How to separate a column of data.table given conditions - r

Question

After reading some XML files, I am to create a data.table with a specific column names, e.g. Name, Score, Medal, etc. However, I am confused of how i should separate the single column (see the code and results) into many with given criterias.
In my opinion, we either need a cycle just with a step, or a special function, but I do not know what function exactly :/
stage1 <- read_html("1973.html")
stage2 <- xml_find_all(stage1, ".//tr")
xml_text(stage2)
stage3 <- xml_text(xml_find_all(stage2, ".//td"))
stage3
DT <- data.table(stage3, keep.rownames=TRUE, check.names=TRUE, key=NULL,
stringsAsFactors=TRUE)
for (i in seq(from = 1, to = 1375, by = 11)){
if (is.numeric(DT[i,stage3] = FALSE)){
DT$Name <- DT[i,stage3]
}
}
https://pp.userapi.com/c845220/v845220632/1678a5/IRykEniYiiA.jpg
This is example of first 20 rows of 1375
Here how the data.table looks now. What I need, is to separate these results to columns "Name" (e.g. Sergei konyagin), Country (e.g. USSR), score for problems 1-8 (8 columns, respectively), and the medal. The cycle I have written, I think, is something that should extract with a step 11 (since every name, country, etc. repeats every 11 rows) the value from existing column and transfer it into new one. Unfortunately, it doesn't work :/
Thanks in advance for your help!

Answer 1

Give this a shot.
First, load the required packages:
library (data.table)
library (stringr) # this is just for the piping operator %>%
You would read in your own data table here, I am creating one as an example:
dat = c( "Sergey","USSR",1,2,3,4,5,6,7,8,"silver") %>% rep (125) %>% data.table
setnames (dat, "stage3")
As a quick note, I would not be reading in your strings as factors as you do in your own code, because then it can screw up the conversion to numeric.
This will repeat itself to fill out the table. this only works if your table doesn't skip values. also, not advisable to have column names as numbers, better to give them proper names like "test1","test2", etc:
dat [, metadata := c ("name","country",1:8,"medal") ] # whatever you want to name your future 11 columns
dat [, participant := 1: (.N / 11) %>% rep (each = 11) ] # same idea, can't have missing rows
Now, reshape and convert from strings to numeric where possible:
new.dat =
dcast (dat, participant ~ metadata, value.var = "stage3") [, lapply (.SD, type.convert) ]