Merge repeated rows into multirow cells

merge_repeated_rows() looks within each column for contiguous groups of identical cells. These are merged by setting rowspan(). Doing this helps remove redundant information from the table.

Usage

merge_repeated_rows(ht, row, col)

Arguments

ht: A huxtable.
row: A row specifier. See rowspecs for details.
col: An optional column specifier.

Value

The ht object.

Details

If row contains gaps, results may be unexpected (and a warning is given).

Cell content

In merged cell ranges, only the top left cell's content is displayed. In addition, when you merge cells (either by setting colspan() or rowspan(), or using merge_cells() and friends) the content of the top left cell is copied to other cells. This prevents unexpected changes to content if you reorder or subset rows and columns.

Examples

ht <- as_hux(jams[c(1, 2, 2, 3, 3, 4), ])
ht <- add_columns(ht, c("Sugar", "30%", "40%", "30%", "40%", "30%"),
  after = 1
)
ht
#>                            Type         Sugar   Price  
#>                            Strawberry   30%      1.90  
#>                            Strawberry   40%      1.90  
#>                            Raspberry    30%      2.10  
#>                            Raspberry    40%      2.10  
#>                            Plum         30%      1.80  
#> 
#> Column names: Type, , Price
merge_repeated_rows(ht)
#>                            Type         Sugar   Price  
#>                            Strawberry   30%      1.90  
#>                                         40%            
#>                            Raspberry    30%      2.10  
#>                                         40%            
#>                            Plum         30%      1.80  
#> 
#> Column names: Type, , Price
merge_repeated_rows(ht, everywhere, "Type")
#>                            Type         Sugar   Price  
#>                            Strawberry   30%      1.90  
#>                                         40%      1.90  
#>                            Raspberry    30%      2.10  
#>                                         40%      2.10  
#>                            Plum         30%      1.80  
#> 
#> Column names: Type, , Price