# Modern data ----
`%>%` <- magrittr::`%>%`
## Load data ----
### Metadata ----
other_southern_hemisphere_metadata <-
"data-raw/GLOBAL/other_southern_hemisphere_SPH.xlsx" %>%
readxl::read_excel(sheet = 1) %>%
janitor::clean_names() %>%
dplyr::rename(age_BP = age_bp) %>%
dplyr::mutate(ID_SAMPLE = seq_along(entity_name))
### Polen counts ----
other_southern_hemisphere_counts <-
"data-raw/GLOBAL/other_southern_hemisphere_SPH.xlsx" %>%
readxl::read_excel(sheet = 2, col_names = FALSE) %>%
magrittr::set_names(c(
"entity_name", "taxon_name", "taxon_count"
))
### Amalgamations ----
other_southern_hemisphere_taxa_amalgamation <-
"data-raw/GLOBAL/other_southern_hemisphere_SPH.xlsx" %>%
readxl::read_excel(sheet = 3) %>%
magrittr::set_names(c(
"taxon_name", "clean", "intermediate", "amalgamated"
)) %>%
dplyr::distinct() %>%
dplyr::mutate(clean = clean %>% stringr::str_squish(),
intermediate = intermediate %>% stringr::str_squish(),
amalgamated = amalgamated %>% stringr::str_squish())
### Combine counts and amalgamation ----
other_southern_hemisphere_taxa_counts_amalgamation <-
other_southern_hemisphere_counts %>%
dplyr::left_join(other_southern_hemisphere_taxa_amalgamation,
by = c("taxon_name")) %>%
dplyr::relocate(taxon_count, .after = amalgamated) %>%
dplyr::left_join(other_southern_hemisphere_metadata %>%
dplyr::select(entity_name, ID_SAMPLE),
by = "entity_name") %>%
dplyr::select(-entity_name, -taxon_name) %>%
dplyr::relocate(ID_SAMPLE, .before = 1)
other_southern_hemisphere_taxa_counts_amalgamation %>%
dplyr::filter(is.na(clean) | is.na(intermediate) | is.na(amalgamated))
## Find DOIs ----
other_southern_hemisphere_metadata_pubs <-
other_southern_hemisphere_metadata %>%
dplyr::distinct(publication) %>%
dplyr::arrange(publication) %>%
dplyr::mutate(DOI = publication %>%
stringr::str_extract_all("\\[DOI\\s*(.*?)\\s*\\](;|$)") %>%
purrr::map_chr(~.x %>%
stringr::str_remove_all("^\\[DOI:|\\]$") %>%
stringr::str_squish() %>%
stringr::str_c(collapse = ";\n"))
) %>%
dplyr::mutate(ID_PUB = seq_along(publication))
# other_southern_hemisphere_metadata_pubs %>%
# readr::write_excel_csv("data-raw/GLOBAL/other_southern_hemisphere_modern-references.csv")
### Load cleaned publications list ----
other_southern_hemisphere_clean_publications <-
"data-raw/GLOBAL/other_southern_hemisphere_modern-references_clean.csv" %>%
readr::read_csv() %>%
dplyr::select(-DOI)
# dplyr::mutate(ID_PUB = seq_along(publication))
## Append clean publications ----
other_southern_hemisphere_metadata_2 <-
other_southern_hemisphere_metadata %>%
dplyr::left_join(other_southern_hemisphere_metadata_pubs %>%
dplyr::select(-DOI),
by = "publication") %>%
dplyr::left_join(other_southern_hemisphere_clean_publications,
by = "ID_PUB") %>%
dplyr::select(-publication.x, -publication.y, -doi) %>%
dplyr::rename(doi = updated_DOI,
publication = updated_publication)
## Extract PNV/BIOME ----
other_southern_hemisphere_metadata_3 <-
other_southern_hemisphere_metadata_2 %>%
smpds::parallel_extract_biome(cpus = 12) %>%
# smpds::biome_name() %>%
dplyr::relocate(ID_BIOME, .after = doi) %>%
smpds::pb()
other_southern_hemisphere_metadata_3 %>%
smpds::plot_biome(xlim = range(.$longitude, na.rm = TRUE) * 1.1,
ylim = range(.$latitude, na.rm = TRUE) * 1.1)
## Create count tables ----
### Clean ----
other_southern_hemisphere_clean <-
other_southern_hemisphere_taxa_counts_amalgamation %>%
dplyr::select(-intermediate, -amalgamated) %>%
dplyr::rename(taxon_name = clean) %>%
dplyr::group_by(ID_SAMPLE, taxon_name) %>%
dplyr::mutate(taxon_count = sum(taxon_count, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::distinct() %>%
tidyr::pivot_wider(ID_SAMPLE,
names_from = taxon_name,
values_from = taxon_count,
names_sort = TRUE)
### Intermediate ----
other_southern_hemisphere_intermediate <-
other_southern_hemisphere_taxa_counts_amalgamation %>%
dplyr::select(-clean, -amalgamated) %>%
dplyr::rename(taxon_name = intermediate) %>%
dplyr::group_by(ID_SAMPLE, taxon_name) %>%
dplyr::mutate(taxon_count = sum(taxon_count, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::distinct() %>%
tidyr::pivot_wider(ID_SAMPLE,
names_from = taxon_name,
values_from = taxon_count,
names_sort = TRUE)
### Amalgamated ----
other_southern_hemisphere_amalgamated <-
other_southern_hemisphere_taxa_counts_amalgamation %>%
dplyr::select(-clean, -intermediate) %>%
dplyr::rename(taxon_name = amalgamated) %>%
dplyr::group_by(ID_SAMPLE, taxon_name) %>%
dplyr::mutate(taxon_count = sum(taxon_count, na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::distinct() %>%
tidyr::pivot_wider(ID_SAMPLE,
names_from = taxon_name,
values_from = taxon_count,
names_sort = TRUE)
# Store subsets ----
southern_hemisphere_pollen <-
other_southern_hemisphere_metadata_3 %>%
dplyr::mutate(
clean = other_southern_hemisphere_clean %>%
dplyr::select(-c(ID_SAMPLE)),
intermediate = other_southern_hemisphere_intermediate %>%
dplyr::select(-c(ID_SAMPLE)),
amalgamated = other_southern_hemisphere_amalgamated %>%
dplyr::select(-c(ID_SAMPLE))
) %>%
dplyr::mutate(
basin_size = basin_size %>%
stringr::str_replace_all("unknown", "not known"),
entity_type = entity_type %>%
stringr::str_replace_all("unknown", "not known"),
site_type = site_type %>%
stringr::str_replace_all("unknown", "not known")
) %>%
dplyr::relocate(ID_SAMPLE, .before = clean)
usethis::use_data(southern_hemisphere_pollen, overwrite = TRUE, compress = "xz")
## Inspect enumerates ----
### basin_size -----
southern_hemisphere_pollen$basin_size %>%
unique() %>% sort()
### site_type ----
southern_hemisphere_pollen$site_type %>%
unique() %>% sort()
### entity_type ----
southern_hemisphere_pollen$entity_type %>%
unique() %>% sort()
# Export Excel workbook ----
wb <- openxlsx::createWorkbook()
openxlsx::addWorksheet(wb, "metadata")
openxlsx::writeData(wb, "metadata",
southern_hemisphere_pollen %>%
dplyr::select(site_name:ID_SAMPLE))
openxlsx::addWorksheet(wb, "clean")
openxlsx::writeData(wb, "clean",
southern_hemisphere_pollen %>%
dplyr::select(ID_SAMPLE, clean) %>%
tidyr::unnest(clean))
openxlsx::addWorksheet(wb, "intermediate")
openxlsx::writeData(wb, "intermediate",
southern_hemisphere_pollen %>%
dplyr::select(ID_SAMPLE, intermediate) %>%
tidyr::unnest(intermediate))
openxlsx::addWorksheet(wb, "amalgamated")
openxlsx::writeData(wb, "amalgamated",
southern_hemisphere_pollen %>%
dplyr::select(ID_SAMPLE, amalgamated) %>%
tidyr::unnest(amalgamated))
openxlsx::saveWorkbook(wb,
paste0("data-raw/GLOBAL/southern_hemisphere_pollen_",
Sys.Date(),
".xlsx"))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.