Parse and examine further GBIF issues on a dataset.
Output from a call to
Named parameters to only get back (e.g., cdround), or to remove (e.g. -cdround).
(character) One of:
For split and split_expand, values in cells become y ("yes") or n ("no").
See also the vignette Cleaning data using GBIF issues
Note that you can also query based on issues, e.g.,
occ_search(taxonKey=1, issue='DEPTH_UNLIKELY'). However, I imagine
it's more likely that you want to search for occurrences based on a
taxonomic name, or geographic area, not based on issues, so it makes sense
to pull data down, then clean as needed using this function.
This function only affects the
data element in the
gbif class that is
returned from a call to
occ_search(). Maybe in a future version
we will remove the associated records from the
elements as they are remove from the
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## Not run: ## what do issues mean, can print whole table, or search for matches head(gbif_issues()) gbif_issues()[ gbif_issues()$code %in% c('cdround','cudc','gass84','txmathi'), ] # compare out data to after occ_issues use (out <- occ_search(limit=100)) out %>% occ_issues(cudc) # Parsing output by issue (res <- occ_search(geometry='POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))', limit = 50)) ## or parse issues in various ways ### inlude only rows with gass84 issue gg <- res %>% occ_issues(gass84) NROW(res$data) NROW(gg$data) head(res$data)[,c(1:5)] head(gg$data)[,c(1:5)] ### remove data rows with certain issue classes res %>% occ_issues(-cdround, -cudc) ### split issues into separate columns res %>% occ_issues(mutate = "split") res %>% occ_issues(-cudc, -mdatunl, mutate = "split") res %>% occ_issues(gass84, mutate = "split") ### expand issues to more descriptive names res %>% occ_issues(mutate = "expand") ### split and expand res %>% occ_issues(mutate = "split_expand") ### split, expand, and remove an issue class res %>% occ_issues(-cudc, mutate = "split_expand") ## Or you can use occ_issues without %>% occ_issues(res, -cudc, mutate = "split_expand") ## End(Not run)
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