Copy attributes from one object to another — copy

This function copies over any additional attributes from `source` into `target`. Any attributes already present in `target` would be left untouched. This function is useful after manipulating the data from the *_data preparation functions to ensure any attributes necessary for creating the plot aren't lost.

Usage

copy_attributes(target, source)

Arguments

target: The object to which attributes should be added.
source: The object whose attributes to copy.

Value

The object specified in `target` with all additional attributes in `source` object.

Examples


## Simple example
a <- data.frame(Var1 = runif(1:10), Var2 = runif(1:10))
b <- data.frame(Var3 = runif(1:10), Var4 = runif(1:10))
attr(b, "attr1") <- "Lorem"
attr(b, "attr2") <- "ipsum"

print(attributes(a))
#> $names
#> [1] "Var1" "Var2"
#> 
#> $class
#> [1] "data.frame"
#> 
#> $row.names
#>  [1]  1  2  3  4  5  6  7  8  9 10
#> 
print(attributes(b))
#> $names
#> [1] "Var3" "Var4"
#> 
#> $class
#> [1] "data.frame"
#> 
#> $row.names
#>  [1]  1  2  3  4  5  6  7  8  9 10
#> 
#> $attr1
#> [1] "Lorem"
#> 
#> $attr2
#> [1] "ipsum"
#> 

## Copy over attributes of `b` into `a`
print(copy_attributes(target = a, source = b))
#>          Var1      Var2
#> 1  0.67838043 0.2255625
#> 2  0.73531960 0.3008308
#> 3  0.19595673 0.6364656
#> 4  0.98053967 0.4790245
#> 5  0.74152153 0.4321713
#> 6  0.05144628 0.7064338
#> 7  0.53021246 0.9485766
#> 8  0.69582388 0.1803388
#> 9  0.68855600 0.2168999
#> 10 0.03123033 0.6801629
## Note the attributes already present in `a` are left untouched

## Can also be used in the dplyr pipeline
library(dplyr)

iris_sub <- iris[1:10, ]
attr(iris_sub, "attr1") <- "Lorem"
attr(iris_sub, "attr2") <- "ipsum"
attributes(iris_sub)
#> $names
#> [1] "Sepal.Length" "Sepal.Width"  "Petal.Length" "Petal.Width"  "Species"     
#> 
#> $row.names
#>  [1]  1  2  3  4  5  6  7  8  9 10
#> 
#> $class
#> [1] "data.frame"
#> 
#> $attr1
#> [1] "Lorem"
#> 
#> $attr2
#> [1] "ipsum"
#> 

## Grouping can drop attributes we set
iris_sub %>%
   group_by(Species) %>%
   summarise(mean(Sepal.Length)) %>%
   attributes()
#> $class
#> [1] "tbl_df"     "tbl"        "data.frame"
#> 
#> $row.names
#> [1] 1
#> 
#> $names
#> [1] "Species"            "mean(Sepal.Length)"
#> 

## Use copy_attributes with `iris_sub` object as source
##  to add the attributes again
iris_sub %>%
   group_by(Species) %>%
   summarise(mean(Sepal.Length)) %>%
   copy_attributes(source = iris_sub) %>%
   attributes()
#> $class
#> [1] "tbl_df"     "tbl"        "data.frame"
#> 
#> $row.names
#> [1] 1
#> 
#> $names
#> [1] "Species"            "mean(Sepal.Length)"
#> 
#> $attr1
#> [1] "Lorem"
#> 
#> $attr2
#> [1] "ipsum"
#>