R/data.R

#' Weather data for in-situ stations in Queensland from 1990 to 2020
#'
#' @format A tibble with 9 columns:
#' \describe{
#' \item{id}{station ID, ASN000xxxxx}
#' \item{ym}{date in `tsibble::yearmonth` format}
#' \item{prcp}{aggregated monthly precipitation from daily data}
#' \item{tmax, tmin, tavg}{maximum/minimum/ average temperature}
#' \item{long, lat}{longitude and latitude of the station}
#' \item{name}{station name}
#' }
#' @rdname weather
"tenterfield"

#' @rdname weather
"aus_climate"

#' @rdname weather
"queensland"

#' Human Development Index (2022)
#'
#' @format A tibble with three columns:
#' \describe{
#' \item{id}{the row number}
#' \item{country}{191 countries with computed HDI}
#' \item{hdi}{the HDI index value}
#' \item{life_exp}{life expectancy}
#' \item{exp_sch}{expected schooling}
#' \item{avg_sch}{average schooling}
#' \item{gni_pc}{GNI per capital, logged}
#' }
#' @references https://hdr.undp.org/data-center/human-development-index#/indicies/HDI
#' @rdname hdi
"hdi"

#' @rdname hdi
"hdi_scales"


#' Global Gender Gap Index (2023)
#'
#' The Global Gender Gap Index combines 14 variables from four dimensions to
#' measure the gender parity across 146 countries in the world.
#'
#' @details
#' The dataset includes country, region, GGGI score and rank, the combined four
#' dimensions (Economic Participation and Opportunity, Educational Attainment,
#' Health and Survival, and Political Empowerment), and variables under each
#' dimensions. The variable composition of each dimension is as follows:
#'
#' * Economic Participation and Opportunity: Labour force
#' participation, Wage equality for similar work, Estimated earned income,
#' Legislators, senior officials and managers, and Professional and technical
#' workers
#'
#' * Educational attainment: Literacy rate, Enrolment in primary education,
#' Enrolment in secondary education, Enrolment in tertiary education
#'
#' * Health and survival: Sex ratio at birth and Healthy life expectancy
#'
#' * Political empowerment:  Women in parliament, Women in ministerial
#' positions, and Years with female head of state
#'
#' Variable names are cleaned with [janitor::clean_names()].
#'
#' The weight data is extracted from page 65 of the Global Gender Gap Report
#' (see reference), see page 61 for the region classification.
#' @rdname gggi
#' @references https://www3.weforum.org/docs/WEF_GGGR_2023.pdf
"gggi"

#' @rdname gggi
"gggi_weights"

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tidyindex documentation built on Nov. 16, 2023, 5:08 p.m.