Subset a huxtable

Usage

# S3 method for class 'huxtable'
x[i, j, drop = FALSE]

# S3 method for class 'huxtable'
x[i, j] <- value

# S3 method for class 'huxtable'
x$name <- value

# S3 method for class 'huxtable'
x[[i, j]] <- value

Arguments

x: A huxtable.
i: Rows to select.
j, name: Columns to select.
drop: Only included for compatibility with [.data.frame. Do not use.
value: A matrix, data frame, huxtable or similar object.

Value

[ returns a huxtable. $ and [[ return data from the underlying data frame.

Replacing existing rows and columns

For the replacement function [<-, if value is a huxtable, then its properties will be copied into x. Replacement functions $<- and [[<- replace existing data without affecting any properties.

Adding new rows and columns

If new columns or rows are created, then properties will be copied from the last column or row of x, or from value if value is a huxtable.

These methods are stricter than their data frame equivalents in some places. You can't add new rows or column at a numeric location without specifying all intervening rows/columns. New values must have the appropriate dimensions (vectors will be interpreted appropriately).

Examples

jams[1:3, ]
#>                               Type           Price  
#>                               Strawberry      1.90  
#>                               Raspberry       2.10  
#> 
#> Column names: Type, Price
class(jams[1:3, ])
#> [1] "huxtable"   "data.frame"
jams[, 1]
#>                                  Type            
#>                                  Strawberry      
#>                                  Raspberry       
#>                                  Plum            
#> 
#> Column names: Type
jams$Type
#> [1] "Type"       "Strawberry" "Raspberry"  "Plum"      
prices <- huxtable(c("Price", 1.70, 2.00, 2.20))
number_format(prices) <- 2
bold(prices) <- TRUE
jams[, 2] <- prices
jams
#>                               Type         Price    
#>                               Strawberry   1.70     
#>                               Raspberry    2.00     
#>                               Plum         2.20     
#> 
#> Column names: Type, Price

data(jams)
jams$price <- c("Price", 1.70, 2.00, 2.20)
jams
#>                            Type         Price   Price  
#>                            Strawberry   1.70    1.70   
#>                            Raspberry    2.00    2.00   
#>                            Plum         2.20    2.20   
#> 
#> Column names: Type, Price, price