Because the bdc::bdc_country_from_coordinates() function is very RAM-intensive, this wrapper
allows a user to specify chunk-sizes and only analyse a small portion of the occurrence data at a
time. The prefix jbd_ is used to highlight the difference between this function and the original
bdc::bdc_country_from_coordinates().
jbd_CfC_chunker(
data = NULL,
lat = "decimalLatitude",
lon = "decimalLongitude",
country = "country",
stepSize = 1e+06,
chunkStart = 1,
scale = "medium",
path = tempdir(),
mc.cores = 1
)A data frame or tibble. Occurrence records to use as input.
Character. The name of the column to use as latitude. Default = "decimalLatitude".
Character. The name of the column to use as longitude. Default = "decimalLongitude".
Character. The name of the column containing country names. Default = "country.
Numeric. The number of occurrences to process in each chunk. Default = 1000000.
Numeric. The chunk number to start from. This can be > 1 when you need to restart the function from a certain chunk. For example, can be used if R failed unexpectedly.
Passed to rnaturalearth's ne_countries(). Scale of map to return, one of 110, 50, 10 or 'small', 'medium', 'large'. Default = "large".
Character. The directory path to a folder in which to save the running countrylist csv file.
Numeric. If > 1, the function will run in parallel using mclapply using the number of cores specified. If = 1 then it will be run using a serial loop. NOTE: Windows machines must use a value of 1 (see ?parallel::mclapply). Additionally, be aware that each thread can use large chunks of memory. Default = 1.
A data frame containing database_ids and a country column that needs to be re-merged with the data input.
if(requireNamespace("rnaturalearthdata")){
library("dplyr")
data(beesFlagged)
HomePath = tempdir()
# Tibble of common issues in country names and their replacements
commonProblems <- dplyr::tibble(problem = c('U.S.A.', 'US','USA','usa','UNITED STATES',
'United States','U.S.A','MX','CA','Bras.','Braz.','Brasil','CNMI','USA TERRITORY: PUERTO RICO'),
fix = c('United States of America','United States of America',
'United States of America','United States of America',
'United States of America','United States of America',
'United States of America','Mexico','Canada','Brazil','Brazil',
'Brazil','Northern Mariana Islands','Puerto Rico'))
beesFlagged <- beesFlagged %>%
# Replace a name to test
dplyr::mutate(country = stringr::str_replace_all(country, "Brazil", "Brasil"))
beesFlagged_out <- countryNameCleanR(
data = beesFlagged,
commonProblems = commonProblems)
suppressWarnings(
countryOutput <- jbd_CfC_chunker(data = beesFlagged_out,
lat = "decimalLatitude",
lon = "decimalLongitude",
country = "country",
# How many rows to process at a time
stepSize = 1000000,
# Start row
chunkStart = 1,
path = HomePath,
scale = "medium"),
classes = "warning")
# Left join these datasets
beesFlagged_out <- left_join(beesFlagged_out, countryOutput, by = "database_id") %>%
# merge the two country name columns into the "country" column
dplyr::mutate(country = dplyr::coalesce(country.x, country.y)) %>%
# remove the now redundant country columns
dplyr::select(!c(country.x, country.y)) %>%
# put the column back
dplyr::relocate(country) %>%
# Remove duplicates if they arose!
dplyr::distinct()
# Remove illegal characters
beesFlagged_out$country <- beesFlagged_out$country %>%
stringr::str_replace(., pattern = paste("\\[", "\\]", "\\?",
sep= "|"), replacement = "")
} # END if require
#> - Using default country names and codes from https:en.wikipedia.org/wiki/ISO_3166-1_alpha-2 - static version from July 2022.
#> - Running chunker with:
#> stepSize = 1,000,000
#> chunkStart = 1
#> chunkEnd = 1,000,000
#> - Starting parallel operation. Unlike the serial operation (mc.cores = 1) , a parallel operation will not provide running feedback. Please be patient as this function may take some time to complete. Each chunk will be run on a seperate thread so also be aware of RAM usage.
#> Loading required package: rnaturalearth
#> - Completed in 0.36 secs
#> - We have updated the country names of 5 occurrences that previously had no country name assigned.