Retrieve and assign elements of a TableTree

Retrieve and assign elements of a TableTree

Usage

# S4 method for VTableTree,ANY,ANY,list
[(x, i, j, ...) <- value

# S4 method for VTableTree,logical,logical
[(x, i, j, ..., drop = FALSE)

Arguments

x

TableTree

i

index

j

index

...

Includes

keep_topleft: logical(1) ([ only) Should the top-left material for the table be retained after subsetting. Defaults to TRUE if all rows are included (i.e. subsetting was by column), and drops it otherwise.
keep_titles: logical(1) Should title information be retained. Defaults to FALSE.
keep_footers: logical(1) Should non-referential footer information be retained. Defaults to keep_titles.
reindex_refs: logical(1). Should referential footnotes be re-indexed as if the resulting subset is the entire table. Defaults to TRUE.

value

Replacement value (list, TableRow, or TableTree)

drop

logical(1). Should the value in the cell be returned if one cell is selected by the combination of i and j. It is not possible to return a vector of values. To do so please consider using cell_values(). Defaults to FALSE.

Value

a TableTree (or ElementaryTable) object, unless a single cell was selected with drop=TRUE, in which case the (possibly multi-valued) fully stripped raw value of the selected cell.

Details

by default, subsetting drops the information about title, subtitle, main footer, provenance footer, and topleft. If only a column is selected and all rows are kept, the topleft information remains as default. Any referential footnote is kept whenever the subset table contains the referenced element.

Note

subsetting always preserve the original order, even if provided indexes do not preserve it. If sorting is needed, please consider using sort_at_path(). Also note that character indices are treated as paths, not vectors of names in both [ and [<-.

Examples

lyt <- basic_table(title = "Title",
                   subtitles = c("Sub", "titles"),
                   prov_footer = "prov footer",
                   main_footer = "main footer") %>%
   split_cols_by("ARM") %>%
   split_rows_by("SEX") %>%
   analyze(c("AGE"))

tbl <- build_table(lyt, DM)
top_left(tbl) <- "Info"
tbl
#> Title
#> Sub
#> titles
#> 
#> ——————————————————————————————————————————————————————————
#> Info               A: Drug X   B: Placebo   C: Combination
#> ——————————————————————————————————————————————————————————
#> F                                                         
#>   Mean               33.71       33.84          34.89     
#> M                                                         
#>   Mean               36.55       32.10          34.28     
#> U                                                         
#>   Mean                NA           NA             NA      
#> UNDIFFERENTIATED                                          
#>   Mean                NA           NA             NA      
#> ——————————————————————————————————————————————————————————
#> 
#> main footer
#> 
#> prov footer

# As default header, footer, and topleft information is lost
tbl[1, ]
#>     A: Drug X   B: Placebo   C: Combination
#> ———————————————————————————————————————————
#> F                                          
tbl[1:2, 2]
#>          B: Placebo
#> ———————————————————
#> F                  
#>   Mean     33.84   

# Also boolean filters can work
tbl[, c(FALSE, TRUE, FALSE)]
#> Note: method with signature ‘VTableTree#missing#ANY’ chosen for function ‘[’,
#>  target signature ‘TableTree#missing#logical’.
#>  "VTableTree#ANY#logical" would also be valid
#> Info               B: Placebo
#> —————————————————————————————
#> F                            
#>   Mean               33.84   
#> M                            
#>   Mean               32.10   
#> U                            
#>   Mean                 NA    
#> UNDIFFERENTIATED             
#>   Mean                 NA    

# If drop = TRUE, the content values are directly retrieved
tbl[2, 1]
#>        A: Drug X
#> ————————————————
#> Mean     33.71  
tbl[2, 1, drop = TRUE]
#> [1] 33.71429

# Drop works also if vectors are selected, but not matrices
tbl[, 1, drop = TRUE]
#> Warning: Trying to drop more than one subsetted value. We support this only with accessor function `cell_values()`. No drop will be done at this time.
#> Info               A: Drug X
#> ————————————————————————————
#> F                           
#>   Mean               33.71  
#> M                           
#>   Mean               36.55  
#> U                           
#>   Mean                NA    
#> UNDIFFERENTIATED            
#>   Mean                NA    
tbl[2, , drop = TRUE]
#> Warning: Trying to drop more than one subsetted value. We support this only with accessor function `cell_values()`. No drop will be done at this time.
#>        A: Drug X   B: Placebo   C: Combination
#> ——————————————————————————————————————————————
#> Mean     33.71       33.84          34.89     
tbl[1, 1, drop = TRUE] # NULL because it is a label row
#> Warning: The value selected with drop = TRUE belongs to a label row. NULL will be returned
#> NULL
tbl[2, 1:2, drop = TRUE] # vectors can be returned only with cell_values()
#> Warning: Trying to drop more than one subsetted value. We support this only with accessor function `cell_values()`. No drop will be done at this time.
#>        A: Drug X   B: Placebo
#> —————————————————————————————
#> Mean     33.71       33.84   
tbl[1:2, 1:2, drop = TRUE] # no dropping because it is a matrix
#> Warning: Trying to drop more than one subsetted value. We support this only with accessor function `cell_values()`. No drop will be done at this time.
#>          A: Drug X   B: Placebo
#> ———————————————————————————————
#> F                              
#>   Mean     33.71       33.84   

# If all rows are selected, topleft is kept by default
tbl[, 2]
#> Info               B: Placebo
#> —————————————————————————————
#> F                            
#>   Mean               33.84   
#> M                            
#>   Mean               32.10   
#> U                            
#>   Mean                 NA    
#> UNDIFFERENTIATED             
#>   Mean                 NA    
tbl[, 1]
#> Info               A: Drug X
#> ————————————————————————————
#> F                           
#>   Mean               33.71  
#> M                           
#>   Mean               36.55  
#> U                           
#>   Mean                NA    
#> UNDIFFERENTIATED            
#>   Mean                NA    

# It is possible to deselect values
tbl[-2, ]
#>                    A: Drug X   B: Placebo   C: Combination
#> ——————————————————————————————————————————————————————————
#> F                                                         
#> M                                                         
#>   Mean               36.55       32.10          34.28     
#> U                                                         
#>   Mean                NA           NA             NA      
#> UNDIFFERENTIATED                                          
#>   Mean                NA           NA             NA      
tbl[, -1]
#> Info               B: Placebo   C: Combination
#> ——————————————————————————————————————————————
#> F                                             
#>   Mean               33.84          34.89     
#> M                                             
#>   Mean               32.10          34.28     
#> U                                             
#>   Mean                 NA             NA      
#> UNDIFFERENTIATED                              
#>   Mean                 NA             NA      

# Values can be reassigned
tbl[2, 1] <- rcell(999)
tbl[2, ] <- list(rrow("FFF", 888, 666, 777))
tbl[6, ] <- list(-111, -222, -333)
tbl
#> Title
#> Sub
#> titles
#> 
#> ——————————————————————————————————————————————————————————
#> Info               A: Drug X   B: Placebo   C: Combination
#> ——————————————————————————————————————————————————————————
#> F                                                         
#>   FFF                 888         666            777      
#> M                                                         
#>   Mean               36.55       32.10          34.28     
#> U                                                         
#>   Mean               -111         -222           -333     
#> UNDIFFERENTIATED                                          
#>   Mean                NA           NA             NA      
#> ——————————————————————————————————————————————————————————
#> 
#> main footer
#> 
#> prov footer

# We can keep some information from the original table if we need
tbl[1, 2, keep_titles = TRUE]
#> Title
#> Sub
#> titles
#> 
#> ——————————————
#>     B: Placebo
#> ——————————————
#> F             
#> ——————————————
#> 
#> main footer
#> 
#> prov footer
tbl[1, 2, keep_footers = TRUE, keep_titles = FALSE]
#>     B: Placebo
#> ——————————————
#> F             
#> ——————————————
#> 
#> main footer
#> 
#> prov footer
tbl[1, 2, keep_footers = FALSE, keep_titles = TRUE]
#> Title
#> Sub
#> titles
#> 
#> ——————————————
#>     B: Placebo
#> ——————————————
#> F             
tbl[1, 2, keep_footers = TRUE]
#>     B: Placebo
#> ——————————————
#> F             
#> ——————————————
#> 
#> main footer
#> 
#> prov footer
tbl[1, 2, keep_topleft = TRUE]
#> Info   B: Placebo
#> —————————————————
#> F                

# Keeps the referential footnotes when subset contains them
fnotes_at_path(tbl, rowpath = c("SEX", "M", "AGE", "Mean")) <- "important"
tbl[4, 1]
#>            A: Drug X
#> ————————————————————
#> Mean {1}     36.55  
#> ————————————————————
#> 
#> {1} - important
#> ————————————————————
#> 
tbl[2, 1] # None present
#>       A: Drug X
#> ———————————————
#> FFF      888   

# We can reindex referential footnotes, so that the new table does not depend
#  on the original one
fnotes_at_path(tbl, rowpath = c("SEX", "U", "AGE", "Mean")) <- "important"
tbl[, 1] # both present
#> Info               A: Drug X
#> ————————————————————————————
#> F                           
#>   FFF                 888   
#> M                           
#>   Mean {1}           36.55  
#> U                           
#>   Mean {2}           -111   
#> UNDIFFERENTIATED            
#>   Mean                NA    
#> ————————————————————————————
#> 
#> {1} - important
#> {2} - important
#> ————————————————————————————
#> 
tbl[5:6, 1] # {1} because it has been indexed again
#>              A: Drug X
#> ——————————————————————
#> U                     
#>   Mean {1}     -111   
#> ——————————————————————
#> 
#> {1} - important
#> ——————————————————————
#> 
tbl[5:6, 1, reindex_refs = FALSE] # {2} -> not reindexed
#>              A: Drug X
#> ——————————————————————
#> U                     
#>   Mean {2}     -111   
#> ——————————————————————
#> 
#> {2} - important
#> ——————————————————————
#> 

# Note that order can not be changed with subsetting
tbl[c(4, 3, 1), c(3, 1)] # It preserves order and wanted selection
#>              A: Drug X   C: Combination
#> ———————————————————————————————————————
#> F                                      
#> M                                      
#>   Mean {1}     34.28         36.55     
#> ———————————————————————————————————————
#> 
#> {1} - important
#> ———————————————————————————————————————
#>

Retrieve and assign elements of a `TableTree`