CODEWITHSUNDEEP
r
Vasile
Vasile

Reputation: 1017

Transform a named vector in data frame

I have the following vector:

dput(z1)
c(Measure = "Height", IFS = "12,636.00", IFS = "15,401.00", 
IFS = "15,371.00", IFS = "16,218.00", IFS = "20,975.00", Measure = "Height", 
IFS = "12,258.00", IFS = "12,542.00", IFS = "13,014.00", IFS = "13,508.00", 
IFS = "11,934.00", Measure = "Height", IFS = "5,854.46", IFS = "6,500.39", 
IFS = "5,208.78", IFS = "4,221.37", NA, Measure = "Height", 
IFS = "845.70", IFS = "1,161.30", IFS = "1,217.80", IFS = "875.90", 
IFS = "401.90", Measure = "Height", IFS = "34,416.00", IFS = "33,249.00", 
IFS = "32,942.00", IFS = "33,174.00", IFS = "33,267.00", Measure = "Height", 
IFS = "2,390.00", IFS = "2,269.00", IFS = "1,902.00", IFS = "1,710.20", 
IFS = "1,734.60")

I would like to transform it into a data frame that would look like this:

Measure    IFS          IFS       IFS           IFS          IFS     

Height    12,636.00  15,401.00  15,371.00   16,218.00     20,975.00
Height    12,258.00  12,542.00  13,014.00   13,508.00     11,934.00
Height    5,854.46   6,500.39   5,208.78    4,221.37       NA

... plus the three more rows. That is the first 6 values are a row and so on.

I tried

z1<-stack(z1) then
z1<-t(z1)
z1<-as.data.frame(z1)
z1<-matrix( z1, ncol=6)

But the data is not arranging the way I need it. Thanks

Upvotes: 1

Views: 53

Answers (1)

akrun
akrun

Reputation: 887831

We could split into a list, based on the presence of 'Height' and collapse them by rbinding with map_dfr

library(purrr)
library(dplyr)
z2 <- z1[complete.cases(z1)]
map_dfr(split(z2, cumsum(z2 %in% 'Height')), as.data.frame.list)

-output

Measure       IFS     IFS.1     IFS.2     IFS.3     IFS.4
1  Height 12,636.00 15,401.00 15,371.00 16,218.00 20,975.00
2  Height 12,258.00 12,542.00 13,014.00 13,508.00 11,934.00
3  Height  5,854.46  6,500.39  5,208.78  4,221.37      <NA>
4  Height    845.70  1,161.30  1,217.80    875.90    401.90
5  Height 34,416.00 33,249.00 32,942.00 33,174.00 33,267.00
6  Height  2,390.00  2,269.00  1,902.00  1,710.20  1,734.60

Upvotes: 1

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