R/logbook_floating_object_buoy_id_redundancy_control.R
    logbook_floating_object_buoy_id_redundancy_control.RdThe purpose of the logbook_floating_object_buoy_id_redundancy_control function is to provide a table of data that contains a incoherent buoy operation on a same object.
logbook_floating_object_buoy_id_redundancy_control(
  dataframe1,
  dataframe2,
  output,
  operation_code = c("2", "3")
)data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_floating_object_buoy_id_redundancy_control.
data.frame expected. Csv or output of the function data_extraction, which must be done before using the logbook_floating_object_buoy_id_redundancy_control.
character expected. Kind of expected output. You can choose between "message", "report" or "logical".
character expected. Default values: c("2","3"). Vector containing the operation code to detected to avoid incoherence.
The function returns a character with output is "message", a data.frame with output is "report", a logical with output is "logical".
The input dataframe must contain all these columns for the function to work :
  floatingobject_id
Dataframe 2:
  transmittingbuoy_id
  transmittingbuoyoperation_code
  floatingobject_id
  transmittingbuoy_code
dataframe1 <- data.frame(floatingobject_id = c("1","2","3","4", "5"))
dataframe2 <- data.frame(transmittingbuoy_id = c("1","2","3","4", "5", "6"),
                         floatingobject_id = c("1","2","3","3","5","5"),
                         transmittingbuoyoperation_code = c("2","3","2","4", "2", "3"),
                         transmittingbuoy_code = c("1","2","3","3", "1", "1"))
logbook_floating_object_buoy_id_redundancy_control(dataframe1, dataframe2, output = "report")
#> # A tibble: 5 × 3
#>   floatingobject_id transmittingbuoy_code logical
#>   <chr>             <chr>                 <lgl>  
#> 1 1                 1                     FALSE  
#> 2 2                 2                     FALSE  
#> 3 3                 3                     FALSE  
#> 4 4                 NA                    FALSE  
#> 5 5                 1                     TRUE