## code to prepare `pepfar_data_calendar`
#source: https://datim.zendesk.com/hc/en-us/articles/115001940503-PEPFAR-Data-Calendar
pepfar_data_calendar <-
tibble::tribble(
~fiscal_year, ~quarter, ~type, ~entry_open, ~entry_close, ~msd_release,
2021L, 1L, "initial", "2021-01-06", "2021-02-12", "2021-02-19",
2021L, 1L, "clean", "2021-03-01", "2021-03-19", "2021-03-26",
2021L, 2L, "initial", "2021-04-01", "2021-05-14", "2021-05-21",
2021L, 2L, "clean", "2021-06-01", "2021-06-18", "2021-06-25",
2021L, 3L, "initial", "2021-07-01", "2021-08-13", "2021-08-20",
2021L, 3L, "clean", "2021-09-01", "2021-09-17", "2021-09-24",
2021L, 4L, "initial", "2021-10-01", "2021-11-12", "2021-11-19",
2021L, 4L, "clean", "2021-12-01", "2021-12-17", "2022-01-07",
2022L, 1L, "initial", "2022-01-05", "2022-02-11", "2022-02-18",
2022L, 1L, "clean", "2022-03-01", "2022-03-18", "2022-03-25",
2022L, 2L, "initial", "2022-04-01", "2022-05-13", "2022-05-20",
2022L, 2L, "clean", "2022-06-01", "2022-06-17", "2022-06-24",
2022L, 3L, "initial", "2022-07-01", "2022-08-12", "2022-08-19",
2022L, 3L, "clean", "2022-09-01", "2022-09-16", "2022-09-23",
2022L, 4L, "initial", "2022-10-03", "2022-11-10", "2022-11-22",
2022L, 4L, "clean", "2022-12-01", "2022-12-16", "2023-01-06",
2023L, 1L, "initial", "2023-01-04", "2023-02-10", "2023-02-17",
2023L, 1L, "clean", "2023-02-28", "2023-03-17", "2023-03-24",
2023L, 2L, "initial", "2023-03-31", "2023-05-12", "2023-05-19",
2023L, 2L, "clean", "2023-05-31", "2023-06-16", "2023-06-27",
2023L, 3L, "initial", "2023-06-30", "2023-08-11", "2023-08-18",
2023L, 3L, "clean", "2023-08-31", "2023-09-15", "2023-09-22",
2023L, 4L, "initial", "2023-10-02", "2023-11-14", "2023-11-21",
2023L, 4L, "clean", "2023-11-30", "2023-11-15", "2024-01-05",
2024L, 1L, "initial", "2024-01-03", "2024-02-15", "2024-02-23",
2024L, 1L, "clean", "2024-03-01", "2024-03-15", "2024-03-22",
2024L, 2L, "initial", "2024-04-01", "2024-05-17", "2024-05-24",
2024L, 2L, "clean", "2024-05-31", "2024-06-14", "2024-06-25",
2024L, 3L, "initial", "2024-07-01", "2024-08-16", "2024-08-23",
2024L, 3L, "clean", "2024-08-30", "2024-09-13", "2024-09-20",
2024L, 4L, "initial", "2024-10-01", "2024-11-15", "2024-11-22",
2024L, 4L, "clean", "2024-12-02", "2024-12-13", "2024-12-20"
) %>%
dplyr::filter(fiscal_year >= max(fiscal_year) - 1) %>%
dplyr::mutate(dplyr::across(c(entry_open, entry_close, msd_release), as.Date))
usethis::use_data(pepfar_data_calendar, overwrite = TRUE)
## PEPFAR country list
library(tidyverse)
devtools::load_all()
gophr::get_metadata()
# df_msd <- si_path() %>%
# return_latest("OU_IM") %>%
# gophr::read_msd()
# df_cntry <- df_msd %>%
# filter(fiscal_year == curr_fy,
# funding_agency %ni% c("Dedup", "Default"),
# indicator != "TX_NET_NEW") %>%
# distinct(operatingunit, country)
df_fsd <- si_path() %>%
return_latest("Financial") %>%
gophr::read_psd()
df_cntry <- df_fsd %>%
filter(fiscal_year == metadata$curr_fy,
str_detect(country, "Region", negate = TRUE),
cop_budget_total > 0,
funding_agency %ni% c("Dedup", "Default")) %>%
distinct(operatingunit, country)
ou_table <- grabr::get_outable(datim_user(), datim_pwd()) %>%
select(operatingunit, operatingunit_iso, operatingunit_uid,
country, country_iso, country_uid)
pepfar_country_list <- df_cntry %>%
left_join(ou_table, by = c("operatingunit", "country")) %>%
relocate(starts_with("op")) %>%
arrange(operatingunit, country)
#Amb Nkengasong's 8 + 1 + 1 countries (2023-06-09 re:Moving countries to green!)
pepfar_focus <- c("Cameroon", "Cote d'Ivoire", "Ethiopia", "Kenya",
"Mozambique", "Nigeria", "Tanzania", "Zambia",
"South Africa", "Philippines")
pepfar_country_list <- pepfar_country_list %>%
mutate(pepfar_accel = country %in% pepfar_focus)
usethis::use_data(pepfar_country_list, overwrite = TRUE)
## PEPFAR, UN and NE countries cross-walk
library(tidyverse)
library(glamr)
library(countrycode)
library(rnaturalearth)
library(janitor)
# PEPFAR Countries
cntries <- glamr::pepfar_country_list
# NE Countries
ne_cntries <- rnaturalearth::ne_countries() %>%
sf::st_as_sf() %>%
sf::st_drop_geometry() %>%
tibble::as_tibble() %>%
select(iso_a3, sovereignt, admin, name)
# Countrycode
cntrycodes <- countrycode::codelist %>%
select(iso3c, continent, region, region23, un.region.name,
starts_with("iso.name"),
starts_with("country.name"),
starts_with("un.name"))
# Combine and keep only PEPFAR Countries
pepfar_country_xwalk <- cntrycodes %>%
filter(!is.na(iso3c)) %>%
left_join(ne_cntries %>% filter(!is.na(iso_a3)),
by = c("iso3c" = "iso_a3")) %>%
left_join(cntries, by = c("iso3c" = "country_iso")) %>%
filter(!is.na(operatingunit_iso)) %>%
clean_names()
# publish dataset
usethis::use_data(pepfar_country_xwalk, overwrite = TRUE)
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