Description Usage Arguments Details Value Examples
eBird checklists can be shared among a group of multiple observers, in which
case observations will be duplicated in the database. This functions removes
these duplicates from the eBird Basic Dataset (EBD) or the EBD sampling event
data (with checklists_only = TRUE
), creating a set of unique bird
observations. This function is called automatically by read_ebd()
and
read_sampling()
.
1 2 3 | auk_unique(x, group_id = "group_identifier",
checklist_id = "sampling_event_identifier",
species_id = "scientific_name", checklists_only = FALSE)
|
x |
data.frame; the EBD data frame, typically as imported by
|
group_id |
character; the name of the group ID column. |
checklist_id |
character; the name of the checklist ID column, each
checklist within a group will get a unique value for this field. The record
with the lowest |
species_id |
character; the name of the column identifying species uniquely. This is required to ensure that removing duplicates is done independently for each species. Note that this will not treat sub-species independently and, if that behavior is desired, the user will have to generate a column uniquely identifying species and subspecies and pass that column's name to this argument. |
checklists_only |
logical; whether the dataset provided only contains
checklist information as with the sampling event data file. If this
argument is |
This function chooses the checklist within in each that has the
lowest value for the field specified by checklist_id
. A new column is
also created, checklist_id
, whose value is the taken from the field
specified in the checklist_id
parameter for non-group checklists and from
the field specified by the group_id
parameter for grouped checklists.
A data.frame with unique observations, and an additional field,
checklist_id
, which is a combination of the sampling event and group IDs.
1 2 3 4 5 6 7 | # read in an ebd file and don't automatically remove duplicates
ebd <- system.file("extdata/ebd-sample.txt", package = "auk") %>%
read_ebd(unique = FALSE)
# remove duplicates
ebd_unique <- auk_unique(ebd)
nrow(ebd)
nrow(ebd_unique)
|
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