data-raw/memberships/DESTA_MEM/prepare-DESTA_MEM.R

In globalgov/qTrade: Trade Agreements for manydata

# DESTA_MEM Preparation Script

# This is a template for importing, cleaning, and exporting data
# ready for the many package.

# Stage one: Collecting data
# Note that the original data (in excel format) has been converted and saved as
# a csv file with the same variables and data.
DESTA_MEM <- read.csv2("data-raw/memberships/DESTA_MEM/DESTA_MEM.csv")

# Stage two: Correcting data
# In this stage you will want to correct the variable names and
# formats of the 'DESTA_MEM' object until the object created
# below (in stage three) passes all the tests.
parties <- tibble::as_tibble(DESTA_MEM) %>%
  # merge rows with same base_treaty
  dplyr::group_by(base_treaty, year) %>%
  dplyr::summarise(dplyr::across(c("c1":"c91"), ~ .[!is.na(.)][1])) %>%
  dplyr::mutate(base_treaty = as.character(base_treaty))
basetitles <- DESTA_MEM %>%
  dplyr::select(number, name, entry_type, year) %>%
  dplyr::filter(entry_type == "base_treaty" |
                  entry_type == "protocol or amendment") %>%
  dplyr::distinct() %>%
  dplyr::rename(Title2 = name) %>%
  manydata::transmutate(Sign1 = messydates::as_messydate(as.character(year))) %>%
  dplyr::select(number, Title2, Sign1)
DESTA_MEM <- tibble::as_tibble(DESTA_MEM) %>%
  dplyr::select(base_treaty, name, entry_type, year,
                entryforceyear) %>%
  dplyr::mutate(base_treaty = as.character(base_treaty)) %>%
  dplyr::left_join(basetitles, by = c("base_treaty" = "number")) %>%
  dplyr::left_join(parties, by = c("base_treaty", "year")) %>%
  # rename agreement title to base treaty title for accession, withdrawal,
  # and consolidated treaties
  dplyr::mutate(Title = ifelse(entry_type == "accession" |
                                 entry_type == "withdrawal",
                               Title2,
                               name)) %>%
  tidyr::pivot_longer(c("c1":"c91"), names_to = "Member",
                      values_to = "stateID",
                      values_drop_na = TRUE) %>%
  # arrange columns containing countries into one column,
  # with each stateID in rows corresponding to the treaty it is party to
  manydata::transmutate(destaID = as.character(`base_treaty`),
                        Signature = messydates::as_messydate(as.character(year)),
                        Force = messydates::as_messydate(as.character(entryforceyear))) %>%
  dplyr::mutate(Begin = ifelse(entry_type == "accession" |
                                 entry_type == "withdrawal",
                               dplyr::coalesce(Sign1, Force),
                               dplyr::coalesce(Signature, Force)),
                Title = manypkgs::standardise_titles(Title)) %>%
  dplyr::select(destaID, stateID, Title, Begin, Signature, Force) %>%
  dplyr::arrange(Begin)

DESTA_MEM$StateName <- countrycode::countrycode(DESTA_MEM$stateID,
                                                origin = "iso3n",
                                                destination = "country.name")
DESTA_MEM <- DESTA_MEM %>%
  dplyr::mutate(StateName = ifelse(stateID == 530, "Netherlands Antilles",
                                   StateName)) %>%
  dplyr::mutate(StateName = ifelse(stateID == 900, "Kosovo", StateName))

#Change iso numeric to iso character code
DESTA_MEM$stateID <- countrycode::countrycode(DESTA_MEM$stateID,
                                              origin = "iso3n",
                                              destination = "iso3c")

#Add a treatyID column
DESTA_MEM$treatyID <- manypkgs::code_agreements(DESTA_MEM, DESTA_MEM$Title, 
                                                DESTA_MEM$Begin)

# Add manyID column
manyID <- manypkgs::condense_agreements(manytrade::memberships)
DESTA_MEM <- dplyr::left_join(DESTA_MEM, manyID, by = "treatyID") %>%
  dplyr::distinct()

# Re-order the columns
DESTA_MEM <- dplyr::relocate(DESTA_MEM, manyID, stateID, Title, Begin,
                             Signature, Force, StateName, destaID)
DESTA_MEM <- DESTA_MEM %>% 
  dplyr::mutate(across(everything(),
                       ~stringr::str_replace_all(., "^NA$", NA_character_))) %>%
  dplyr::mutate(Begin = messydates::as_messydate(Begin),
         Signature = messydates::as_messydate(Signature),
         Force = messydates::as_messydate(Force)) %>%
  dplyr::distinct(.keep_all = TRUE)

# Check for duplicates in manyID
# duplicates <- DESTA_MEM %>%
#   dplyr::mutate(duplicates = duplicated(DESTA_MEM[, c(1,2)])) %>%
#   dplyr::relocate(manyID, stateID,  duplicates)

# manypkgs includes several functions that should help cleaning
# and standardising your data.
# Please see the vignettes or website for more details.

# Stage three: Connecting data
# Next run the following line to make DESTA_MEM available
# within the many universe.
manypkgs::export_data(DESTA_MEM, datacube = "memberships",
                      URL = "https://www.designoftradeagreements.org/downloads/")
# This function also does two additional things.
# First, it creates a set of tests for this object to ensure adherence
# to certain standards.You can hit Cmd-Shift-T (Mac) or Ctrl-Shift-T (Windows)
# to run these tests locally at any point.
# Any test failures should be pretty self-explanatory and may require
# you to return to stage two and further clean, standardise, or wrangle
# your data into the expected format.
# Second, it also creates a documentation file for you to fill in.
# Please note that the export_data() function requires a .bib file to be
# present in the data_raw folder of the package for citation purposes.
# Therefore, please make sure that you have permission to use the dataset
# that you're including in the package.
# To add a template of .bib file to package,
# run `manypkgs::add_bib(memberships, DESTA_MEM)`.