inst/extdata/respecExistingGeom.R
In sjbeckett/subregionalcovid19: Processing and mapping COVID-19 case data at subnational scales
source("librariesMinimal.R")
library(readr)
# Fields will be as follows:
## GEOID = ISO3m49_micro_macro
## m49code
## iso3
## county_name
## macro_code
## macro_name
## micro_code
## micro_name
## geometry
respecEnv <- new.env()
## Load in the m49 codes for countries
m49 <- readxl::read_xlsx("updateGeometry/UNSD_m49.xlsx")
m49 <- m49 %>%
rename_with(
.fn = \(x) str_replace_all(x, "[\\s/-]", "")
)
# Afghanistan
respecEnv$geomAfghanistan <- sf::st_read("countries/data/orig_geom/geomAfghanistan.geojson")
respecEnv$geomAfghanistan <- respecEnv$geomAfghanistan %>%
dplyr::mutate(
country_name = "Afghanistan",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = id,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Algeria
respecEnv$geomAlgeria <- sf::st_read("countries/data/orig_geom/geomAlgeria.geojson")
respecEnv$geomAlgeria <- respecEnv$geomAlgeria %>%
dplyr::mutate(
country_name = "Algeria",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ID,
micro_name = NAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Argentina
respecEnv$geomArgentina <- sf::st_read("countries/data/orig_geom/geomArgentina.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscArgentina.csv")) {
respecEnv$geomArgentina %>%
st_drop_geometry() %>%
write_csv("countries/data/miscArgentina.csv")
cat("\nmiscArgentina.csv Created\n")
}else{
cat("\nmiscArgentina.csv Already Exists\n")
}
respecEnv$geomArgentina <- respecEnv$geomArgentina %>%
dplyr::mutate(
country_name = "Argentina",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ID_1,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Australia
respecEnv$geomAustralia <- sf::st_read("countries/data/orig_geom/geomAustralia.geojson")
respecEnv$geomAustralia <- respecEnv$geomAustralia %>%
dplyr::mutate(
country_name = "Australia",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = STATE_CODE,
micro_name = STATE_NAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Austria
respecEnv$geomAustria <- sf::st_read("countries/data/orig_geom/geomAustria.geojson")
respecEnv$geomAustria <- respecEnv$geomAustria %>%
mutate(
country_name = "Austria",
) %>%
left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = iso,
micro_name = name
) %>%
mutate(across(.cols = ends_with("code"), .fns = as.character))
# Belgium
respecEnv$geomBelgium <- sf::st_read("countries/data/orig_geom/geomBelgium.geojson")
respecEnv$geomBelgium <- respecEnv$geomBelgium %>%
dplyr::mutate(
country_name = "Belgium",
micro_code = row_number() # I'm assigning IDs based on row number, but we could go back and do country subdivision ISOs
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NameDUT
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Brazil
respecEnv$geomBrazil <- sf::st_read("countries/data/orig_geom/geomBrazil.geojson")
respecEnv$geomBrazil <- respecEnv$geomBrazil %>%
dplyr::mutate(
country_name = "Brazil"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = regiao_id,
micro_code = sigla,
micro_name = nome
) %>%
sf::st_make_valid() %>% # Brazil has some invalidity
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Canada
respecEnv$geomCanada <- sf::st_read("countries/data/orig_geom/geomCanada.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscCanada.csv")) {
respecEnv$geomCanada %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscCanada.csv")
cat("\nmiscCanada.csv Created\n")
}else{
cat("\nmiscCanada.csv Already Exists\n")
}
respecEnv$geomCanada <- respecEnv$geomCanada %>%
dplyr::mutate(
country_name = "Canada"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = Province,
micro_code = HR_UID,
micro_name = ENGNAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Make canada valid
respecEnv$geomCanada <- respecEnv$geomCanada %>%
sf::st_transform(3347) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Chile
respecEnv$geomChile <- sf::st_read("countries/data/orig_geom/geomChile.geojson")
if (!file.exists("countries/data/miscChile.csv")) {
respecEnv$geomChile %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscChile.csv")
cat("\nmiscChile.csv Created\n")
}else{
cat("\nmiscChile.csv Already Exists\n")
}
respecEnv$geomChile <- respecEnv$geomChile %>%
dplyr::mutate(
country_name = "Chile"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = codregion,
micro_name = matchName
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Make Chile valid
respecEnv$geomChile <- respecEnv$geomChile %>%
sf::st_transform("+proj=utm +zone=23 +south +ellps=aust_SA +units=m +no_defs") %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# China
respecEnv$geomChina <- sf::st_read("countries/data/orig_geom/geomChina.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscChina.csv")) {
respecEnv$geomChina %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscChina.csv")
cat("\nmiscChina.csv Created\n")
}else{
cat("\nmiscChina.csv Already Exists\n")
}
respecEnv$geomChina <- respecEnv$geomChina %>%
dplyr::mutate(
country_name = "China"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ISO,
micro_name = NAME_1
) %>%
dplyr::filter(micro_code != "CN-71") %>% # Remove Taiwan because we have higher resolution in geomTaiwan
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Colombia
respecEnv$geomColombia <- sf::st_read("countries/data/orig_geom/geomColombia.geojson")
respecEnv$geomColombia <- respecEnv$geomColombia %>%
dplyr::mutate(
country_name = "Colombia",
NOMBRE_DPT = str_to_title(NOMBRE_DPT)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = DPTO,
micro_name = NOMBRE_DPT
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Cuba
respecEnv$geomCuba <- sf::st_read("countries/data/orig_geom/geomCuba.geojson")
respecEnv$geomCuba <- respecEnv$geomCuba %>%
dplyr::mutate(
country_name = "Cuba",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = province_id,
micro_name = province
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
dplyr::filter(micro_code != "unk")
## Make Cuba valid
respecEnv$geomCuba <- respecEnv$geomCuba %>%
sf::st_transform(32617) %>%
sf::st_make_valid() %>%
sf::st_transform(4326) %>%
sf::st_make_valid()
# Czechia
respecEnv$geomCzechia <- sf::st_read("countries/data/orig_geom/geomCzechia.geojson")
namesCzechia <- vroom::vroom("countries/data/czech_pop.csv") %>%
dplyr::select(-Population)
## Load codes for Local Admin Units (LAU)
respecEnv$geomCzechia <- respecEnv$geomCzechia %>%
dplyr::full_join(namesCzechia, by = c("name" = "District")) %>%
dplyr::mutate(
country_name = "Czechia",
macro_code = str_sub(Code, 1, 5) # NUTS 3 level code
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code,
micro_code = Code,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(namesCzechia)
# Denmark
respecEnv$geomDenmark <- sf::st_read("countries/data/orig_geom/geomDenmark.geojson")
respecEnv$geomDenmark <- respecEnv$geomDenmark %>%
sf::st_zm() %>%
dplyr::group_by(name) %>%
dplyr::summarise() %>%
sf::st_cast("MULTIPOLYGON") %>%
mutate(
country_name = "Denmark",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Europe
respecEnv$geomEurope <- sf::st_read("countries/data/orig_geom/geomEurope.geojson")
namesEurope <- vroom::vroom("countries/data/namesEurope.csv")
respecEnv$geomEurope <- respecEnv$geomEurope %>%
dplyr::inner_join(namesEurope, by = "UID") %>%
dplyr::mutate(CountryName = case_when(
CountryName == "Moldova" ~ "Republic of Moldova",
CountryName == "Russian Fed." ~ "Russian Federation",
CountryName == "United Kingdom" ~ "United Kingdom of Great Britain and Northern Ireland",
TRUE ~ CountryName
)) %>%
dplyr::left_join(
m49,
by = c("CountryName" = "CountryorArea")
) %>%
dplyr::mutate(
CountryName = dplyr::case_when(
CountryName == "Republic of Moldova" ~ "Moldova",
CountryName == "United Kingdom of Great Britain and Northern Ireland" ~ "United Kingdom",
CountryName == "Russian Federation" ~ "Russia",
TRUE ~ CountryName
)
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name = CountryName,
micro_code = UID,
micro_name = Region
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Europe valid
respecEnv$geomEurope <- respecEnv$geomEurope %>%
sf::st_transform("+proj=lcc +lat_1=43 +lat_2=62 +lat_0=30 +lon_0=10 +x_0=0 +y_0=0 +ellps=intl +units=m +no_defs") %>% # ESRI 102014: Europe Lambert Conformal Conic
sf::st_make_valid() %>%
sf::st_transform(4326)
rm(namesEurope)
# France
respecEnv$geomFrance <- sf::st_read("countries/data/orig_geom/geomFrance.geojson")
respecEnv$geomFrance <- respecEnv$geomFrance %>%
dplyr::mutate(
country_name = "France"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = code,
micro_name = nom
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Germany
respecEnv$geomGermany <- sf::st_read("countries/data/orig_geom/geomGermany.geojson")
respecEnv$geomGermany <- respecEnv$geomGermany %>%
dplyr::mutate(
country_name = "Germany",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = county
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# India
respecEnv$geomIndia <- sf::st_read("countries/data/orig_geom/geomIndia.geojson")
respecEnv$geomIndia <- respecEnv$geomIndia %>%
dplyr::group_by(NAME_1) %>% # Merge the two Dadra... so they only take up one entry
dplyr::summarise() %>%
sf::st_cast("MULTIPOLYGON") %>%
dplyr::mutate(
country_name = "India",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Indonesia
respecEnv$geomIndonesia <- sf::st_read("countries/data/orig_geom/geomIndonesia.geojson")
respecEnv$geomIndonesia <- respecEnv$geomIndonesia %>%
dplyr::mutate(
country_name = "Indonesia",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Ireland
respecEnv$geomIreland <- sf::st_read("countries/data/orig_geom/geomIreland.geojson")
provIreland <- respecEnv$geomIreland %>%
dplyr::group_by(PROVINCE) %>%
dplyr::group_keys() %>%
tibble::rowid_to_column("macro_code")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscIreland.csv")) {
respecEnv$geomIreland %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscIreland.csv")
cat("\nmiscIreland.csv Created\n")
}else{
cat("\nmiscIreland.csv Already Exists\n")
}
respecEnv$geomIreland <- respecEnv$geomIreland %>%
dplyr::mutate(
country_name = "Ireland"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::left_join(provIreland) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code,
macro_name = PROVINCE,
micro_code = CO_ID,
micro_name = id
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Ireland valid
respecEnv$geomIreland <- respecEnv$geomIreland %>%
sf::st_transform(23029) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
rm(provIreland)
# Italy
respecEnv$geomItaly <- sf::st_read("countries/data/orig_geom/geomItaly.geojson")
respecEnv$geomItaly <- respecEnv$geomItaly %>%
dplyr::mutate(
country_name = "Italy"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = reg_istat_code,
macro_name = reg_name,
micro_code = prov_istat_code,
micro_name = prov_name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Japan
respecEnv$geomJapan <- sf::st_read("countries/data/orig_geom/geomJapan.geojson")
respecEnv$geomJapan <- respecEnv$geomJapan %>%
dplyr::mutate(
country_name = "Japan",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Japan valid
respecEnv$geomJapan <- respecEnv$geomJapan %>%
sf::st_transform(3100) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Malaysia
respecEnv$geomMalaysia <- sf::st_read("countries/data/orig_geom/geomMalaysia.geojson")
respecEnv$geomMalaysia <- respecEnv$geomMalaysia %>%
dplyr::mutate(
country_name = "Malaysia"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = id,
micro_name = Name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Mexico
respecEnv$geomMexico <- sf::st_read("countries/data/orig_geom/geomMexico.geojson")
respecEnv$geomMexico <- respecEnv$geomMexico %>%
dplyr::mutate(
country_name = "Mexico",
macro_code = str_sub(CVEGEO, 1, 2)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code,
macro_name = estado,
micro_code = CVEGEO,
micro_name = NOMGEO
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Mexico valid
respecEnv$geomMexico <- respecEnv$geomMexico %>%
sf::st_transform(6372) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Mozambique
respecEnv$geomMozambique <- sf::st_read("countries/data/orig_geom/geomMozambique.geojson")
respecEnv$geomMozambique <- respecEnv$geomMozambique %>%
dplyr::mutate(
country_name = "Mozambique"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ID_1,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Netherlands
respecEnv$geomNetherlands <- sf::st_read("countries/data/orig_geom/geomNetherlands.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscNetherlands.csv")) {
respecEnv$geomNetherlands %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscNetherlands.csv")
cat("\nmiscNetherlands.csv Created\n")
}else{
cat("\nmiscNetherlands.csv Already Exists\n")
}
respecEnv$geomNetherlands <- respecEnv$geomNetherlands %>%
dplyr::mutate(
country_name = "Netherlands"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = Provinciecode,
macro_name = Provincie,
micro_code = Gemeentecode,
micro_name = Gemeentenaam
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Nigeria
respecEnv$geomNigeria <- sf::st_read("countries/data/orig_geom/geomNigeria.geojson")
respecEnv$geomNigeria <- respecEnv$geomNigeria %>%
dplyr::mutate(
country_name = "Nigeria"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = admin1Pcod,
micro_name = admin1Name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Norway
respecEnv$geomNorway <- sf::st_read("countries/data/orig_geom/geomNorway.geojson")
## this geometry is missing Svalbard and Ukjent, but they also don't have population in the dataset
norw_kommune <- vroom::vroom("https://raw.githubusercontent.com/thohan88/covid19-nor-data/master/data/01_infected/msis/municipality.csv") %>%
dplyr::select(kommune_no, kommune_name, fylke_no, fylke_name) %>%
dplyr::distinct()
respecEnv$geomNorway <- respecEnv$geomNorway %>%
dplyr::group_by(kommunenummer) %>%
dplyr::summarise() %>%
sf::st_cast("MULTIPOLYGON") %>%
dplyr::mutate(
country_name = "Norway",
kommune_no = str_pad(kommunenummer, pad = "0", side = "left", width = 4)
) %>%
dplyr::left_join(
norw_kommune
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = fylke_no,
macro_name = fylke_name,
micro_code = kommune_no,
micro_name = kommune_name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(norw_kommune)
# NZ
respecEnv$geomNZ <- sf::st_read("countries/data/orig_geom/geomNZ.geojson")
respecEnv$geomNZ <- respecEnv$geomNZ %>%
dplyr::mutate(
country_name = "New Zealand"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = DHB2015_Co,
micro_name = DHB2015_Na
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Peru
respecEnv$geomPeru <- sf::st_read("countries/data/orig_geom/geomPeru.geojson")
respecEnv$geomPeru <- respecEnv$geomPeru %>%
dplyr::mutate(
country_name = "Peru",
NOMBDEP = str_replace_all(
str_to_title(NOMBDEP),
"\\sDe\\s",
" de "
)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = FIRST_IDDP,
micro_name = NOMBDEP
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Philippines
respecEnv$geomPhilippines <- sf::st_read("countries/data/orig_geom/geomPhilippines.geojson")
namesPhilippines <- vroom::vroom("countries/data/namesPhilippines.csv") %>%
dplyr::select(starts_with("ADM2"), starts_with("ADM1")) %>%
dplyr::distinct()
respecEnv$geomPhilippines <- respecEnv$geomPhilippines %>%
dplyr::mutate(
country_name = "Philippines"
) %>%
dplyr::left_join(namesPhilippines) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = ADM1_PCODE,
macro_name = ADM1_EN,
micro_code = ADM2_PCODE,
micro_name = ADM2_EN
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(namesPhilippines)
# SaudiArabia
respecEnv$geomSaudiArabia <- sf::st_read("countries/data/orig_geom/geomSaudiArabia.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscSaudiArabia.csv")) {
geomSaudiArabia %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscSaudiArabia.csv")
cat("\nmiscSaudiArabia.csv Created\n")
}else{
cat("\nmiscSaudiArabia.csv Already Exists\n")
}
respecEnv$geomSaudiArabia <- respecEnv$geomSaudiArabia %>%
dplyr::mutate(
country_name = "Saudi Arabia"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = REG_CODE,
micro_name = region_name_en
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
sf::st_make_valid() # Make Saudi Arabia valid
# SouthAfrica
respecEnv$geomSouthAfrica <- sf::st_read("countries/data/orig_geom/geomSouthAfrica.geojson")
respecEnv$geomSouthAfrica <- respecEnv$geomSouthAfrica %>%
dplyr::mutate(
country_name = "South Africa"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = PROVINCE
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Spain
respecEnv$geomSpain <- sf::st_read("countries/data/orig_geom/geomSpain.geojson")
namesSpain <- vroom::vroom("countries/data/namesSpain.csv") %>%
dplyr::mutate(cod_ccaa = stringr::str_pad(Code, width = 2, side = "left", pad = "0"))
respecEnv$geomSpain <- respecEnv$geomSpain %>%
dplyr::mutate(
country_name = "Spain"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::left_join(namesSpain) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = cod_ccaa,
macro_name = Region,
micro_code = cod_prov,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
sf::st_make_valid() # Make Spain valid
rm(namesSpain)
# Sweden
respecEnv$geomSweden <- sf::st_read("countries/data/orig_geom/geomSweden.geojson")
respecEnv$geomSweden <- respecEnv$geomSweden %>%
dplyr::mutate(
country_name = "Sweden"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = cartodb_id,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# SwitzerlandLiechtenstein
respecEnv$geomSwitzerlandLiechtenstein <- sf::st_read("countries/data/orig_geom/geomSwitzerlandLiechtenstein.geojson")
respecEnv$geomSwitzerlandLiechtenstein <- respecEnv$geomSwitzerlandLiechtenstein %>%
dplyr::mutate(
country_name = case_when(
name == "Liechtenstein" ~ "Liechtenstein",
TRUE ~ "Switzerland"
)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = id,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Switzerland and Liechtenstein valid
respecEnv$geomSwitzerlandLiechtenstein <- respecEnv$geomSwitzerlandLiechtenstein %>%
sf::st_transform(21781) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Taiwan"
respecEnv$geomTaiwan <- sf::st_read("countries/data/orig_geom/geomTaiwan.geojson")
respecEnv$geomTaiwan <- respecEnv$geomTaiwan %>%
dplyr::mutate(
country_name = "Taiwan",
m49code = 158, # Using ISO3166 code bc Taiwan is not in the M49 list
iso3 = "TWN"
) %>%
dplyr::select(
m49code,
iso3,
country_name,
micro_code = COUNTYSN,
micro_name = COUNTYNAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
dplyr::filter(!micro_code %in% c("10011001", "10006003"))
# Thailand"
respecEnv$geomThailand <- sf::st_read("countries/data/orig_geom/geomThailand.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscThailand.csv")) {
respecEnv$geomThailand %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscThailand.csv")
cat("\nmiscThailand.csv Created\n")
}else{
cat("\nmiscThailand.csv Already Exists\n")
}
respecEnv$geomThailand <- respecEnv$geomThailand %>%
dplyr::mutate(
country_name = "Thailand"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_name = reg_nesdb,
micro_code = pro_code,
micro_name = pro_en
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# UnitedKingdom"
respecEnv$geomUnitedKingdom <- sf::st_read("countries/data/orig_geom/geomUnitedKingdom.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscUK.csv")) {
respecEnv$geomUnitedKingdom %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscUK.csv")
cat("\nmiscUK.csv Created\n")
}else{
cat("\nmiscUK.csv Already Exists\n")
}
respecEnv$geomUnitedKingdom <- respecEnv$geomUnitedKingdom %>%
dplyr::mutate(
country_name = "United Kingdom",
m49code = m49$M49Code[which(m49$CountryorArea == "United Kingdom of Great Britain and Northern Ireland")],
iso3 = m49$ISOalpha3Code[which(m49$CountryorArea == "United Kingdom of Great Britain and Northern Ireland")]
) %>%
dplyr::select(
m49code,
iso3,
country_name,
micro_code = code,
micro_name = name
) %>%
dplyr::mutate(across(.cols = dplyr::ends_with("code"), .fns = as.character))
# UnitedStates"
respecEnv$geomUnitedStates <- sf::st_read("countries/data/orig_geom/geomUnitedStates.geojson")
usStatelines <- sf::st_read("countries/data/orig_geom/US_stateLines.geojson") %>%
st_drop_geometry()
respecEnv$geomUnitedStates <- respecEnv$geomUnitedStates %>%
dplyr::mutate(
country_name = "United States",
m49code = m49$M49Code[which(m49$CountryorArea == "United States of America")],
iso3 = m49$ISOalpha3Code[which(m49$CountryorArea == "United States of America")]
) %>%
dplyr::inner_join(usStatelines, by = c("stname" = "STUSPS")) %>%
dplyr::select(
m49code,
iso3,
country_name,
macro_code = stname,
macro_name = NAME.y,
micro_code = GEOID.x,
micro_name = NAME.x
) %>%
dplyr::mutate(across(.cols = dplyr::ends_with("code"), .fns = as.character))
respecEnv$geomAK <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "AK") %>%
sf::st_transform(3467) %>%
dplyr::group_by(m49code, iso3, country_name, macro_code, macro_name, micro_code, micro_name) %>%
dplyr::summarise() %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
respecEnv$geomCO <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "CO") %>%
sf::st_transform(2773) %>%
dplyr::group_by(m49code, iso3, country_name, macro_code, macro_name, micro_code, micro_name) %>%
dplyr::summarise() %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
respecEnv$geomID <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "ID") %>%
sf::st_transform(2788) %>%
dplyr::group_by(m49code, iso3, country_name, macro_code, macro_name, micro_code, micro_name) %>%
dplyr::summarise() %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
respecEnv$geomKS <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "KS") %>%
sf::st_make_valid()
respecEnv$geomUnitedStates <- respecEnv$geomUnitedStates %>%
dplyr::filter(!macro_code %in% c("AK", "CO", "ID", "KS")) %>%
dplyr::bind_rows(respecEnv$geomAK, respecEnv$geomCO, respecEnv$geomID, respecEnv$geomKS)
rm(list = c("geomAK", "geomCO", "geomID", "geomKS"), envir = respecEnv)
rm(usStatelines)
# Venezuela"
respecEnv$geomVenezuela <- sf::st_read("countries/data/orig_geom/geomVenezuela.geojson")
respecEnv$geomVenezuela <- respecEnv$geomVenezuela %>%
dplyr::mutate(
country_name = "Venezuela",
m49code = m49$M49Code[which(m49$CountryorArea == "Venezuela (Bolivarian Republic of)")],
iso3 = m49$ISOalpha3Code[which(m49$CountryorArea == "Venezuela (Bolivarian Republic of)")]
) %>%
dplyr::select(
m49code,
iso3,
country_name,
micro_code = ID_1,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = dplyr::ends_with("code"), .fns = as.character))
## Make Venezuela valid
respecEnv$geomVenezuela <- respecEnv$geomVenezuela %>%
sf::st_transform(2201) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Small Countries
respecEnv$geomSmallCountries <- sf::st_read("countries/data/orig_geom/WB_countries_Admin0_lowres.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/popSmallCountries.csv")) {
respecEnv$geomSmallCountries %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/popSmallCountries.csv")
cat("\npopSmallCountries.csv Created\n")
}else{
cat("\npopSmallCountries.csv Already Exists\n")
}
respecEnv$geomSmallCountries <- respecEnv$geomSmallCountries %>%
dplyr::left_join(m49, by = c("ISO_A3" = "ISOalpha3Code")) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISO_A3,
country_name = NAME_EN
)
respecEnv$geomFiji <- respecEnv$geomSmallCountries %>%
dplyr::filter(iso3 == "FJI") %>% # Fiji
sf::st_cast("POLYGON") %>%
sf::st_wrap_dateline() %>%
dplyr::group_by(m49code, iso3, country_name) %>%
dplyr::summarise() %>%
dplyr::ungroup()
respecEnv$geomSmallCountries <- respecEnv$geomSmallCountries[which(sf::st_is_valid(respecEnv$geomSmallCountries, reason = T) == "Valid Geometry"), ] %>% # Russia, USA, and Japan are accounted for in other data sets, so we can afford to loose them
dplyr::bind_rows(respecEnv$geomFiji) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(geomFiji, envir = respecEnv)
# Tidy up and finish
## the respecEnv has all the country geoms *and only the country geoms*
geom_list <- ls(respecEnv)
geomWorld <- purrr::map_df(
geom_list, # For each geometry file...
~ get(.x, envir = respecEnv) %>%
dplyr::mutate(
filename = .x # Add a column with the filename...
) %>%
{ if(st_geometry_type(., FALSE) %in% c("GEOMETRY", "GEOMETRYCOLLECTION")){
sf::st_collection_extract(.) # If geometry type "geometry" or "geometrycollection," cast back to polygon...
}else{.}
} %>%
sf::st_cast("MULTIPOLYGON") # Cast everything to Multipolygon so they are all the same type
) %>%
replace_na(list("macro_code" = "00")) %>% # Replace NAs in macro_code with "00"
dplyr::mutate( # Create GEOIDs
geoid = paste(paste0(iso3, m49code), macro_code, micro_code, sep = "_")
) %>%
dplyr::select(geoid, m49code, iso3, country_name, macro_code, macro_name, everything()) %>%
sf::st_as_sf() %>%
tibble::remove_rownames()
## Write presimplified geometry
sf::st_write(geomWorld, "geomWorld_presimp.geojson", delete_dsn = T)
rm(respecEnv) ## delete environment with individual geometries
## Zip presimplified geometry
nowtime <- round(difftime(now(tzone = "UTC"), ymd_hms("1970-01-01 00:00:00"), tz = "UTC", units = "mins"))
utils::zip(zipfile = paste0("updateGeometry/WorldPreSimplified/WorldPreSimp", nowtime, ".zip"), "geomWorld_presimp.geojson")
file.remove("geomWorld_presimp.geojson")
rm(m49)
rm(geom_list)
sjbeckett/subregionalcovid19 documentation built on Feb. 7, 2023, 6 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
source("librariesMinimal.R")
library(readr)
# Fields will be as follows:
## GEOID = ISO3m49_micro_macro
## m49code
## iso3
## county_name
## macro_code
## macro_name
## micro_code
## micro_name
## geometry
respecEnv <- new.env()
## Load in the m49 codes for countries
m49 <- readxl::read_xlsx("updateGeometry/UNSD_m49.xlsx")
m49 <- m49 %>%
rename_with(
.fn = \(x) str_replace_all(x, "[\\s/-]", "")
)
# Afghanistan
respecEnv$geomAfghanistan <- sf::st_read("countries/data/orig_geom/geomAfghanistan.geojson")
respecEnv$geomAfghanistan <- respecEnv$geomAfghanistan %>%
dplyr::mutate(
country_name = "Afghanistan",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = id,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Algeria
respecEnv$geomAlgeria <- sf::st_read("countries/data/orig_geom/geomAlgeria.geojson")
respecEnv$geomAlgeria <- respecEnv$geomAlgeria %>%
dplyr::mutate(
country_name = "Algeria",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ID,
micro_name = NAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Argentina
respecEnv$geomArgentina <- sf::st_read("countries/data/orig_geom/geomArgentina.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscArgentina.csv")) {
respecEnv$geomArgentina %>%
st_drop_geometry() %>%
write_csv("countries/data/miscArgentina.csv")
cat("\nmiscArgentina.csv Created\n")
}else{
cat("\nmiscArgentina.csv Already Exists\n")
}
respecEnv$geomArgentina <- respecEnv$geomArgentina %>%
dplyr::mutate(
country_name = "Argentina",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ID_1,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Australia
respecEnv$geomAustralia <- sf::st_read("countries/data/orig_geom/geomAustralia.geojson")
respecEnv$geomAustralia <- respecEnv$geomAustralia %>%
dplyr::mutate(
country_name = "Australia",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = STATE_CODE,
micro_name = STATE_NAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Austria
respecEnv$geomAustria <- sf::st_read("countries/data/orig_geom/geomAustria.geojson")
respecEnv$geomAustria <- respecEnv$geomAustria %>%
mutate(
country_name = "Austria",
) %>%
left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = iso,
micro_name = name
) %>%
mutate(across(.cols = ends_with("code"), .fns = as.character))
# Belgium
respecEnv$geomBelgium <- sf::st_read("countries/data/orig_geom/geomBelgium.geojson")
respecEnv$geomBelgium <- respecEnv$geomBelgium %>%
dplyr::mutate(
country_name = "Belgium",
micro_code = row_number() # I'm assigning IDs based on row number, but we could go back and do country subdivision ISOs
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NameDUT
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Brazil
respecEnv$geomBrazil <- sf::st_read("countries/data/orig_geom/geomBrazil.geojson")
respecEnv$geomBrazil <- respecEnv$geomBrazil %>%
dplyr::mutate(
country_name = "Brazil"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = regiao_id,
micro_code = sigla,
micro_name = nome
) %>%
sf::st_make_valid() %>% # Brazil has some invalidity
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Canada
respecEnv$geomCanada <- sf::st_read("countries/data/orig_geom/geomCanada.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscCanada.csv")) {
respecEnv$geomCanada %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscCanada.csv")
cat("\nmiscCanada.csv Created\n")
}else{
cat("\nmiscCanada.csv Already Exists\n")
}
respecEnv$geomCanada <- respecEnv$geomCanada %>%
dplyr::mutate(
country_name = "Canada"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = Province,
micro_code = HR_UID,
micro_name = ENGNAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Make canada valid
respecEnv$geomCanada <- respecEnv$geomCanada %>%
sf::st_transform(3347) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Chile
respecEnv$geomChile <- sf::st_read("countries/data/orig_geom/geomChile.geojson")
if (!file.exists("countries/data/miscChile.csv")) {
respecEnv$geomChile %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscChile.csv")
cat("\nmiscChile.csv Created\n")
}else{
cat("\nmiscChile.csv Already Exists\n")
}
respecEnv$geomChile <- respecEnv$geomChile %>%
dplyr::mutate(
country_name = "Chile"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = codregion,
micro_name = matchName
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Make Chile valid
respecEnv$geomChile <- respecEnv$geomChile %>%
sf::st_transform("+proj=utm +zone=23 +south +ellps=aust_SA +units=m +no_defs") %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# China
respecEnv$geomChina <- sf::st_read("countries/data/orig_geom/geomChina.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscChina.csv")) {
respecEnv$geomChina %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscChina.csv")
cat("\nmiscChina.csv Created\n")
}else{
cat("\nmiscChina.csv Already Exists\n")
}
respecEnv$geomChina <- respecEnv$geomChina %>%
dplyr::mutate(
country_name = "China"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ISO,
micro_name = NAME_1
) %>%
dplyr::filter(micro_code != "CN-71") %>% # Remove Taiwan because we have higher resolution in geomTaiwan
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Colombia
respecEnv$geomColombia <- sf::st_read("countries/data/orig_geom/geomColombia.geojson")
respecEnv$geomColombia <- respecEnv$geomColombia %>%
dplyr::mutate(
country_name = "Colombia",
NOMBRE_DPT = str_to_title(NOMBRE_DPT)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = DPTO,
micro_name = NOMBRE_DPT
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Cuba
respecEnv$geomCuba <- sf::st_read("countries/data/orig_geom/geomCuba.geojson")
respecEnv$geomCuba <- respecEnv$geomCuba %>%
dplyr::mutate(
country_name = "Cuba",
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = province_id,
micro_name = province
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
dplyr::filter(micro_code != "unk")
## Make Cuba valid
respecEnv$geomCuba <- respecEnv$geomCuba %>%
sf::st_transform(32617) %>%
sf::st_make_valid() %>%
sf::st_transform(4326) %>%
sf::st_make_valid()
# Czechia
respecEnv$geomCzechia <- sf::st_read("countries/data/orig_geom/geomCzechia.geojson")
namesCzechia <- vroom::vroom("countries/data/czech_pop.csv") %>%
dplyr::select(-Population)
## Load codes for Local Admin Units (LAU)
respecEnv$geomCzechia <- respecEnv$geomCzechia %>%
dplyr::full_join(namesCzechia, by = c("name" = "District")) %>%
dplyr::mutate(
country_name = "Czechia",
macro_code = str_sub(Code, 1, 5) # NUTS 3 level code
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code,
micro_code = Code,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(namesCzechia)
# Denmark
respecEnv$geomDenmark <- sf::st_read("countries/data/orig_geom/geomDenmark.geojson")
respecEnv$geomDenmark <- respecEnv$geomDenmark %>%
sf::st_zm() %>%
dplyr::group_by(name) %>%
dplyr::summarise() %>%
sf::st_cast("MULTIPOLYGON") %>%
mutate(
country_name = "Denmark",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Europe
respecEnv$geomEurope <- sf::st_read("countries/data/orig_geom/geomEurope.geojson")
namesEurope <- vroom::vroom("countries/data/namesEurope.csv")
respecEnv$geomEurope <- respecEnv$geomEurope %>%
dplyr::inner_join(namesEurope, by = "UID") %>%
dplyr::mutate(CountryName = case_when(
CountryName == "Moldova" ~ "Republic of Moldova",
CountryName == "Russian Fed." ~ "Russian Federation",
CountryName == "United Kingdom" ~ "United Kingdom of Great Britain and Northern Ireland",
TRUE ~ CountryName
)) %>%
dplyr::left_join(
m49,
by = c("CountryName" = "CountryorArea")
) %>%
dplyr::mutate(
CountryName = dplyr::case_when(
CountryName == "Republic of Moldova" ~ "Moldova",
CountryName == "United Kingdom of Great Britain and Northern Ireland" ~ "United Kingdom",
CountryName == "Russian Federation" ~ "Russia",
TRUE ~ CountryName
)
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name = CountryName,
micro_code = UID,
micro_name = Region
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Europe valid
respecEnv$geomEurope <- respecEnv$geomEurope %>%
sf::st_transform("+proj=lcc +lat_1=43 +lat_2=62 +lat_0=30 +lon_0=10 +x_0=0 +y_0=0 +ellps=intl +units=m +no_defs") %>% # ESRI 102014: Europe Lambert Conformal Conic
sf::st_make_valid() %>%
sf::st_transform(4326)
rm(namesEurope)
# France
respecEnv$geomFrance <- sf::st_read("countries/data/orig_geom/geomFrance.geojson")
respecEnv$geomFrance <- respecEnv$geomFrance %>%
dplyr::mutate(
country_name = "France"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = code,
micro_name = nom
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Germany
respecEnv$geomGermany <- sf::st_read("countries/data/orig_geom/geomGermany.geojson")
respecEnv$geomGermany <- respecEnv$geomGermany %>%
dplyr::mutate(
country_name = "Germany",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = county
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# India
respecEnv$geomIndia <- sf::st_read("countries/data/orig_geom/geomIndia.geojson")
respecEnv$geomIndia <- respecEnv$geomIndia %>%
dplyr::group_by(NAME_1) %>% # Merge the two Dadra... so they only take up one entry
dplyr::summarise() %>%
sf::st_cast("MULTIPOLYGON") %>%
dplyr::mutate(
country_name = "India",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Indonesia
respecEnv$geomIndonesia <- sf::st_read("countries/data/orig_geom/geomIndonesia.geojson")
respecEnv$geomIndonesia <- respecEnv$geomIndonesia %>%
dplyr::mutate(
country_name = "Indonesia",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Ireland
respecEnv$geomIreland <- sf::st_read("countries/data/orig_geom/geomIreland.geojson")
provIreland <- respecEnv$geomIreland %>%
dplyr::group_by(PROVINCE) %>%
dplyr::group_keys() %>%
tibble::rowid_to_column("macro_code")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscIreland.csv")) {
respecEnv$geomIreland %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscIreland.csv")
cat("\nmiscIreland.csv Created\n")
}else{
cat("\nmiscIreland.csv Already Exists\n")
}
respecEnv$geomIreland <- respecEnv$geomIreland %>%
dplyr::mutate(
country_name = "Ireland"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::left_join(provIreland) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code,
macro_name = PROVINCE,
micro_code = CO_ID,
micro_name = id
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Ireland valid
respecEnv$geomIreland <- respecEnv$geomIreland %>%
sf::st_transform(23029) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
rm(provIreland)
# Italy
respecEnv$geomItaly <- sf::st_read("countries/data/orig_geom/geomItaly.geojson")
respecEnv$geomItaly <- respecEnv$geomItaly %>%
dplyr::mutate(
country_name = "Italy"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = reg_istat_code,
macro_name = reg_name,
micro_code = prov_istat_code,
micro_name = prov_name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Japan
respecEnv$geomJapan <- sf::st_read("countries/data/orig_geom/geomJapan.geojson")
respecEnv$geomJapan <- respecEnv$geomJapan %>%
dplyr::mutate(
country_name = "Japan",
micro_code = row_number()
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Japan valid
respecEnv$geomJapan <- respecEnv$geomJapan %>%
sf::st_transform(3100) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Malaysia
respecEnv$geomMalaysia <- sf::st_read("countries/data/orig_geom/geomMalaysia.geojson")
respecEnv$geomMalaysia <- respecEnv$geomMalaysia %>%
dplyr::mutate(
country_name = "Malaysia"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = id,
micro_name = Name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Mexico
respecEnv$geomMexico <- sf::st_read("countries/data/orig_geom/geomMexico.geojson")
respecEnv$geomMexico <- respecEnv$geomMexico %>%
dplyr::mutate(
country_name = "Mexico",
macro_code = str_sub(CVEGEO, 1, 2)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code,
macro_name = estado,
micro_code = CVEGEO,
micro_name = NOMGEO
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Mexico valid
respecEnv$geomMexico <- respecEnv$geomMexico %>%
sf::st_transform(6372) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Mozambique
respecEnv$geomMozambique <- sf::st_read("countries/data/orig_geom/geomMozambique.geojson")
respecEnv$geomMozambique <- respecEnv$geomMozambique %>%
dplyr::mutate(
country_name = "Mozambique"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = ID_1,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Netherlands
respecEnv$geomNetherlands <- sf::st_read("countries/data/orig_geom/geomNetherlands.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscNetherlands.csv")) {
respecEnv$geomNetherlands %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscNetherlands.csv")
cat("\nmiscNetherlands.csv Created\n")
}else{
cat("\nmiscNetherlands.csv Already Exists\n")
}
respecEnv$geomNetherlands <- respecEnv$geomNetherlands %>%
dplyr::mutate(
country_name = "Netherlands"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = Provinciecode,
macro_name = Provincie,
micro_code = Gemeentecode,
micro_name = Gemeentenaam
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Nigeria
respecEnv$geomNigeria <- sf::st_read("countries/data/orig_geom/geomNigeria.geojson")
respecEnv$geomNigeria <- respecEnv$geomNigeria %>%
dplyr::mutate(
country_name = "Nigeria"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = admin1Pcod,
micro_name = admin1Name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Norway
respecEnv$geomNorway <- sf::st_read("countries/data/orig_geom/geomNorway.geojson")
## this geometry is missing Svalbard and Ukjent, but they also don't have population in the dataset
norw_kommune <- vroom::vroom("https://raw.githubusercontent.com/thohan88/covid19-nor-data/master/data/01_infected/msis/municipality.csv") %>%
dplyr::select(kommune_no, kommune_name, fylke_no, fylke_name) %>%
dplyr::distinct()
respecEnv$geomNorway <- respecEnv$geomNorway %>%
dplyr::group_by(kommunenummer) %>%
dplyr::summarise() %>%
sf::st_cast("MULTIPOLYGON") %>%
dplyr::mutate(
country_name = "Norway",
kommune_no = str_pad(kommunenummer, pad = "0", side = "left", width = 4)
) %>%
dplyr::left_join(
norw_kommune
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = fylke_no,
macro_name = fylke_name,
micro_code = kommune_no,
micro_name = kommune_name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(norw_kommune)
# NZ
respecEnv$geomNZ <- sf::st_read("countries/data/orig_geom/geomNZ.geojson")
respecEnv$geomNZ <- respecEnv$geomNZ %>%
dplyr::mutate(
country_name = "New Zealand"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = DHB2015_Co,
micro_name = DHB2015_Na
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Peru
respecEnv$geomPeru <- sf::st_read("countries/data/orig_geom/geomPeru.geojson")
respecEnv$geomPeru <- respecEnv$geomPeru %>%
dplyr::mutate(
country_name = "Peru",
NOMBDEP = str_replace_all(
str_to_title(NOMBDEP),
"\\sDe\\s",
" de "
)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = FIRST_IDDP,
micro_name = NOMBDEP
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Philippines
respecEnv$geomPhilippines <- sf::st_read("countries/data/orig_geom/geomPhilippines.geojson")
namesPhilippines <- vroom::vroom("countries/data/namesPhilippines.csv") %>%
dplyr::select(starts_with("ADM2"), starts_with("ADM1")) %>%
dplyr::distinct()
respecEnv$geomPhilippines <- respecEnv$geomPhilippines %>%
dplyr::mutate(
country_name = "Philippines"
) %>%
dplyr::left_join(namesPhilippines) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = ADM1_PCODE,
macro_name = ADM1_EN,
micro_code = ADM2_PCODE,
micro_name = ADM2_EN
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(namesPhilippines)
# SaudiArabia
respecEnv$geomSaudiArabia <- sf::st_read("countries/data/orig_geom/geomSaudiArabia.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscSaudiArabia.csv")) {
geomSaudiArabia %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscSaudiArabia.csv")
cat("\nmiscSaudiArabia.csv Created\n")
}else{
cat("\nmiscSaudiArabia.csv Already Exists\n")
}
respecEnv$geomSaudiArabia <- respecEnv$geomSaudiArabia %>%
dplyr::mutate(
country_name = "Saudi Arabia"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = REG_CODE,
micro_name = region_name_en
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
sf::st_make_valid() # Make Saudi Arabia valid
# SouthAfrica
respecEnv$geomSouthAfrica <- sf::st_read("countries/data/orig_geom/geomSouthAfrica.geojson")
respecEnv$geomSouthAfrica <- respecEnv$geomSouthAfrica %>%
dplyr::mutate(
country_name = "South Africa"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = PROVINCE
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# Spain
respecEnv$geomSpain <- sf::st_read("countries/data/orig_geom/geomSpain.geojson")
namesSpain <- vroom::vroom("countries/data/namesSpain.csv") %>%
dplyr::mutate(cod_ccaa = stringr::str_pad(Code, width = 2, side = "left", pad = "0"))
respecEnv$geomSpain <- respecEnv$geomSpain %>%
dplyr::mutate(
country_name = "Spain"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::left_join(namesSpain) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_code = cod_ccaa,
macro_name = Region,
micro_code = cod_prov,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
sf::st_make_valid() # Make Spain valid
rm(namesSpain)
# Sweden
respecEnv$geomSweden <- sf::st_read("countries/data/orig_geom/geomSweden.geojson")
respecEnv$geomSweden <- respecEnv$geomSweden %>%
dplyr::mutate(
country_name = "Sweden"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = cartodb_id,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# SwitzerlandLiechtenstein
respecEnv$geomSwitzerlandLiechtenstein <- sf::st_read("countries/data/orig_geom/geomSwitzerlandLiechtenstein.geojson")
respecEnv$geomSwitzerlandLiechtenstein <- respecEnv$geomSwitzerlandLiechtenstein %>%
dplyr::mutate(
country_name = case_when(
name == "Liechtenstein" ~ "Liechtenstein",
TRUE ~ "Switzerland"
)
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
micro_code = id,
micro_name = name
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
## Make Switzerland and Liechtenstein valid
respecEnv$geomSwitzerlandLiechtenstein <- respecEnv$geomSwitzerlandLiechtenstein %>%
sf::st_transform(21781) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Taiwan"
respecEnv$geomTaiwan <- sf::st_read("countries/data/orig_geom/geomTaiwan.geojson")
respecEnv$geomTaiwan <- respecEnv$geomTaiwan %>%
dplyr::mutate(
country_name = "Taiwan",
m49code = 158, # Using ISO3166 code bc Taiwan is not in the M49 list
iso3 = "TWN"
) %>%
dplyr::select(
m49code,
iso3,
country_name,
micro_code = COUNTYSN,
micro_name = COUNTYNAME
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character)) %>%
dplyr::filter(!micro_code %in% c("10011001", "10006003"))
# Thailand"
respecEnv$geomThailand <- sf::st_read("countries/data/orig_geom/geomThailand.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscThailand.csv")) {
respecEnv$geomThailand %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscThailand.csv")
cat("\nmiscThailand.csv Created\n")
}else{
cat("\nmiscThailand.csv Already Exists\n")
}
respecEnv$geomThailand <- respecEnv$geomThailand %>%
dplyr::mutate(
country_name = "Thailand"
) %>%
dplyr::left_join(
m49,
by = c("country_name" = "CountryorArea")
) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISOalpha3Code,
country_name,
macro_name = reg_nesdb,
micro_code = pro_code,
micro_name = pro_en
) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
# UnitedKingdom"
respecEnv$geomUnitedKingdom <- sf::st_read("countries/data/orig_geom/geomUnitedKingdom.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/miscUK.csv")) {
respecEnv$geomUnitedKingdom %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/miscUK.csv")
cat("\nmiscUK.csv Created\n")
}else{
cat("\nmiscUK.csv Already Exists\n")
}
respecEnv$geomUnitedKingdom <- respecEnv$geomUnitedKingdom %>%
dplyr::mutate(
country_name = "United Kingdom",
m49code = m49$M49Code[which(m49$CountryorArea == "United Kingdom of Great Britain and Northern Ireland")],
iso3 = m49$ISOalpha3Code[which(m49$CountryorArea == "United Kingdom of Great Britain and Northern Ireland")]
) %>%
dplyr::select(
m49code,
iso3,
country_name,
micro_code = code,
micro_name = name
) %>%
dplyr::mutate(across(.cols = dplyr::ends_with("code"), .fns = as.character))
# UnitedStates"
respecEnv$geomUnitedStates <- sf::st_read("countries/data/orig_geom/geomUnitedStates.geojson")
usStatelines <- sf::st_read("countries/data/orig_geom/US_stateLines.geojson") %>%
st_drop_geometry()
respecEnv$geomUnitedStates <- respecEnv$geomUnitedStates %>%
dplyr::mutate(
country_name = "United States",
m49code = m49$M49Code[which(m49$CountryorArea == "United States of America")],
iso3 = m49$ISOalpha3Code[which(m49$CountryorArea == "United States of America")]
) %>%
dplyr::inner_join(usStatelines, by = c("stname" = "STUSPS")) %>%
dplyr::select(
m49code,
iso3,
country_name,
macro_code = stname,
macro_name = NAME.y,
micro_code = GEOID.x,
micro_name = NAME.x
) %>%
dplyr::mutate(across(.cols = dplyr::ends_with("code"), .fns = as.character))
respecEnv$geomAK <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "AK") %>%
sf::st_transform(3467) %>%
dplyr::group_by(m49code, iso3, country_name, macro_code, macro_name, micro_code, micro_name) %>%
dplyr::summarise() %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
respecEnv$geomCO <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "CO") %>%
sf::st_transform(2773) %>%
dplyr::group_by(m49code, iso3, country_name, macro_code, macro_name, micro_code, micro_name) %>%
dplyr::summarise() %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
respecEnv$geomID <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "ID") %>%
sf::st_transform(2788) %>%
dplyr::group_by(m49code, iso3, country_name, macro_code, macro_name, micro_code, micro_name) %>%
dplyr::summarise() %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
respecEnv$geomKS <- respecEnv$geomUnitedStates %>%
dplyr::filter(macro_code == "KS") %>%
sf::st_make_valid()
respecEnv$geomUnitedStates <- respecEnv$geomUnitedStates %>%
dplyr::filter(!macro_code %in% c("AK", "CO", "ID", "KS")) %>%
dplyr::bind_rows(respecEnv$geomAK, respecEnv$geomCO, respecEnv$geomID, respecEnv$geomKS)
rm(list = c("geomAK", "geomCO", "geomID", "geomKS"), envir = respecEnv)
rm(usStatelines)
# Venezuela"
respecEnv$geomVenezuela <- sf::st_read("countries/data/orig_geom/geomVenezuela.geojson")
respecEnv$geomVenezuela <- respecEnv$geomVenezuela %>%
dplyr::mutate(
country_name = "Venezuela",
m49code = m49$M49Code[which(m49$CountryorArea == "Venezuela (Bolivarian Republic of)")],
iso3 = m49$ISOalpha3Code[which(m49$CountryorArea == "Venezuela (Bolivarian Republic of)")]
) %>%
dplyr::select(
m49code,
iso3,
country_name,
micro_code = ID_1,
micro_name = NAME_1
) %>%
dplyr::mutate(across(.cols = dplyr::ends_with("code"), .fns = as.character))
## Make Venezuela valid
respecEnv$geomVenezuela <- respecEnv$geomVenezuela %>%
sf::st_transform(2201) %>%
sf::st_make_valid() %>%
sf::st_transform(4326)
# Small Countries
respecEnv$geomSmallCountries <- sf::st_read("countries/data/orig_geom/WB_countries_Admin0_lowres.geojson")
## Only create csv if it doesn't exist.
if (!file.exists("countries/data/popSmallCountries.csv")) {
respecEnv$geomSmallCountries %>%
sf::st_drop_geometry() %>%
write_csv("countries/data/popSmallCountries.csv")
cat("\npopSmallCountries.csv Created\n")
}else{
cat("\npopSmallCountries.csv Already Exists\n")
}
respecEnv$geomSmallCountries <- respecEnv$geomSmallCountries %>%
dplyr::left_join(m49, by = c("ISO_A3" = "ISOalpha3Code")) %>%
dplyr::select(
m49code = M49Code,
iso3 = ISO_A3,
country_name = NAME_EN
)
respecEnv$geomFiji <- respecEnv$geomSmallCountries %>%
dplyr::filter(iso3 == "FJI") %>% # Fiji
sf::st_cast("POLYGON") %>%
sf::st_wrap_dateline() %>%
dplyr::group_by(m49code, iso3, country_name) %>%
dplyr::summarise() %>%
dplyr::ungroup()
respecEnv$geomSmallCountries <- respecEnv$geomSmallCountries[which(sf::st_is_valid(respecEnv$geomSmallCountries, reason = T) == "Valid Geometry"), ] %>% # Russia, USA, and Japan are accounted for in other data sets, so we can afford to loose them
dplyr::bind_rows(respecEnv$geomFiji) %>%
dplyr::mutate(across(.cols = ends_with("code"), .fns = as.character))
rm(geomFiji, envir = respecEnv)
# Tidy up and finish
## the respecEnv has all the country geoms *and only the country geoms*
geom_list <- ls(respecEnv)
geomWorld <- purrr::map_df(
geom_list, # For each geometry file...
~ get(.x, envir = respecEnv) %>%
dplyr::mutate(
filename = .x # Add a column with the filename...
) %>%
{ if(st_geometry_type(., FALSE) %in% c("GEOMETRY", "GEOMETRYCOLLECTION")){
sf::st_collection_extract(.) # If geometry type "geometry" or "geometrycollection," cast back to polygon...
}else{.}
} %>%
sf::st_cast("MULTIPOLYGON") # Cast everything to Multipolygon so they are all the same type
) %>%
replace_na(list("macro_code" = "00")) %>% # Replace NAs in macro_code with "00"
dplyr::mutate( # Create GEOIDs
geoid = paste(paste0(iso3, m49code), macro_code, micro_code, sep = "_")
) %>%
dplyr::select(geoid, m49code, iso3, country_name, macro_code, macro_name, everything()) %>%
sf::st_as_sf() %>%
tibble::remove_rownames()
## Write presimplified geometry
sf::st_write(geomWorld, "geomWorld_presimp.geojson", delete_dsn = T)
rm(respecEnv) ## delete environment with individual geometries
## Zip presimplified geometry
nowtime <- round(difftime(now(tzone = "UTC"), ymd_hms("1970-01-01 00:00:00"), tz = "UTC", units = "mins"))
utils::zip(zipfile = paste0("updateGeometry/WorldPreSimplified/WorldPreSimp", nowtime, ".zip"), "geomWorld_presimp.geojson")
file.remove("geomWorld_presimp.geojson")
rm(m49)
rm(geom_list)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.