## 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")
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