Convert long tibble to multi-column HTML table - r

Question

I have a two-column tibble with many rows, and I would like to display the contents of the tibble in an HTML table while flowing the contents of the tibble to multiple columns. Here's a sample tibble of data typical of what I'm working with.
structure(list(scores = 328:360, points = c(1.44976648822324,
2.39850620178477, 3.54432361637504, 4.87641377160755, 6.38641933285773,
8.06758106817846, 9.91425882252425, 11.9216360940354, 14.0855256867808,
16.4022354393545, 18.8684718158155, 21.4812684932283, 24.2379320869751,
27.136, 30.1732070790481, 33.3474588150326, 36.6568095024477,
40.0994442217347, 43.6736638137649, 47.3778722279125, 51.2105657758874,
55.1703239324027, 59.2558014037444, 63.46572124494, 67.7988688512606,
72.2540866842331, 76.8302696189673, 81.5263608204015, 86.3413480724772,
91.2742604972992, 96.3241656118041, 101.490166677918, 106.771400309065
)), row.names = c(NA, -33L), class = c("tbl_df", "tbl", "data.frame"
))
I would like to display those data pairs in an HTML table something like the following:
| Score | Points | Score | Points | Score | Points | Score | Points |
|------:|-------:|------:|-------:|------:|-------:|------:|-------:|
| 328 | 1.4 | 337 | 16.4 | 346 | 43.7 | 355 | 81.5 |
| 329 | 2.4 | 338 | 18.9 | 347 | 47.4 | 356 | 86.3 |
| 330 | 3.5 | 339 | 21.5 | 348 | 51.2 | 357 | 91.3 |
| 331 | 4.9 | 340 | 24.2 | 349 | 55.2 | 358 | 96.3 |
| 332 | 6.4 | 341 | 27.1 | 350 | 59.3 | 359 | 101.5 |
| 333 | 8.1 | 342 | 30.2 | 351 | 63.5 | 360 | 106.8 |
| 334 | 9.9 | 343 | 33.3 | 352 | 67.8 | | |
| 335 | 11.9 | 344 | 36.7 | 353 | 72.3 | | |
| 336 | 14.1 | 345 | 40.1 | 354 | 76.8 | | |
I'd like to have a solution that would generate a four-doublecolumn layout no matter how many rows are in the original tibble.
I started by slicing the tibble into four sections, but got stuck because the fourth one didn't have as many elements as the first three.
Any suggestions on a method to accomplish this?

Answer 1

You can write a small function, that will take in the data and the number of columns you need. Default is just 4 columns
reshaping = function(dat, cols = 4){
n = nrow(dat)
m = ceiling(n/cols)
time=rep(1:cols, each = m, len = n)
id = rep(1:m, times = cols, len = n)
reshape(cbind(id, time, dat), idvar = 'id', dir='wide')[-1]
}
reshaping(dat)
scores.1 points.1 scores.2 points.2 scores.3 points.3 scores.4 points.4
1 328 1.449766 337 16.40224 346 43.67366 355 81.52636
2 329 2.398506 338 18.86847 347 47.37787 356 86.34135
3 330 3.544324 339 21.48127 348 51.21057 357 91.27426
4 331 4.876414 340 24.23793 349 55.17032 358 96.32417
5 332 6.386419 341 27.13600 350 59.25580 359 101.49017
6 333 8.067581 342 30.17321 351 63.46572 360 106.77140
7 334 9.914259 343 33.34746 352 67.79887 NA NA
8 335 11.921636 344 36.65681 353 72.25409 NA NA
9 336 14.085526 345 40.09944 354 76.83027 NA NA
reshaping(dat,8)
scores.1 points.1 scores.2 points.2 scores.3 points.3 scores.4 points.4 scores.5 points.5 scores.6 points.6 scores.7 points.7
1 328 1.449766 333 8.067581 338 18.86847 343 33.34746 348 51.21057 353 72.25409 358 96.32417
2 329 2.398506 334 9.914259 339 21.48127 344 36.65681 349 55.17032 354 76.83027 359 101.49017
3 330 3.544324 335 11.921636 340 24.23793 345 40.09944 350 59.25580 355 81.52636 360 106.77140
4 331 4.876414 336 14.085526 341 27.13600 346 43.67366 351 63.46572 356 86.34135 NA NA
5 332 6.386419 337 16.402235 342 30.17321 347 47.37787 352 67.79887 357 91.27426 NA NA