Duplicates are found by comparison of labnrs.
Only dates with exactly equal labnrs are considered duplicates.
Duplicate groups are numbered (from 0) and these numbers linked to
the individual dates in a internal column duplicate_group.
If you only want to see this grouping without removing anything use the mark_only flag.
c14bazAAR::remove_duplicates() can remove duplicates with three different strategies
according to the value of the arguments preferences and supermerge:
Option 1: By merging all dates in a duplicate_group. All non-equal variables in the duplicate group are turned to
NA. This is the default option.Option 2: By selecting individual database entries in a duplicate_group according to a trust hierarchy as defined by the parameter
preferences. In case of duplicates within one database the first occurrence in the table (top down) is selected. All databases not mentioned inpreferencesare dropped.Option 3: Like option 2, but in this case the different datasets in a duplicate_group are merged column by column to create a superdataset with a maximum of information. The column sourcedb is dropped in this case to indicate that multiple databases have been merged. Data citation is a lot more difficult with this option. It can be activated with
supermerge.
The option log allows to add a new column duplicate_remove_log
that documents the variety of values provided by all databases for this
duplicated date.
Usage
remove_duplicates(
x,
preferences = NULL,
supermerge = FALSE,
log = TRUE,
mark_only = FALSE
)
# Default S3 method
remove_duplicates(
x,
preferences = NULL,
supermerge = FALSE,
log = TRUE,
mark_only = FALSE
)
# S3 method for class 'c14_date_list'
remove_duplicates(
x,
preferences = NULL,
supermerge = FALSE,
log = TRUE,
mark_only = FALSE
)Arguments
- x
an object of class c14_date_list
- preferences
character vector with the order of source databases by which the deduping should be executed. If e.g. preferences = c("radon", "calpal") and a certain date appears in radon and euroevol, then only the radon entry remains. Default: NULL. With preferences = NULL all overlapping, conflicting information in individual columns of one duplicated date is removed. See Option 2 and 3.
- supermerge
boolean. Should the duplicated datasets be merged on the column level? Default: FALSE. See Option 3.
- log
logical. If log = TRUE, an additional column is added that contains a string documentation of all variants of the information for one date from all conflicting databases. Default = TRUE.
- mark_only
boolean. Should duplicates not be removed, but only indicated? Default: FALSE.
Value
an object of class c14_date_list with the additional columns duplicate_group or duplicate_remove_log
Examples
library(magrittr)
test_data <- tibble::tribble(
~sourcedb, ~labnr, ~c14age, ~c14std,
"A", "lab-1", 1100, 10,
"A", "lab-1", 2100, 20,
"B", "lab-1", 3100, 30,
"A", "lab-2", NA, 10,
"B", "lab-2", 2200, 20,
"C", "lab-3", 1300, 10
) %>% as.c14_date_list()
# remove duplicates with option 1:
test_data %>% remove_duplicates()
#> You did not provide the argument 'preferences' or your c14_date_list does not contain the necessary column 'sourcedb'. That means that duplicates are removed in a way that obscures conflicting information. As a result of this vital data for your analysis might get lost.
#> Please check '?duplicates' for more information.
#> Marking duplicates...
#> -> Search for accordances in Lab Codes...
#> -> Writing duplicate groups...
#>
|
| | 0%
|
|+++++++++++++++++++++++++ | 50%
|
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100%
#> Removing duplicates...
#> Radiocarbon date list
#> dates: 3
#> uncalBP: 2200 - 1300
#>
#> # A data frame: 3 × 5
#> sourcedb labnr c14age c14std duplicate_remove_log
#> <chr> <chr> <int> <int> <chr>
#> 1 C lab-3 1300 10 NA
#> 2 NA lab-1 NA NA sourcedb: A|B, labnr: lab-1, c14age: 1100|2100|3…
#> 3 NA lab-2 2200 NA sourcedb: A|B, labnr: lab-2, c14age: NA|2200, c1…
# remove duplicates with option 2:
test_data %>% remove_duplicates(
preferences = c("A", "B")
)
#> Marking duplicates...
#> -> Search for accordances in Lab Codes...
#> -> Writing duplicate groups...
#>
|
| | 0%
|
|+++++++++++++++++++++++++ | 50%
|
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100%
#> Removing duplicates...
#> Radiocarbon date list
#> dates: 2
#> uncalBP: 1100 - 1100
#>
#> # A data frame: 2 × 5
#> sourcedb labnr c14age c14std duplicate_remove_log
#> <chr> <chr> <int> <int> <chr>
#> 1 A lab-1 1100 10 sourcedb: A|B, labnr: lab-1, c14age: 1100|2100|3…
#> 2 A lab-2 NA 10 sourcedb: A|B, labnr: lab-2, c14age: NA|2200, c1…
# remove duplicates with option 3:
test_data %>% remove_duplicates(
preferences = c("A", "B"),
supermerge = TRUE
)
#> Marking duplicates...
#> -> Search for accordances in Lab Codes...
#> -> Writing duplicate groups...
#>
|
| | 0%
|
|+++++++++++++++++++++++++ | 50%
|
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100%
#> Removing duplicates...
#> Radiocarbon date list
#> dates: 2
#> uncalBP: 2200 - 1100
#>
#> # A data frame: 2 × 4
#> labnr c14age c14std duplicate_remove_log
#> <chr> <int> <int> <chr>
#> 1 lab-1 1100 10 sourcedb: A|B, labnr: lab-1, c14age: 1100|2100|3100, c14s…
#> 2 lab-2 2200 10 sourcedb: A|B, labnr: lab-2, c14age: NA|2200, c14std: 10|…