L, 48L, 9L, 35L, 21L, 22L, 10L, 36L, 49L, 1L, 40L, 27L,
44L, 17L, 5L, 31L, 21L, 9L, 48L, 35L, 41L, 14L, 28L, 2L, 32L,
6L, 18L, 45L, 49L, 22L, 10L, 36L, 40L, 1L, 27L, 2L, 28L, 41L,
14L, 3L, 15L, 29L, 42L, 32L, 18L, 6L, 45L, 46L, 19L, 7L, 33L,
21L, 48L, 9L, 35L, 36L, 22L, 49L, 10L, 1L, 27L, 40L, 41L, 2L,
28L, 14L, 29L, 42L, 3L, 15L, 32L, 45L, 6L, 18L, 33L, 46L, 19L,
7L, 35L, 9L, 48L, 21L, 36L, 10L, 49L, 22L, 14L, 2L, 41L, 28L,
45L, 6L, 18L, 32L, 49L, 10L, 22L, 36L, 1L, 27L, 40L, 48L, 35L,
9L, 21L, 6L, 45L, 32L, 18L, 36L, 10L, 49L, 22L, 40L, 27L, 1L,
41L, 2L, 14L, 28L, 29L, 42L, 3L, 15L, 32L, 6L, 45L, 18L, 19L,
46L, 33L, 7L, 48L, 9L, 21L, 35L, 22L, 10L, 36L, 49L, 40L, 27L,
1L, 41L, 14L, 2L, 28L, 29L, 42L, 15L, 3L, 5L, 31L, 44L, 17L,
45L, 32L, 18L, 6L, 33L, 46L, 19L, 7L, 48L, 21L, 35L, 9L, 49L,
10L, 36L, 22L, 27L, 1L, 40L, 28L, 41L, 2L, 14L, 29L, 15L, 3L,
42L, 6L, 45L, 32L, 18L, 46L, 33L, 19L, 7L, 21L, 35L, 48L, 9L,
22L, 36L, 10L, 49L, 18L, 32L, 6L, 45L, 49L, 10L, 22L, 36L, 27L,
40L, 1L, 41L, 28L, 14L, 2L, 42L, 3L, 15L, 29L, 6L, 18L, 32L,
45L, 9L, 48L, 21L, 35L, 10L, 36L, 22L, 49L, 1L, 40L, 27L, 41L,
28L, 14L, 2L, 29L, 15L, 3L, 42L, 18L, 32L, 45L, 6L, 9L, 21L,
48L, 35L, 10L, 22L, 49L, 36L, 1L, 27L, 40L, 2L, 14L, 41L, 28L,
42L, 29L, 15L, 3L, 18L, 32L, 6L, 45L, 46L, 7L, 33L, 19L, 35L,
21L, 9L, 48L, 10L, 49L, 22L, 36L, 6L, 32L, 18L, 45L, 10L, 22L,
36L, 49L, 40L, 1L, 27L, 41L, 14L, 28L, 2L, 29L, 3L, 15L, 42L,
18L, 32L, 6L, 45L, 46L, 7L, 19L, 33L, 48L, 9L, 21L, 35L, 36L,
49L, 22L, 10L, 6L, 32L, 18L, 45L, 49L, 22L, 10L, 36L, 27L, 1L,
40L, 2L, 14L, 41L, 28L, 15L, 29L, 3L, 42L, 18L, 45L, 6L, 32L,
9L, 21L, 35L, 48L, 10L, 36L, 49L, 22L, 40L, 1L, 27L, 14L, 41L,
28L, 2L, 3L, 15L, 42L, 29L, 18L, 32L, 6L, 45L, 48L, 35L, 9L,
21L, 10L, 49L, 36L, 22L, 45L, 32L, 6L, 18L, 36L, 22L, 49L, 10L,
18L, 6L, 45L, 32L, 10L, 36L, 49L, 22L, 1L, 40L, 27L, 2L, 14L,
28L, 41L, 42L, 3L, 15L, 29L, 32L, 6L, 45L, 18L, 33L, 46L, 7L,
19L, 48L, 9L, 21L, 35L, 22L, 49L, 36L, 10L, 32L, 45L, 6L, 18L,
22L, 36L, 10L, 49L, 41L, 28L, 14L, 2L, 6L, 18L, 32L, 45L, 49L,
22L, 10L, 36L, 1L, 27L, 40L, 2L, 14L, 41L, 28L, 15L, 29L, 42L,
3L, 6L, 45L, 32L, 18L, 19L, 7L, 46L, 33L, 21L, 9L, 35L, 48L,
36L, 49L, 10L, 22L, 1L, 27L, 40L, 30L, 43L, 4L, 40L, 1L, 27L,
41L, 2L, 28L, 14L, 3L, 42L, 29L, 15L, 44L, 31L, 17L, 5L, 6L,
32L, 18L, 45L, 33L, 46L, 19L, 7L, 21L, 9L, 35L, 48L, 10L, 22L,
49L, 36L, 27L, 1L, 40L, 14L, 2L, 28L, 41L, 29L, 42L, 3L, 15L,
45L, 18L, 6L, 32L, 33L, 19L, 46L, 7L, 21L, 35L, 9L, 48L, 10L,
36L, 49L, 22L, 40L, 1L, 27L, 18L, 45L, 32L, 6L, 22L, 36L, 10L,
49L, 40L, 1L, 27L, 2L, 14L, 28L, 41L, 3L, 15L, 29L, 42L, 6L,
32L, 45L, 18L, 46L, 33L, 7L, 19L, 48L, 35L, 21L, 9L, 22L, 36L,
10L, 49L, 28L, 14L, 2L, 41L, 32L, 18L, 6L, 45L, 49L, 10L, 22L,
36L, 2L, 28L, 41L, 14L, 32L, 6L, 45L, 18L, 10L, 49L, 36L, 22L,
45L, 32L, 18L, 6L, 10L, 22L, 49L, 36L, 6L, 32L, 18L, 45L, 36L,
10L, 22L, 49L, 18L, 6L, 45L, 32L, 10L, 36L, 22L, 49L, 40L, 1L,
27L, 28L, 2L, 14L, 41L, 3L, 29L, 15L, 42L, 45L, 32L, 6L, 18L,
35L, 21L, 48L, 9L, 22L, 49L, 10L, 36L, 14L, 41L, 2L, 28L, 18L,
45L, 6L, 32L, 10L, 49L, 36L, 22L, 18L, 32L, 45L, 6L, 22L, 36L,
49L, 10L, 14L, 41L, 28L, 2L, 32L, 6L, 45L, 18L, 49L, 36L, 10L,
22L, 41L, 2L, 14L, 28L, 6L, 45L, 18L, 32L, 10L, 22L, 49L, 36L,
6L, 32L, 45L, 18L, 49L, 22L, 36L, 10L, 41L, 28L, 14L, 2L, 6L,
45L, 18L, 32L, 22L, 10L, 49L, 36L, 1L, 27L, 40L, 28L, 2L, 14L,
41L, 42L, 29L, 15L, 3L, 45L, 6L, 18L, 32L, 9L, 21L, 35L, 48L,
10L, 36L, 49L, 22L, 27L, 1L, 40L, 14L, 28L, 41L, 2L, 15L, 29L,
42L, 3L, 18L, 45L, 32L, 6L, 46L, 19L, 7L, 33L, 9L, 35L, 21L,
48L, 49L, 36L, 22L, 10L, 1L, 40L, 27L, 28L, 14L, 2L, 41L, 15L,
42L, 29L, 3L, 32L, 6L, 18L, 45L, 7L, 33L, 19L, 46L, 48L, 35L,
21L, 9L, 10L, 36L, 49L, 22L, 27L, 1L, 40L, 48L, 9L, 35L, 21L,
14L, 41L, 2L, 28L, 45L, 18L, 6L, 32L, 49L, 10L, 36L, 22L, 1L,
40L, 27L, 2L, 28L, 14L, 41L, 15L, 3L, 42L, 29L, 18L, 6L, 45L,
32L, 33L, 19L, 7L, 46L, 9L, 48L, 21L, 35L, 10L, 49L, 22L, 36L,
2L, 41L, 14L, 28L, 45L, 32L, 18L, 6L, 49L, 10L, 22L, 36L, 1L,
40L, 27L, 41L, 14L, 28L, 2L, 15L, 29L, 42L, 3L, 17L, 31L, 44L,
5L, 18L, 32L, 45L, 6L, 33L, 7L, 46L, 19L, 9L, 35L, 48L, 21L,
36L, 10L, 22L, 49L, 2L, 14L, 41L, 28L, 45L, 6L, 32L, 18L, 36L,
22L, 10L, 49L, 41L, 14L, 28L, 2L, 18L, 45L, 32L, 6L, 49L, 22L,
36L, 10L, 40L, 27L, 1L, 41L, 2L, 14L, 28L, 42L, 29L, 3L, 15L,
32L, 45L, 18L, 6L, 46L, 19L, 33L, 7L, 9L, 48L, 21L, 35L, 10L,
49L, 36L, 22L, 1L, 40L, 27L, 41L, 28L, 14L, 2L, 3L, 29L, 15L,
42L, 6L, 18L, 32L, 45L, 46L, 7L, 33L, 19L, 9L, 48L, 21L, 35L,
36L, 10L, 49L, 22L, 14L, 28L, 2L, 41L, 45L, 18L, 32L, 6L, 10L,
22L, 36L, 49L, 1L, 27L, 40L, 14L, 2L, 41L, 28L, 29L, 15L, 3L,
42L, 18L, 45L, 32L, 6L, 22L, 10L, 49L, 36L, 27L, 40L, 1L, 14L,
28L, 41L, 2L, 29L, 15L, 42L, 3L, 32L, 45L, 6L, 18L, 7L, 46L,
19L, 33L, 21L, 9L, 48L, 35L, 49L, 36L, 22L, 10L, 27L, 1L, 40L,
28L, 41L, 14L, 2L, 15L, 3L, 29L, 42L, 18L, 32L, 6L, 45L, 46L,
19L, 33L, 7L, 21L, 48L, 35L, 9L, 49L, 36L, 22L, 10L, 28L, 2L,
14L, 41L, 32L, 18L, 45L, 6L, 22L, 10L, 49L, 36L, 40L, 1L, 27L,
28L, 14L, 41L, 2L, 15L, 42L, 3L, 29L, 6L, 45L, 18L, 32L, 48L,
21L, 9L, 35L, 22L, 36L, 49L, 10L, 14L, 41L, 28L, 2L, 45L, 6L,
18L, 32L, 36L, 22L, 10L, 49L, 40L, 27L, 1L, 5L, 44L, 17L, 31L,
35L, 9L, 21L, 48L, 27L, 1L, 40L, 14L, 2L, 28L, 41L, 15L, 29L,
3L, 42L, 45L, 6L, 32L, 18L, 36L, 10L, 22L, 49L, 28L, 2L, 14L,
41L, 15L, 29L, 42L, 3L, 18L, 45L, 32L, 6L, 46L, 7L, 33L, 19L,
9L, 48L, 21L, 35L, 49L, 36L, 10L, 22L, 1L, 40L, 27L, 14L, 28L,
2L, 41L, 42L, 3L, 15L, 29L, 18L, 32L, 45L, 6L, 9L, 21L, 48L,
35L, 36L, 49L, 22L, 10L, 1L, 40L, 27L, 41L, 2L, 28L, 14L, 3L,
42L, 15L, 29L, 45L, 6L, 18L, 32L, 48L, 9L, 21L, 35L, 36L, 22L,
10L, 49L, 40L, 1L, 27L, 14L, 41L, 2L, 28L, 15L, 42L, 3L, 29L,
6L, 32L, 45L, 18L, 33L, 19L, 7L, 46L, 35L, 48L, 9L, 21L, 36L,
22L, 49L, 10L, 6L, 18L, 45L, 32L, 22L, 10L, 49L, 36L, 6L, 18L,
32L, 45L, 36L, 10L, 22L, 49L, 2L, 14L, 28L, 41L, 45L, 18L, 32L,
6L, 22L, 49L, 10L, 36L, 2L, 28L, 14L, 41L, 32L, 6L, 18L, 45L,
10L, 36L, 49L, 22L, 14L, 28L, 2L, 41L, 18L, 32L, 6L, 45L, 22L,
49L, 36L, 10L, 28L, 41L, 14L, 2L, 18L, 6L, 45L, 32L, 10L, 22L,
49L, 36L, 41L, 14L, 2L, 28L, 18L, 32L, 45L, 6L, 36L, 49L, 10L,
22L, 1L, 27L, 40L, 41L, 28L, 14L, 2L, 3L, 29L, 42L, 15L, 32L,
6L, 45L, 18L, 46L, 7L, 33L, 19L, 21L, 48L, 35L, 9L, 10L, 22L,
49L, 36L, 1L, 27L, 40L, 28L, 41L, 14L, 2L, 15L, 29L, 3L, 42L,
6L, 18L, 45L, 32L, 33L, 7L, 19L, 46L, 9L, 35L, 21L, 48L, 10L,
22L, 36L, 49L, 41L, 2L, 14L, 28L, 32L, 6L, 45L, 18L, 22L, 49L,
10L, 36L, 2L, 14L, 28L, 41L, 32L, 18L, 6L, 45L, 22L, 49L, 36L,
10L, 18L, 6L, 45L, 32L, 22L, 10L, 36L, 49L, 40L, 1L, 27L, 48L,
21L, 9L, 35L, 27L, 40L, 1L, 28L, 14L, 2L, 41L, 42L, 15L, 29L,
3L, 32L, 45L, 18L, 6L, 21L, 35L, 9L, 48L, 36L, 10L, 22L, 49L,
40L, 1L, 27L, 41L, 28L, 14L, 2L, 42L, 29L, 3L, 15L, 45L, 6L,
32L, 18L, 46L, 7L, 19L, 33L, 48L, 35L, 21L, 9L, 49L, 22L, 10L,
36L, 41L, 2L, 14L, 28L, 6L, 18L, 45L, 32L, 10L, 49L, 22L, 36L,
2L, 28L, 41L, 14L, 32L, 6L, 45L, 18L, 10L, 22L, 49L, 36L, 40L,
1L, 27L, 2L, 41L, 14L, 28L, 3L, 29L, 42L, 15L, 45L, 32L, 18L,
6L, 9L, 35L, 21L, 48L, 22L, 10L, 36L, 49L, 1L, 40L, 27L, 28L,
41L, 14L, 2L, 3L, 29L, 15L, 42L, 45L, 32L, 6L, 18L, 35L, 21L,
9L, 48L, 10L, 49L, 22L, 36L, 27L, 1L, 40L, 35L, 9L, 48L, 21L,
27L, 1L, 40L, 9L, 48L, 21L, 35L, 40L, 1L, 27L, 2L, 14L, 28L,
41L, 3L, 42L, 29L, 15L, 18L, 32L, 6L, 45L, 21L, 35L, 9L, 48L,
36L, 22L, 10L, 49L, 14L, 28L, 41L, 2L, 5L, 31L, 17L, 44L, 32L,
45L, 6L, 18L, 22L, 49L, 36L, 10L, 1L, 27L, 40L, 2L, 14L, 28L,
41L, 42L, 29L, 3L, 15L, 45L, 32L, 18L, 6L, 33L, 19L, 46L, 7L,
21L, 35L, 9L, 48L, 10L, 22L, 36L, 49L, 40L, 1L, 27L, 28L, 41L,
2L, 14L, 29L, 3L, 42L, 15L, 32L, 18L, 6L, 45L, 22L, 10L, 49L,
36L, 41L, 28L, 14L, 2L, 45L, 6L, 32L, 18L, 36L, 49L, 10L, 22L,
18L, 45L, 6L, 32L, 36L, 22L, 49L, 10L, 45L, 32L, 6L, 18L, 36L,
10L, 49L, 22L, 1L, 40L, 27L, 14L, 28L, 41L, 2L, 15L, 42L, 3L,
29L, 18L, 32L, 6L, 45L, 7L, 46L, 33L, 19L, 9L, 21L, 48L, 35L,
49L, 22L, 36L, 10L, 41L, 14L, 28L, 2L, 32L, 45L, 6L, 18L, 49L,
36L, 22L, 10L, 6L, 32L, 45L, 18L, 10L, 22L, 49L, 36L, 18L, 27L,
1L, 40L, 41L, 28L, 2L, 14L, 42L, 29L, 3L, 15L, 45L, 6L, 18L,
32L, 33L, 46L, 7L, 19L, 48L, 9L, 21L, 35L, 10L, 22L, 36L, 49L,
40L, 27L, 1L, 15L, 3L, 42L, 29L, 6L, 32L, 18L, 45L, 10L, 36L,
22L, 49L, 1L, 27L, 40L, 28L, 41L, 2L, 14L, 3L, 15L, 29L, 42L,
6L, 18L, 32L, 45L, 35L, 9L, 48L, 21L, 10L, 22L, 36L, 49L, 32L,
45L, 6L, 18L, 36L, 10L, 22L, 49L, 27L, 40L, 1L, 9L, 21L, 35L,
48L, 27L, 1L, 40L, 29L, 42L, 3L, 15L, 18L, 27L, 1L, 40L, 14L,
2L, 28L, 41L, 42L, 15L, 3L, 29L, 6L, 18L, 32L, 45L, 48L, 35L,
9L, 21L, 49L, 22L, 36L, 10L, 43L, 4L, 30L, 40L, 27L, 1L, 2L,
28L, 41L, 14L, 29L, 42L, 3L, 15L, 45L, 32L, 18L, 6L, 33L, 7L,
46L, 19L, 35L, 48L, 9L, 21L, 36L, 22L, 49L, 10L, 14L, 28L, 41L,
2L, 18L, 45L, 32L, 6L, 49L, 22L, 10L, 36L, 40L, 27L, 1L, 41L,
2L, 14L, 28L, 29L, 15L, 42L, 3L, 6L, 45L, 32L, 18L, 48L, 9L,
21L, 35L, 36L, 49L, 22L, 10L, 27L, 40L, 1L, 14L, 28L, 41L, 2L,
29L, 15L, 3L, 42L, 32L, 6L, 45L, 18L, 21L, 9L, 48L, 35L, 10L,
36L, 49L, 22L, 1L, 27L, 40L, 28L, 14L, 2L, 41L, 42L, 3L, 29L,
15L, 45L, 18L, 32L, 6L, 33L, 7L, 46L, 19L, 35L, 9L, 48L, 21L,
36L, 10L, 22L, 49L, 40L, 1L, 27L, 14L, 41L, 28L, 2L, 15L, 29L,
3L, 42L, 32L, 45L, 18L, 6L, 9L, 48L, 35L, 21L, 10L, 36L, 49L,
22L, 40L, 1L, 27L, 28L, 2L, 14L, 41L, 42L, 15L, 3L, 29L, 45L,
6L, 18L, 32L, 33L, 19L, 46L, 7L, 35L, 21L, 9L, 48L, 49L, 22L,
36L, 10L, 40L, 27L, 1L, 28L, 41L, 2L, 14L, 29L, 42L, 3L, 15L,
6L, 45L, 32L, 18L, 33L, 19L, 7L, 46L, 48L, 9L, 21L, 35L, 36L,
49L, 10L, 22L, 14L, 41L, 28L, 2L, 45L, 18L, 32L, 6L, 10L, 22L,
36L, 49L, 32L, 45L, 6L, 18L, 10L, 49L, 36L, 22L, 28L, 2L, 14L,
41L, 6L, 32L, 45L, 18L, 10L, 36L, 22L, 49L, 27L, 1L, 40L, 41L,
2L, 28L, 14L, 15L, 42L, 3L, 29L, 32L, 6L, 45L, 18L, 19L, 7L,
33L, 46L, 35L, 21L, 9L, 48L, 36L, 49L, 22L, 10L, 28L, 14L, 2L,
41L, 32L, 6L, 18L, 45L, 36L, 49L, 10L, 22L), .Label = c("Apr 06 - Jun 06",
"Apr 07 - Jun 07", "Apr 08 - Jun 08", "Apr 09 - Jun 09", "Apr 10 - Jun 10",
"Apr 11 - Jun 11", "Apr 12 - Jun 12", "Apr 13 - Jun 13", "Apr 14 - Jun 14",
"Apr 15 - Jun 15", "Apr 16 - Jun 16", "Apr 17 - Jun 17", "Apr 18 - Jun 18",
"Jan 07 - Mar 07", "Jan 08 - Mar 08", "Jan 09 - Mar 09", "Jan 10 - Mar 10",
"Jan 11 - Mar 11", "Jan 12 - Mar 12", "Jan 13 - Mar 13", "Jan 14 - Mar 14",
"Jan 15 - Mar 15", "Jan 16 - Mar 16", "Jan 17 - Mar 17", "Jan 18 - Mar 18",
"Jan 19 - Mar 19", "Jul 06 - Sep 06", "Jul 07 - Sep 07", "Jul 08 - Sep 08",
"Jul 09 - Sep 09", "Jul 10 - Sep 10", "Jul 11 - Sep 11", "Jul 12 - Sep 12",
"Jul 13 - Sep 13", "Jul 14 - Sep 14", "Jul 15 - Sep 15", "Jul 16 - Sep 16",
"Jul 17 - Sep 17", "Jul 18 - Sep 18", "Oct 06 - Dec 06", "Oct 07 - Dec 07",
"Oct 08 - Dec 08", "Oct 09 - Dec 09", "Oct 10 - Dec 10", "Oct 11 - Dec 11",
"Oct 12 - Dec 12", "Oct 13 - Dec 13", "Oct 14 - Dec 14", "Oct 15 - Dec 15",
"Oct 16 - Dec 16", "Oct 17 - Dec 17", "Oct 18 - Dec 18"), class = "factor")
Is there a way of turning this into a data object using lubridate? I tried different things like this:
a <- as.numeric(df$Period)
library(lubridate)
a <- quarter(a, with_year = TRUE)
And many similar iterations of this, but I cannot really get it tight.
Thanks!

Assuming the input is as shown below we can split it into from and to.
Then convert to yearmon class which represents year/month as year + fraction where fraction = 0 for Jan, 1/12 for Feb, ..., 11/12 for Dec (so for example adding 1/12 to such an object increments it by one month) and displays as shown.
We also convert to yearqtr class which represents quarters as year + fraction where the fraction is 0, 1/4, 1/2 and 3/4 for successive quarters so, for example, adding 1/4 to such an object increments it by one quarter.
These objects display as shown below.
Note that the question states that Period is character but the dput output shows it has factor class, not character.
library(dplyr)
library(tidyr)
library(zoo)
df <- data.frame(Period = c("Jul 06 - Sep 06", "Oct 06 - Dec 06",
"Apr 06 - Jun 06", "Apr 08 - Jun 08"))
df %>%
separate(Period, c("from", "to"), sep = " - ") %>%
mutate(from = as.yearmon(from, "%b %y"),
to = as.yearmon(to, "%b %y"),
year_qtr = as.yearqtr(to),
year = as.integer(to),
qtr = cycle(year_qtr),
from_date = as.Date(from),
to_date = as.Date(to, frac = 1))
giving:
from to year_qtr year qtr from_date to_date
1 Jul 2006 Sep 2006 2006 Q3 2006 3 2006-07-01 2006-09-30
2 Oct 2006 Dec 2006 2006 Q4 2006 4 2006-10-01 2006-12-31
3 Apr 2006 Jun 2006 2006 Q2 2006 2 2006-04-01 2006-06-30
4 Apr 2008 Jun 2008 2008 Q2 2008 2 2008-04-01 2008-06-30

Conditional replace values in a column

I am trying to replace some key numbers with their respective people names.
Despite my two attempts, I cannot change the numbers (characters) into names, any suggestions?
Here is what I tried so far:
setDT(df)[person == "447745939698" , person := "John"]
and
df <- df %>% mutate(person=ifelse(person=="447745939698","John",person))
Dataset:
structure(list(person = c("Pavel", "Anna", "Julian", "Bernardo",
"Bryony", "KJ", "Filippo", "Duncan", "‪447761633878‬", "Josh",
"Alex", "Berna", "Melina", "Martha", "‪447999592975‬", "‪48512044757‬",
"Don", "‪447404192025‬", "Sofia", "Jonas", "Chantal", "‪447441458269‬",
"‪447745939698‬", "Sungjoo", "‪447850449670‬", "Blanche",
"Vedo", "‪966554857666‬", "‪447787327724‬", "‪447407102816‬",
"‪447972826119‬", "‪447516428644‬", "‪447973747720‬",
"‪447383865362‬", "‪447478422564‬", "‪447543834973‬",
"Cris", "‪31642688469‬", "‪447921148041‬", "‪447865832098‬",
"Steve", "‪447492829467‬", "Andrea", "‪447878829919‬",
"‪447880747575‬", "‪34635960936‬", "‪447464871555‬",
"‪31640838890‬", "‪46707218515‬", "‪4528822826‬",
"‪393480848355‬", "‪447568552037‬", "‪4580211317‬",
"‪551198299‑2336‬", "‪447935988040‬", "‪447340827646‬"
)), class = c("data.table", "data.frame"), row.names = c(NA,
-56L), index = structure(integer(0), "`__person`" = c(11L,
43L, 2L, 12L, 4L, 26L, 5L, 21L, 37L, 17L, 8L, 7L, 20L, 10L, 3L,
6L, 14L, 13L, 1L, 19L, 41L, 24L, 27L, 48L, 38L, 46L, 51L, 56L,
40L, 34L, 30L, 18L, 47L, 35L, 22L, 42L, 32L, 36L, 52L, 23L, 9L,
29L, 44L, 45L, 25L, 39L, 55L, 31L, 33L, 15L, 50L, 53L, 49L, 16L,
54L, 28L)))

R check if there is a letter and then multiply the value by -1

I have a dataframe (databycitydiff2) column as follows:
x
10N
20N
35S
25S
What I want to do is check if the letter at the end is N or S. If it is S, I want to remove the S and multiply the number by -1. If it is N, then I just want to remove the N.
I tried the following but it adds "-" to all values:
databycitydiff2$x<-gsub( "N", "", databycitydiff2$x)
databycitydiff2$x<-sub("^","-", gsub( "S", "", databycitydiff2$x))
What I get is:
x
-10
-20
-35
-25
What I want is:
x
10
20
-35
-25
Any suggestions? thank you!
Dput of the dataframe column (before i changed it to as.character):
structure(c(57L, 47L, 62L, 45L, 45L, 57L, 62L, 55L, 29L, 55L,
60L, 54L, 70L, 70L, 62L, 13L, 55L, 37L, 33L, 29L, 70L, 23L, 72L,
11L, 72L, 55L, 19L, 51L, 62L, 29L, 37L, 72L, 36L, 7L, 17L, 71L,
9L, 41L, 29L, 21L, 55L, 37L, 25L, 19L, 21L, 13L, 29L, 31L, 49L,
21L, 31L, 25L, 35L, 37L, 41L, 17L, 45L, 39L, 45L, 49L, 70L, 17L,
6L, 7L, 37L, 72L, 41L, 26L, 35L, 38L, 45L, 45L, 45L, 37L, 41L,
37L, 37L, 27L, 23L, 45L, 47L, 37L, 58L, 61L, 55L, 53L, 27L, 41L,
35L, 55L, 35L, 29L, 13L, 2L, 7L, 44L, 5L, 22L, 58L, 54L, 37L,
19L, 31L, 27L, 58L, 12L, 72L, 33L, 21L, 2L, 9L, 21L, 65L, 49L,
51L, 45L, 58L, 9L, 53L, 22L, 45L, 35L, 33L, 41L, 47L, 31L, 37L,
45L, 25L, 37L, 39L, 14L, 39L, 9L, 22L, 18L, 57L, 55L, 37L, 49L,
58L, 25L, 7L, 22L, 57L, 23L, 20L, 4L, 51L, 71L, 35L, 4L, 20L,
20L, 22L, 24L, 39L, 12L, 14L, 71L, 67L, 41L, 51L, 43L, 58L, 44L,
41L, 37L, 61L, 49L, 37L, 21L, 33L, 39L, 31L, 37L, 31L, 9L, 57L,
71L, 51L, 24L, 21L, 25L, 39L, 22L, 35L, 37L, 53L, 38L, 53L, 17L,
45L, 29L, 7L, 70L, 55L, 8L, 55L, 25L, 5L, 70L, 71L, 37L, 72L,
51L, 3L, 9L, 41L, 45L, 47L, 13L, 55L, 25L, 33L, 37L, 11L, 11L,
27L, 21L, 29L, 29L, 42L, 5L, 27L, 53L, 51L, 21L, 37L, 37L, 45L,
58L, 61L, 19L, 2L, 9L, 25L, 21L, 53L, 41L, 23L, 5L, 5L, 55L,
23L, 55L, 39L, 15L, 15L, 44L, 71L, 37L, 5L, 21L, 7L, 43L, 49L,
71L, 44L, 21L, 21L, 23L, 73L, 41L, 35L, 53L, 21L, 21L, 21L, 20L,
3L, 21L, 27L, 45L, 72L, 19L, 21L, 29L, 60L, 3L, 20L, 70L, 3L,
6L, 18L, 49L, 13L, 22L, 3L, 53L, 58L, 21L, 25L, 31L, 15L, 31L,
7L, 53L, 39L, 29L, 44L, 3L, 20L, 17L, 35L, 29L, 25L, 23L, 53L,
29L, 19L, 45L, 18L, 35L, 56L, 2L, 43L, 61L, 22L, 9L, 57L, 49L,
9L, 53L, 55L, 18L, 33L, 33L, 33L, 44L, 6L, 29L, 29L, 26L, 45L,
33L, 3L, 63L, 51L, 64L, 57L, 39L, 58L, 53L, 43L, 53L, 26L, 18L,
25L, 7L, 21L, 23L, 23L, 27L, 19L, 21L, 19L, 19L, 23L, 11L, 25L,
17L, 27L, 21L, 17L, 21L, 19L, 3L, 60L, 13L, 72L, 13L, 58L, 57L,
23L, 11L, 27L, 54L, 19L, 47L, 7L, 43L, 15L, 39L, 25L, 25L, 20L,
33L, 33L, 5L, 34L, 5L, 1L, 58L, 60L, 60L, 57L, 10L, 73L, 30L,
26L, 15L, 3L, 58L, 71L, 43L, 70L, 39L, 21L, 26L, 49L, 60L, 56L,
13L, 57L, 1L, 49L, 35L, 37L, 47L, 19L, 53L, 30L, 58L, 22L, 70L,
54L, 57L, 33L, 60L, 45L, 22L, 13L, 51L, 26L, 10L, 51L, 53L, 61L,
44L, 71L, 58L, 60L, 60L, 51L, 54L, 45L, 57L, 7L, 28L, 58L, 24L,
54L, 25L, 57L, 58L, 57L, 60L, 70L, 49L, 53L, 27L, 43L, 47L, 43L,
43L, 29L, 44L, 37L, 16L, 55L, 27L, 9L, 18L, 5L, 25L, 35L, 29L,
47L, 47L, 19L, 41L, 29L, 1L, 55L, 72L, 51L, 60L, 57L, 72L, 13L,
9L, 3L, 22L, 3L, 30L, 18L, 37L, 54L, 72L, 41L, 3L, 9L, 12L, 29L,
71L, 55L, 72L, 22L, 7L, 21L, 57L, 43L, 19L, 5L, 6L, 19L, 71L,
47L, 17L, 71L, 22L, 18L, 20L, 3L, 38L, 19L, 39L, 30L, 3L, 70L,
17L, 55L, 25L, 34L, 24L, 3L, 3L, 22L, 58L, 18L, 13L, 13L, 13L,
33L, 3L, 43L, 73L, 37L, 33L, 24L, 2L, 28L, 20L, 39L, 3L, 44L,
9L, 56L, 30L, 3L, 47L, 17L, 33L, 17L, 21L, 21L, 27L, 31L, 33L,
21L, 17L, 49L, 27L, 49L, 31L, 31L, 45L, 21L, 26L, 3L, 57L, 33L,
35L, 21L, 35L, 72L, 61L, 58L, 58L, 61L, 57L, 45L, 31L, 21L, 25L,
63L, 54L, 49L, 58L, 54L, 37L, 13L, 25L, 23L, 19L, 13L, 47L, 71L,
47L, 37L, 27L, 7L, 38L, 13L, 17L, 73L, 14L, 5L, 8L, 6L, 31L,
29L, 53L, 58L, 7L, 23L, 14L, 31L, 37L, 9L, 7L, 29L, 57L, 6L,
50L, 33L, 19L, 23L, 23L, 27L, 33L, 71L, 71L, 71L, 71L, 56L, 56L,
71L, 19L, 19L, 71L, 56L, 56L, 56L, 56L, 71L, 71L, 41L, 71L, 71L,
56L, 71L, 71L, 56L, 56L, 72L, 72L, 19L, 37L, 27L, 51L, 45L, 53L,
17L, 13L, 12L, 45L, 18L, 58L, 17L, 57L, 70L, 41L, 35L, 41L, 52L,
72L, 38L, 39L, 32L, 18L, 49L, 37L, 18L, 61L, 28L, 30L, 25L, 32L,
58L, 5L, 33L, 18L, 27L, 28L, 33L, 70L, 22L, 70L, 58L, 58L, 57L,
49L, 57L, 28L, 17L, 13L, 22L, 9L, 16L, 13L, 10L, 23L, 3L, 36L,
24L, 56L, 8L, 57L, 5L, 9L, 57L, 29L, 57L, 55L, 25L, 11L, 37L,
35L, 9L, 25L, 41L, 21L, 33L, 70L, 33L, 5L, 21L, 41L, 21L, 71L,
25L, 25L, 57L, 33L, 7L, 45L, 45L, 61L, 70L, 7L, 41L, 31L, 41L,
72L, 53L, 29L, 23L, 49L, 31L, 27L, 27L, 13L, 39L, 73L, 33L, 41L,
25L, 71L, 29L, 31L, 47L, 60L, 45L, 3L, 47L, 21L, 31L, 33L, 39L,
21L, 21L, 25L, 9L, 25L, 17L, 22L, 27L, 51L, 70L, 53L, 25L, 60L,
23L, 3L, 41L, 9L, 3L, 18L, 55L, 3L, 33L, 56L, 23L, 21L, 17L,
45L, 33L, 39L, 58L, 58L, 39L, 55L, 43L, 20L, 35L, 57L, 49L, 23L,
60L, 58L, 57L, 21L, 33L, 72L, 15L, 62L, 52L, 47L, 22L, 23L, 30L,
19L, 21L, 37L, 45L, 41L, 62L, 34L, 35L, 57L, 47L, 37L, 17L, 43L,
70L, 61L, 47L, 45L, 60L, 58L, 72L, 70L, 58L, 29L, 3L, 31L, 35L,
31L, 9L, 72L, 45L, 60L, 1L, 61L, 51L, 45L, 11L, 22L, 58L, 19L,
57L, 58L, 31L, 70L, 55L, 57L, 54L, 5L, 41L, 41L, 33L, 9L, 45L,
33L, 41L, 37L, 18L, 64L, 57L, 27L, 25L, 49L, 39L, 57L, 29L, 54L,
39L, 31L, 25L, 27L, 21L, 27L, 25L, 35L, 6L, 45L, 21L, 24L, 49L,
22L, 35L, 20L, 25L, 31L, 47L, 49L, 15L, 28L, 70L, 51L, 45L, 35L,
49L, 26L, 45L, 25L, 45L, 33L, 44L, 21L, 24L, 18L, 22L, 22L, 57L,
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"21.70N", "21.70S", "23.31N", "23.31S", "24.92N", "24.92S", "26.52N",
"26.52S", "28.13N", "28.13S", "29.74N", "29.74S", "31.35N", "31.35S",
"32.95N", "32.95S", "34.56N", "34.56S", "36.17N", "36.17S", "37.78N",
"37.78S", "39.38N", "39.38S", "4.02N", "4.02S", "40.99N", "40.99S",
"42.59N", "42.59S", "44.20N", "44.20S", "45.81N", "45.81S", "47.42N",
"49.03N", "5.63N", "5.63S", "50.63N", "52.24N", "52.24S", "53.84N",
"55.45N", "57.05N", "58.66N", "60.27N", "61.88N", "63.49N", "65.09N",
"68.31N", "69.92N", "7.23N", "7.23S", "8.84N", "8.84S"), class = "factor")

Here is a base R approach with chartr to change "N" to "+" and "S" to "-", and then some string processing with sub to change the "+" and "-" to be in front of the number
tmp <- chartr("NS", "+-", c("10N", "10N", "35S", "25S"))
as.numeric(sub("(\\d+)([-+])", "\\2\\1", tmp))
#[1] 10 10 -35 -25

not that efficient though, (and it assumes that always N/S will be present)
ifelse(grepl("N",df$x), as.numeric(gsub("N","",df$x)), -1*as.numeric(gsub("S","",df$x)))
# [1] 10 20 -35 -25

With gsub and grepl:
as.numeric(gsub('[NS]','',x)) * c(-1,1)[grepl('N',x) + 1]
This results in:
> as.numeric(gsub('[NS]','',x)) * c(-1,1)[grepl('N',x) + 1]
[1] 10 20 -35 -25
Even another option is to use the gsubfn package:
x <- c('10N','20N','35S','25S')
library(gsubfn)
sapply(gsubfn('N|S', list('N'='*1','S'='*-1'), x),
function(x) eval(parse(text = x)),
USE.NAMES = FALSE)
This results in:
> sapply(gsubfn('N|S', list('N'='*1','S'='*-1'), x),
+ function(x) eval(parse(text = x)),
+ USE.NAMES = FALSE)
[1] 10 20 -35 -25

Here is an option with parse_number() from readr package to get the numeric values from the column and endsWith (which is a more efficient version of grepl) to check the trailing letter and make a vector of 1 or -1 based on which letter it is with a little mathematics:
df$x <- with(df, readr::parse_number(x) * (-1) ^ endsWith(x, "S"))
df
# x
#1 10
#2 20
#3 -35
#4 -25

strange error when creating a model with zelig

dput(t)
structure(list(Volume = c(2625941L, 4685483L, 3160694L, 2627816L,
2430273L, 2498011L, 2632445L, 3224434L, 2531941L, 5043867L, 2788003L,
3278796L, 3273977L, 3192613L, 3456297L, 2668175L, 2805861L, 2689392L,
2733510L, 3285889L, 2957370L, 3420479L, 3868692L, 4353776L, 3134759L,
2914727L, 3160491L, 3803716L, 3427911L, 2646258L, 3616962L, 3071943L,
3013008L, 4024996L, 4357129L, 3110560L, 3063334L, 4537971L, 1902002L,
2618413L, 2473005L, 2844029L, 2398462L, 3406776L, 3071573L, 3714231L,
4276458L, 3825187L, 2652650L, 3040994L, 2695117L, 3038566L, 2695652L,
2919113L, 2840214L, 2768958L, 5246649L, 3023172L, 3565584L, 2928450L,
3503840L, 2948165L, 3512192L, 3409995L, 3511665L, 3155152L, 3020401L,
2758133L, 2548245L, 3033309L, 2740213L, 2851881L, 3134557L, 4445879L,
3173913L, 3720477L, 3753070L, 3609973L, 3826284L, 4864280L, 4159588L,
3095322L, 3138732L, 3591433L, 3063357L, 3215559L, 3258059L, 3559727L,
4886550L, 4025763L, 4108614L, 5720774L, 4075195L, 3322352L, 3048940L,
3249172L, 3148053L, 3321660L, 3159642L, 3976820L, 3848960L, 3466783L,
3811408L, 6033563L, 4114751L, 3181385L, 2926695L, 2866148L, 2692198L,
3400891L, 2922295L, 3912049L, 3079066L, 2833293L, 3560196L, 3317644L,
3151086L, 3776538L, 5479510L, 3954497L, 3594429L, 3088262L, 2778180L,
3532457L), SLA = c(28L, 44L, 12L, 28L, 4L, 28L, 4L, 4L, 8L, 12L,
8L, 4L, 8L, 4L, 8L, 8L, 32L, 4L, 36L, 8L, 4L, 8L, 20L, 8L, 32L,
12L, 32L, 8L, 16L, 40L, 8L, 20L, 4L, 4L, 8L, 20L, 16L, 4L, 12L,
8L, 4L, 8L, 4L, 4L, 8L, 12L, 12L, 16L, 28L, 28L, 12L, 16L, 16L,
8L, 20L, 20L, 24L, 44L, 12L, 24L, 24L, 24L, 20L, 24L, 36L, 16L,
40L, 24L, 4L, 44L, 8L, 16L, 12L, 8L, 32L, 12L, 20L, 16L, 28L,
8L, 24L, 24L, 4L, 4L, 8L, 8L, 4L, 12L, 8L, 44L, 12L, 24L, 40L,
8L, 4L, 8L, 12L, 12L, 8L, 16L, 24L, 8L, 36L, 48L, 36L, 12L, 36L,
28L, 20L, 12L, 20L, 32L, 24L, 4L, 12L, 16L, 8L, 24L, 16L, 36L,
44L, 12L, 8L, 4L), Duration = c(21L, 25L, 15L, 13L, 15L, 20L,
17L, 20L, 12L, 15L, 31L, 12L, 24L, 16L, 25L, 13L, 13L, 20L, 21L,
20L, 26L, 15L, 26L, 21L, 27L, 20L, 34L, 29L, 74L, 62L, 33L, 27L,
26L, 23L, 30L, 26L, 26L, 18L, 19L, 13L, 25L, 18L, 20L, 18L, 37L,
20L, 22L, 25L, 24L, 22L, 42L, 17L, 18L, 18L, 28L, 18L, 28L, 32L,
23L, 31L, 12L, 30L, 40L, 30L, 18L, 18L, 19L, 27L, 21L, 31L, 23L,
26L, 14L, 22L, 21L, 21L, 26L, 30L, 21L, 23L, 12L, 22L, 24L, 29L,
36L, 19L, 21L, 25L, 24L, 29L, 26L, 34L, 33L, 17L, 17L, 24L, 19L,
18L, 12L, 18L, 11L, 19L, 22L, 48L, 49L, 25L, 16L, 43L, 18L, 18L,
19L, 15L, 38L, 19L, 22L, 28L, 28L, 34L, 16L, 53L, 38L, 23L, 27L,
17L)), .Names = c("Volume", "SLA", "Duration"), class = "data.frame", row.names = c(2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L,
43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L,
56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L,
69L, 70L, 71L, 72L, 73L, 75L, 76L, 77L, 79L, 80L, 81L, 82L, 84L,
85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L,
98L, 99L, 100L, 101L, 102L, 103L, 105L, 106L, 107L, 108L, 110L,
111L, 112L, 113L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L,
123L, 124L, 125L, 126L, 127L, 128L, 129L, 130L, 131L))
when I do this:
z.out1 <- zelig(Duration ~ Volume, model = "logit", data = t)
I get this error:
Error in `rownames<-`(`*tmp*`, value = c(1L, 0L)) :
attempt to set rownames on object with no dimensions
any ideas?

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