Shorter substitute for tab_row_group when rows are large-CodePudding

I love gt package of R but I am having trouble in coming up with a crisp code for row grouping that is suitable for large tables and where row group labels are unknown.

Consider this toy example, and since this is a small data.table it looks ok.

library(data.table)
library(magrittr)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:data.table':
#> 
#>     hour, isoweek, mday, minute, month, quarter, second, wday, week,
#>     yday, year
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
library(gt)

# create a toy data.table
dt <- data.table(datetime = seq(ymd_hm(202205100800),by = "5 hours",length.out = 15))[order(datetime)]
dt[,date:=as_date(datetime)]
dt[,time:=format(datetime,"%H:%M")]
dt[,values:=seq(1000,by = 10,length.out=15)]

# Here's how my toy data.table looks like:
print(dt)
#>                datetime       date  time values
#>  1: 2022-05-10 08:00:00 2022-05-10 08:00   1000
#>  2: 2022-05-10 13:00:00 2022-05-10 13:00   1010
#>  3: 2022-05-10 18:00:00 2022-05-10 18:00   1020
#>  4: 2022-05-10 23:00:00 2022-05-10 23:00   1030
#>  5: 2022-05-11 04:00:00 2022-05-11 04:00   1040
#>  6: 2022-05-11 09:00:00 2022-05-11 09:00   1050
#>  7: 2022-05-11 14:00:00 2022-05-11 14:00   1060
#>  8: 2022-05-11 19:00:00 2022-05-11 19:00   1070
#>  9: 2022-05-12 00:00:00 2022-05-12 00:00   1080
#> 10: 2022-05-12 05:00:00 2022-05-12 05:00   1090
#> 11: 2022-05-12 10:00:00 2022-05-12 10:00   1100
#> 12: 2022-05-12 15:00:00 2022-05-12 15:00   1110
#> 13: 2022-05-12 20:00:00 2022-05-12 20:00   1120
#> 14: 2022-05-13 01:00:00 2022-05-13 01:00   1130
#> 15: 2022-05-13 06:00:00 2022-05-13 06:00   1140

# Now let's create a table using the gt package and add row groups. 
# We will group on date.
dt %>% 
  gt %>% 
  tab_row_group(label = "May 10",id = "may10",rows = date==ymd(20220510)) %>% 
  tab_row_group(label = "May 11",id = "may11",rows = date==ymd(20220511)) %>% 
  tab_row_group(label = "May 12",id = "may12",rows = date==ymd(20220512))  %>% 
  row_group_order(groups = c("may10","may11","may12")) %>% 
  cols_hide(columns = c(datetime,date))

But in real life there may be hundreds of dates. And the dates are not known in advance. If I use the current method of tab_row_group() in gt, the code will become unwieldy

Is there a way to shorten the code and automate the row groupings?

CodePudding user response：

you can use groupname_col inside the gt function

dt %>% 
 gt(groupname_col = c("date")) %>% 
 cols_hide(columns = c(datetime,date))