R/abs-series-abbreviation.R
In mitcda/raustats: Access Data and Statistics from the ABS and RBA Websites
Defines functions
ana_series_abb
## =========================================================================
## Filename:
## Created:
## Updated: <2019-06-19 10:46:32 david at grover>
## Author:
## Description:
##
##
## =========================================================================
#'
#' Table - ABS ANA Series IDs and series names
#'
#' ABS Series ID | Series abb | Series name
#' :---------------|:--------------|:--------------------------------------
#' A2304402X | gdp_cv_sa | GDP Chain Volume measures: Seasonally Adjusted
#' A2304340C | gdp_cv_tr | " : Trend
#' A2302459A | gdp_cv_or | " : Original
#' A2304408L | gdi_cv_sa | Gross Domestic Income, Chain Volume measures: Seasonally Adjusted
#' A2304342J | gdi_cv_tr | " : Trend
#' A2302463T | gdi_cv_or | " : Original
#' A2304412C | gni_cv_sa | GNI Chain Volume measures: Seasonally Adjusted
#' A2304344L | gni_cv_tr | " : Trend
#' A2302464V | gni_cv_or | " : Original
#' A2304414J | nndi_cv_sa | NNDI Chain Volume measures: Seasonally Adjusted
#' A2304346T | nndi_cv_tr | " : Trend
#' A2302465W | nndi_cv_or | " : Original
#' A2304404C | gdppc_cv_sa | GDP per capita Chain volume measures: Seasonally Adjusted
#' A2304336L | gdppc_cv_tr | " : Trend
#' A2302459A | gdppc_cv_or | " : Original
#' A2304113C | gne_cv_sa | GNE Chain Volume measures: Seasonally Adjusted
#' A2304237F | gne_cv_tr | " : Trend
#' A2302514F | gne_cv_or | " : Original
#' A2304111X | dfd_cv_sa | DFD Chain Volume measures: Seasonally Adjusted
#' A2304235A | dfd_cv_tr | " : Trend
#' A2302519T | dfd_cv_or | " : Original
#' A2304114F | exp_cv_sa | Exports Chain Volume measures: Seasonally Adjusted
#' A2304238J | exp_cv_tr | " : Trend
#' A2302520A | exp_cv_or | " : Original
#' A2304115J | imp_cv_sa | Imports Chain Volume measures: Seasonally Adjusted
#' A2304239K | imp_cv_sa | " : Trend
#' A2302521C | imp_cv_sa | " : Original
#'
#' Notes
#' GDI = GDP - ToT effects (GDI - Gross Domestic Income)
#' NNDI = ?? (NNDI - Net National Disposable Income)
#' DFD = GNE - Inventory change (DFD - Domestic Final Demand)
#'
#'
#### Add human-readable series model names (abbreviations)
## -- TO DO - INCLUDE IN ABS data package GENERAL FUNCTIONS
ana_series_abb <- function(x) {
x %>%
## Table abbreviations
mutate(series_abb =
case_when(grepl("^key national accounts aggregates", table_title, ignore.case=TRUE)
~ "ana",
grepl("^expenditure.+GDP", table_title, ignore.case=TRUE)
~ "gdpe",
grepl("^income from.+GDP", table_title, ignore.case=TRUE)
~ "gdpi",
grepl("^gross value added.+industry", table_title, ignore.case=TRUE)
~ "gva",
grepl("^gross value added.+industry.+current price", table_title, ignore.case=TRUE)
~ "gvacp",
grepl("^household.*final.*consumption.*expenditure", table_title, ignore.case=TRUE)
~ "hfce",
TRUE ~ ""),
## Series abbreviations
series_abb =
paste0(series_abb,
case_when(grepl("^gross domestic product", data_item_description, ignore.case=TRUE)
~ "_gdp",
grepl("^gdp", data_item_description, ignore.case=TRUE)
~ "_gdp",
grepl("^gross value added", data_item_description, ignore.case=TRUE)
~ "_gva",
grepl("^net domestic product", data_item_description, ignore.case=TRUE)
~ "_ndp",
grepl("^net domestic product", data_item_description, ignore.case=TRUE)
~ "_ndp",
grepl("gross domestic income", data_item_description, ignore.case=TRUE)
~ "_gdi",
grepl("gross national income", data_item_description, ignore.case=TRUE)
~ "_gni",
grepl("net national disposable income", data_item_description, ignore.case=TRUE)
~ "_ndi",
grepl("terms of trade", data_item_description, ignore.case=TRUE)
~ "_tot",
grepl("gross national expenditure", data_item_description, ignore.case=TRUE)
~ "_gne",
grepl("exports of goods and services", data_item_description, ignore.case=TRUE)
~ "_exp",
grepl("imports of goods and services", data_item_description, ignore.case=TRUE)
~ "_imp",
grepl("domestic final demand", data_item_description, ignore.case=TRUE)
~ "_dfd",
grepl("change.+inventories", data_item_description, ignore.case=TRUE)
~ "_chinv",
grepl("final consumption expenditure", data_item_description, ignore.case=TRUE)
~ "_fce",
grepl("gross fixed capital formation", data_item_description, ignore.case=TRUE)
~ "_gfcf",
grepl("state final demand", data_item_description, ignore.case=TRUE)
~ "_sfd",
grepl("hours worked market sector", data_item_description, ignore.case=TRUE)
~ "_hrsmk",
grepl("hours worked", data_item_description, ignore.case=TRUE)
~ "_hrstl",
grepl("real unit.*labour cost.*non.*farm", data_item_description, ignore.case=TRUE)
~ "_rulcnf",
grepl("real unit.*labour cost.*", data_item_description, ignore.case=TRUE)
~ "_rulc",
grepl("household saving ratio", data_item_description, ignore.case=TRUE)
~ "_hsr",
grepl("net saving", data_item_description, ignore.case=TRUE)
~ "_netsav",
grepl("statistical discrepancy", data_item_description, ignore.case=TRUE)
~ "_statdis",
## Industry gross value added
## grepl(sprintf("\\(%s\\)\\s*;", paste(letters, collapse="|")),
## data_item_description, ignore.case=TRUE)
## ~ sub(sprintf(".+\\((%s)\\)\\s*;.*", paste(letters, collapse="|")),
## tolower("_div\\1"), data_item_description, ignore.case=TRUE),
## Division A - Agriculture, forestry & fishing
grepl("\\(a\\).+Agriculture", data_item_description, ignore.case=TRUE)
~ "_diva_ag",
grepl("\\(a\\).+Forestry.*fishing", data_item_description, ignore.case=TRUE)
~ "_diva_ff",
grepl("\\(a\\).+;$", data_item_description, ignore.case=TRUE)
~ "_diva_tot",
## Division B - Mining
grepl("\\(b\\).+coal.*mining", data_item_description, ignore.case=TRUE)
~ "_divb_cl",
grepl("\\(b\\).+oil.*gas", data_item_description, ignore.case=TRUE)
~ "_divb_og",
grepl("\\(b\\).+iron.*ore", data_item_description, ignore.case=TRUE)
~ "_divb_fe",
grepl("\\(b\\).+other.*mining", data_item_description, ignore.case=TRUE)
~ "_divb_ot",
grepl("\\(b\\).+mining.*excluding.*exploration", data_item_description,
ignore.case=TRUE)
~ "_divb_mn",
grepl("\\(b\\).+exploration.*support", data_item_description,
ignore.case=TRUE)
~ "_divb_es",
grepl("\\(b\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divb_tot",
## Division C - Manufacturing
grepl("\\(c\\).+food.*beverage", data_item_description, ignore.case=TRUE)
~ "_divc_fb",
grepl("\\(c\\).+petroleum.*coal", data_item_description, ignore.case=TRUE)
~ "_divc_pc",
grepl("\\(c\\).+metal.*products", data_item_description, ignore.case=TRUE)
~ "_divc_mt",
grepl("\\(c\\).+machinery.*equipment", data_item_description, ignore.case=TRUE)
~ "_divc_mc",
grepl("\\(c\\).+other.*manufacturing", data_item_description,
ignore.case=TRUE)
~ "_divc_ot",
grepl("\\(c\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divc_tot",
## Division D - Utilities
grepl("\\(d\\).+electricity", data_item_description, ignore.case=TRUE)
~ "_divd_el",
grepl("\\(d\\).+gas", data_item_description, ignore.case=TRUE)
~ "_divd_gs",
grepl("\\(d\\).+water.*supply", data_item_description, ignore.case=TRUE)
~ "_divd_wt",
grepl("\\(d\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divd_tot",
## Division E - Construction
grepl("\\(e\\).+building.*construction", data_item_description, ignore.case=TRUE)
~ "_dive_bc",
grepl("\\(e\\).+civil.*engineering", data_item_description, ignore.case=TRUE)
~ "_dive_ce",
grepl("\\(e\\).+construction.*services", data_item_description, ignore.case=TRUE)
~ "_dive_cs",
grepl("\\(e\\).+;$", data_item_description, ignore.case=TRUE)
~ "_dive_tot",
## Division F - Wholesale trade
grepl("\\(f\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divf_tot",
## Division G - Retail trade
grepl("\\(g\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divg_tot",
## Division H - Accommodation & food services
grepl("\\(h\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divh_tot",
## Division I - Transport
grepl("\\(i\\).+road", data_item_description, ignore.case=TRUE)
~ "_divi_rd",
grepl("\\(i\\).+air.*space", data_item_description, ignore.case=TRUE)
~ "_divi_as",
grepl("\\(i\\).+rail.*pipeline", data_item_description, ignore.case=TRUE)
~ "_divi_rl",
grepl("\\(i\\).+postal.*storage", data_item_description, ignore.case=TRUE)
~ "_divi_ps",
grepl("\\(i\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divi_tot",
## Division J - Telecommunications
grepl("\\(j\\).+telecommunications", data_item_description, ignore.case=TRUE)
~ "_divj_tl",
grepl("\\(j\\).+other.*information", data_item_description, ignore.case=TRUE)
~ "_divj_ot",
grepl("\\(j\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divj_tot",
## Division K - Finance & insurance
grepl("\\(k\\).+finance", data_item_description, ignore.case=TRUE)
~ "_divk_fn",
grepl("\\(k\\).+other.*financial", data_item_description, ignore.case=TRUE)
~ "_divk_ot",
grepl("\\(k\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divk_tot",
## Division L - Rental, hiring & real estate
grepl("\\(l\\).+rental.*hiring", data_item_description, ignore.case=TRUE)
~ "_divl_rh",
grepl("\\(l\\).+real.*estate", data_item_description, ignore.case=TRUE)
~ "_divl_re",
grepl("\\(l\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divl_tot",
## Division M - Professional and scientific services
grepl("\\(m\\).+computer.*system", data_item_description, ignore.case=TRUE)
~ "_divm_cs",
grepl("\\(m\\).+other.*professional", data_item_description, ignore.case=TRUE)
~ "_divm_op",
grepl("\\(m\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divm_tot",
## Division N - Administrative & support services
grepl("\\(n\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divn_tot",
## Division O - Public administration & safety
grepl("\\(o\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divo_tot",
## Division P - Education and training
grepl("\\(p\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divp_tot",
## Division Q - Health care & social assistance
grepl("\\(q\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divq_tot",
## Division R - Arts and recreation services
grepl("\\(r\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divr_tot",
## Division S - Other services
grepl("\\(s\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divs_tot",
## Ownership of dwellings
grepl("ownership.*dwellings", data_item_description, ignore.case=TRUE)
~ "_dwell",
grepl("taxes less subsidies", data_item_description, ignore.case=TRUE)
~ "_nettax",
grepl("gross value added at basi prices taxes less", data_item_description,
ignore.case=TRUE)
~ "_nettax",
## Household Final Consumption Expenditure items
grepl("Food", data_item_description, ignore.case=TRUE)
~ "_01_food",
grepl("Alcoholic.*beverage.*cigarettes.*tobacco", data_item_description,
ignore.case=TRUE)
~ "_02_albt",
grepl("Cigarettes.*tobacco", data_item_description, ignore.case=TRUE)
~ "_02a_tabc",
grepl("Alcoholic.*beverage", data_item_description, ignore.case=TRUE)
~ "_02b_abev",
grepl("Clothing.*footwear", data_item_description, ignore.case=TRUE)
~ "_03_clft",
grepl("Housing.*water.*electricity.*gas", data_item_description, ignore.case=TRUE)
~ "_04_hhsv",
grepl("Rent.*other.*dwelling.*services", data_item_description, ignore.case=TRUE)
~ "_04a_rnts",
grepl("Actual.*imputed.*rent", data_item_description, ignore.case=TRUE)
~ "_04b_rent",
grepl("Electricity.*gas.*other.*fuel", data_item_description, ignore.case=TRUE)
~ "_04c_util",
grepl("Water.*sewerage.*charges", data_item_description, ignore.case=TRUE)
~ "_04d_watr",
grepl("Furnishings.*household.*equip", data_item_description, ignore.case=TRUE)
~ "_05_furn",
grepl("Furniture.*floor.*coverings", data_item_description, ignore.case=TRUE)
~ "_05a_furn",
grepl("Household.*appliances", data_item_description, ignore.case=TRUE)
~ "_05b_appl",
grepl("Household.*tools", data_item_description, ignore.case=TRUE)
~ "_05c_tool",
grepl("Health", data_item_description, ignore.case=TRUE)
~ "_06_hlth",
grepl("Medicines", data_item_description, ignore.case=TRUE)
~ "_06a_hlth",
grepl("Total.*health.*services", data_item_description, ignore.case=TRUE)
~ "_06b_hlth",
grepl("Purchase.*vehicles", data_item_description, ignore.case=TRUE)
~ "_07a_vcpx",
grepl("Operation.*vehicles", data_item_description, ignore.case=TRUE)
~ "_07b_vopx",
grepl("Transport.*services", data_item_description, ignore.case=TRUE)
~ "_07c_tran",
grepl("Transport", data_item_description, ignore.case=TRUE)
~ "_07_tran",
grepl("Communications", data_item_description, ignore.case=TRUE)
~ "_08_comm",
grepl("Goods.*for.*recreation.*culture", data_item_description, ignore.case=TRUE)
~ "_09a_recg",
grepl("^Recreational.*cultural.*services", data_item_description,
ignore.case=TRUE)
~ "_09b_recs",
grepl("Sporting.*recreational.*cultural.*services", data_item_description,
ignore.case=TRUE)
~ "_09c_sprt",
grepl("Net.*losses.*gambling", data_item_description, ignore.case=TRUE)
~ "_09d_gamb",
grepl("Newspapers.*books.*stationery", data_item_description, ignore.case=TRUE)
~ "_09e_news",
grepl("Recreation.*culture", data_item_description, ignore.case=TRUE)
~ "_09_recc",
grepl("Education.*services", data_item_description, ignore.case=TRUE)
~ "_10_educ",
grepl("Hotels.*cafes.*restaurants", data_item_description, ignore.case=TRUE)
~ "_11_acrs",
grepl("Catering.*services", data_item_description, ignore.case=TRUE)
~ "_11a_cats",
grepl("Accommodation.*services", data_item_description, ignore.case=TRUE)
~ "_11b_accs",
grepl("Miscellaneous.*goods.*services", data_item_description, ignore.case=TRUE)
~ "_12_misc",
grepl("Other.*goods", data_item_description, ignore.case=TRUE)
~ "_12a_othg",
grepl("Insurance.*financial.*services", data_item_description, ignore.case=TRUE)
~ "_12b_fins",
grepl("Other.*services", data_item_description, ignore.case=TRUE)
~ "_12c_oths",
grepl("Net.*expenditure.*overseas", data_item_description, ignore.case=TRUE)
~ "_neo",
grepl("Final.*consumption.*expenditure", data_item_description, ignore.case=TRUE)
~ "_totc",
TRUE ~ "")),
##
## Per capita/hour worked series
series_abb = paste0(series_abb,
case_when(grepl("per capita", data_item_description, ignore.case=TRUE)
~ "pc",
grepl("per hour", data_item_description, ignore.case=TRUE)
~ "ph",
TRUE ~ "")),
##
## Households, government, private, public
series_abb = paste0(series_abb,
case_when(grepl("general government", data_item_description, ignore.case=TRUE)
~ "_gov",
TRUE ~ "")),
## -- General government options
series_abb = paste0(series_abb,
case_when(grepl("general government",
data_item_description, ignore.case=TRUE) ~ "_gov",
grepl("general government.+national",
data_item_description, ignore.case=TRUE) ~ "_nat",
grepl("general government.+national.+non-defence",
data_item_description, ignore.case=TRUE) ~ "_ndf",
grepl("general government.+national.+defence",
data_item_description, ignore.case=TRUE) ~ "_def",
grepl("general government.+state and local",
data_item_description, ignore.case=TRUE) ~ "_stl",
grepl("households",
data_item_description, ignore.case=TRUE) ~ "_hhld",
grepl("all sectors",
data_item_description, ignore.case=TRUE) ~ "_tot",
grepl("private",
data_item_description, ignore.case=TRUE) ~ "_priv",
grepl("public", data_item_description, ignore.case=TRUE)
~ "_pub",
TRUE ~ "")),
##
## States/territories
series_abb = paste0(series_abb,
case_when(grepl("new south wales",
data_item_description, ignore.case=TRUE)
~ "_nsw",
grepl("victoria", data_item_description, ignore.case=TRUE)
~ "_vic",
grepl("queensland", data_item_description, ignore.case=TRUE)
~ "_qld",
grepl("south australia", data_item_description, ignore.case=TRUE)
~ "_sa",
grepl("western australia", data_item_description, ignore.case=TRUE)
~ "_wa",
grepl("tasmania", data_item_description, ignore.case=TRUE)
~ "_tas",
grepl("northern territory", data_item_description, ignore.case=TRUE)
~ "_nt",
grepl("australian capital territory", data_item_description, ignore.case=TRUE)
~ "_act",
TRUE ~ "")),
##
## Chain volume/current prices
series_abb = paste0(series_abb,
case_when(grepl("chain volume measures", data_item_description, ignore.case=TRUE) |
grepl("chain volume measures", table_title, ignore.case=TRUE)
~ "_cv",
grepl("current prices", data_item_description, ignore.case=TRUE) |
grepl("current prices", table_title, ignore.case=TRUE)
~ "_cp",
grepl("price indexes", data_item_description, ignore.case=TRUE) |
grepl("price indexes", table_title, ignore.case=TRUE)
~ "_ix",
grepl("implicit price deflators", data_item_description, ignore.case=TRUE) |
grepl("implicit price deflators", table_title, ignore.case=TRUE)
~ "_pd",
TRUE ~ "")),
##
## Original/seasonally adjusted/trend/index
series_abb = paste0(series_abb,
case_when(grepl("original", series_type, ignore.case=TRUE)
~ "_or",
grepl("seasonally adjusted", series_type, ignore.case=TRUE)
~ "_sa",
grepl("trend", series_type, ignore.case=TRUE)
~ "_tr",
TRUE ~ "")),
##
## Percentage change/ratio/index
series_abb = paste0(series_abb,
case_when(grepl("percent", unit, ignore.case=TRUE)
~ "_pc",
grepl("\\$.*(million)*", unit, ignore.case=TRUE)
~ "_aud",
grepl("index", unit, ignore.case=TRUE)
~ "_ix",
grepl("proportion", unit, ignore.case=TRUE)
~ "_rt",
TRUE ~ ""))
);
}
## ana_series_abb <- function(x) {
## x %>%
## ## Series abbreviations
## mutate(series_abb = ifelse(grepl("^gross domestic product", data_item_description, ignore.case=TRUE),
## "gdp", "")) %>%
## mutate(series_abb = ifelse(grepl("^gdp", data_item_description, ignore.case=TRUE),
## "gdp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("^gross value added", data_item_description, ignore.case=TRUE),
## "gva", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("^net domestic product", data_item_description, ignore.case=TRUE),
## "ndp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("^net domestic product", data_item_description, ignore.case=TRUE),
## "ndp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross domestic income", data_item_description, ignore.case=TRUE),
## "gdi", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross national income", data_item_description, ignore.case=TRUE),
## "gni", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("net national disposable income", data_item_description, ignore.case=TRUE),
## "ndi", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("terms of trade", data_item_description, ignore.case=TRUE),
## "tot", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross national expenditure", data_item_description, ignore.case=TRUE),
## "gne", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("exports of goods and services", data_item_description, ignore.case=TRUE),
## "exp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("imports of goods and services", data_item_description, ignore.case=TRUE),
## "imp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("final consumption expenditure", data_item_description, ignore.case=TRUE),
## "fce", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross fixed capital formation", data_item_description, ignore.case=TRUE),
## "gfcf", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("state final demand", data_item_description, ignore.case=TRUE),
## "sfd", series_abb)) %>%
## ##
## ## Per capita series
## mutate(series_abb = ifelse(grepl("per capita", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "pc"), series_abb)) %>%
## ##
## ## Households, government, private, public
## mutate(series_abb = ifelse(grepl("general government", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_gov"), series_abb)) %>%
## ## -- General government options
## mutate(series_abb = ifelse(grepl("general government.+national",
## data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_nat"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("general government.+national.+defence",
## data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_def"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("general government.+national.+non-defence",
## data_item_description, ignore.case=TRUE),
## sub("_def", "_ndf", series_abb), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("general government.+state and local",
## data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_stl"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("households", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_hhld"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("all sectors", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_tot"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("private", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_priv"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("public", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_pub"), series_abb)) %>%
## ##
## ## States/territories
## mutate(series_abb = ifelse(grepl("new south wales", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_nsw"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("victoria", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_vic"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("queensland", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_qld"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("south australia", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_sa"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("western australia", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_wa"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("tasmania", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_tas"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("northern territory", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_nt"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("australian capital territory", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_act"), series_abb)) %>%
## ##
## ## Chain volume/current prices
## mutate(series_abb = ifelse(grepl("chain volume measures", data_item_description, ignore.case=TRUE) |
## grepl("chain volume measures", table_title, ignore.case=TRUE),
## paste0(series_abb, "_cv"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("current prices", data_item_description, ignore.case=TRUE) |
## grepl("current prices", table_title, ignore.case=TRUE),
## paste0(series_abb, "_cp"), series_abb)) %>%
## ##
## ## Original/seasonally adjusted/trend/index
## mutate(series_abb = ifelse(grepl("original", series_type, ignore.case=TRUE),
## paste0(series_abb, "_or"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("seasonally adjusted", series_type, ignore.case=TRUE),
## paste0(series_abb, "_sa"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("trend", series_type, ignore.case=TRUE),
## paste0(series_abb, "_tr"), series_abb)) %>%
## ##
## ## Percentage change/ratio/index
## mutate(series_abb = ifelse(grepl("percent", unit, ignore.case=TRUE),
## paste0(series_abb, "_pc"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("\\$.*million", unit, ignore.case=TRUE),
## paste0(series_abb, "_aud"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("index", unit, ignore.case=TRUE),
## paste0(series_abb, "_ix"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("proportion", unit, ignore.case=TRUE),
## paste0(series_abb, "_rt"), series_abb))
## }
## ppi_series_abb <- function(x) {
## x %>%
## ## Publication abbreviations
## mutate(series_abb = ifelse(grepl("^producer price indexes", publication_title, ignore.case=TRUE),
## "ppi", "")) %>%
## ## Sector abbreviations
## mutate(series_abb = ifelse(grepl("transport.+warehousing", table_title, ignore.case=TRUE),
## paste0(series_abb, "_tr"), series_abb)) %>%
## ## Series abbreviations
## mutate(series_abb =
## paste0(series_abb,
## case_when(grepl("road freight", data_item_description, ignore.case=TRUE) ~ "_rdfrt",
## grepl("urban bus", data_item_description, ignore.case=TRUE) ~ "_ubus",
## grepl("taxi", data_item_description, ignore.case=TRUE) ~ "_taxi",
## grepl("rail freight", data_item_description, ignore.case=TRUE) ~ "_rlfrt",
## grepl("water freight", data_item_description, ignore.case=TRUE) ~ "_wtfrt",
## grepl("pipeline", data_item_description, ignore.case=TRUE) ~ "_pipe",
## grepl("postal and courier", data_item_description, ignore.case=TRUE) ~ "_pstl",
## grepl("courier pick-up", data_item_description, ignore.case=TRUE) ~ "_cour",
## grepl("water transport support", data_item_description, ignore.case=TRUE) ~ "_wtspt",
## grepl("stevedoring", data_item_description, ignore.case=TRUE) ~ "_wtstv",
## grepl("port and water transport", data_item_description, ignore.case=TRUE) ~ "_wtprt",
## grepl("other water", data_item_description, ignore.case=TRUE) ~ "_wtoth",
## grepl("airport operations", data_item_description, ignore.case=TRUE) ~ "_arprt",
## grepl("customs agency", data_item_description, ignore.case=TRUE) ~ "_svcust",
## grepl("warehousing and storage", data_item_description, ignore.case=TRUE) ~ "_whgen",
## grepl("grain storage", data_item_description, ignore.case=TRUE) ~ "_whgrn",
## grepl("other warehousing", data_item_description, ignore.case=TRUE) ~ "_whoth",
## TRUE ~ ""))
## ) %>%
## ## Percentage change/ratio/index
## mutate(series_abb =
## paste0(series_abb,
## case_when(grepl("percent", unit, ignore.case=TRUE) ~ "_pc",
## grepl("\\$.*million", unit, ignore.case=TRUE) ~ "_aud",
## grepl("index", unit, ignore.case=TRUE) ~ "_ix",
## grepl("proportion", unit, ignore.case=TRUE) ~ "_rt",
## TRUE ~ ""))
## );
## }
## =============================== EOF =====================================
mitcda/raustats documentation built on Jan. 18, 2020, 12:36 p.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.
Defines functions ana_series_abb
## =========================================================================
## Filename:
## Created:
## Updated: <2019-06-19 10:46:32 david at grover>
## Author:
## Description:
##
##
## =========================================================================
#'
#' Table - ABS ANA Series IDs and series names
#'
#' ABS Series ID | Series abb | Series name
#' :---------------|:--------------|:--------------------------------------
#' A2304402X | gdp_cv_sa | GDP Chain Volume measures: Seasonally Adjusted
#' A2304340C | gdp_cv_tr | " : Trend
#' A2302459A | gdp_cv_or | " : Original
#' A2304408L | gdi_cv_sa | Gross Domestic Income, Chain Volume measures: Seasonally Adjusted
#' A2304342J | gdi_cv_tr | " : Trend
#' A2302463T | gdi_cv_or | " : Original
#' A2304412C | gni_cv_sa | GNI Chain Volume measures: Seasonally Adjusted
#' A2304344L | gni_cv_tr | " : Trend
#' A2302464V | gni_cv_or | " : Original
#' A2304414J | nndi_cv_sa | NNDI Chain Volume measures: Seasonally Adjusted
#' A2304346T | nndi_cv_tr | " : Trend
#' A2302465W | nndi_cv_or | " : Original
#' A2304404C | gdppc_cv_sa | GDP per capita Chain volume measures: Seasonally Adjusted
#' A2304336L | gdppc_cv_tr | " : Trend
#' A2302459A | gdppc_cv_or | " : Original
#' A2304113C | gne_cv_sa | GNE Chain Volume measures: Seasonally Adjusted
#' A2304237F | gne_cv_tr | " : Trend
#' A2302514F | gne_cv_or | " : Original
#' A2304111X | dfd_cv_sa | DFD Chain Volume measures: Seasonally Adjusted
#' A2304235A | dfd_cv_tr | " : Trend
#' A2302519T | dfd_cv_or | " : Original
#' A2304114F | exp_cv_sa | Exports Chain Volume measures: Seasonally Adjusted
#' A2304238J | exp_cv_tr | " : Trend
#' A2302520A | exp_cv_or | " : Original
#' A2304115J | imp_cv_sa | Imports Chain Volume measures: Seasonally Adjusted
#' A2304239K | imp_cv_sa | " : Trend
#' A2302521C | imp_cv_sa | " : Original
#'
#' Notes
#' GDI = GDP - ToT effects (GDI - Gross Domestic Income)
#' NNDI = ?? (NNDI - Net National Disposable Income)
#' DFD = GNE - Inventory change (DFD - Domestic Final Demand)
#'
#'
#### Add human-readable series model names (abbreviations)
## -- TO DO - INCLUDE IN ABS data package GENERAL FUNCTIONS
ana_series_abb <- function(x) {
x %>%
## Table abbreviations
mutate(series_abb =
case_when(grepl("^key national accounts aggregates", table_title, ignore.case=TRUE)
~ "ana",
grepl("^expenditure.+GDP", table_title, ignore.case=TRUE)
~ "gdpe",
grepl("^income from.+GDP", table_title, ignore.case=TRUE)
~ "gdpi",
grepl("^gross value added.+industry", table_title, ignore.case=TRUE)
~ "gva",
grepl("^gross value added.+industry.+current price", table_title, ignore.case=TRUE)
~ "gvacp",
grepl("^household.*final.*consumption.*expenditure", table_title, ignore.case=TRUE)
~ "hfce",
TRUE ~ ""),
## Series abbreviations
series_abb =
paste0(series_abb,
case_when(grepl("^gross domestic product", data_item_description, ignore.case=TRUE)
~ "_gdp",
grepl("^gdp", data_item_description, ignore.case=TRUE)
~ "_gdp",
grepl("^gross value added", data_item_description, ignore.case=TRUE)
~ "_gva",
grepl("^net domestic product", data_item_description, ignore.case=TRUE)
~ "_ndp",
grepl("^net domestic product", data_item_description, ignore.case=TRUE)
~ "_ndp",
grepl("gross domestic income", data_item_description, ignore.case=TRUE)
~ "_gdi",
grepl("gross national income", data_item_description, ignore.case=TRUE)
~ "_gni",
grepl("net national disposable income", data_item_description, ignore.case=TRUE)
~ "_ndi",
grepl("terms of trade", data_item_description, ignore.case=TRUE)
~ "_tot",
grepl("gross national expenditure", data_item_description, ignore.case=TRUE)
~ "_gne",
grepl("exports of goods and services", data_item_description, ignore.case=TRUE)
~ "_exp",
grepl("imports of goods and services", data_item_description, ignore.case=TRUE)
~ "_imp",
grepl("domestic final demand", data_item_description, ignore.case=TRUE)
~ "_dfd",
grepl("change.+inventories", data_item_description, ignore.case=TRUE)
~ "_chinv",
grepl("final consumption expenditure", data_item_description, ignore.case=TRUE)
~ "_fce",
grepl("gross fixed capital formation", data_item_description, ignore.case=TRUE)
~ "_gfcf",
grepl("state final demand", data_item_description, ignore.case=TRUE)
~ "_sfd",
grepl("hours worked market sector", data_item_description, ignore.case=TRUE)
~ "_hrsmk",
grepl("hours worked", data_item_description, ignore.case=TRUE)
~ "_hrstl",
grepl("real unit.*labour cost.*non.*farm", data_item_description, ignore.case=TRUE)
~ "_rulcnf",
grepl("real unit.*labour cost.*", data_item_description, ignore.case=TRUE)
~ "_rulc",
grepl("household saving ratio", data_item_description, ignore.case=TRUE)
~ "_hsr",
grepl("net saving", data_item_description, ignore.case=TRUE)
~ "_netsav",
grepl("statistical discrepancy", data_item_description, ignore.case=TRUE)
~ "_statdis",
## Industry gross value added
## grepl(sprintf("\\(%s\\)\\s*;", paste(letters, collapse="|")),
## data_item_description, ignore.case=TRUE)
## ~ sub(sprintf(".+\\((%s)\\)\\s*;.*", paste(letters, collapse="|")),
## tolower("_div\\1"), data_item_description, ignore.case=TRUE),
## Division A - Agriculture, forestry & fishing
grepl("\\(a\\).+Agriculture", data_item_description, ignore.case=TRUE)
~ "_diva_ag",
grepl("\\(a\\).+Forestry.*fishing", data_item_description, ignore.case=TRUE)
~ "_diva_ff",
grepl("\\(a\\).+;$", data_item_description, ignore.case=TRUE)
~ "_diva_tot",
## Division B - Mining
grepl("\\(b\\).+coal.*mining", data_item_description, ignore.case=TRUE)
~ "_divb_cl",
grepl("\\(b\\).+oil.*gas", data_item_description, ignore.case=TRUE)
~ "_divb_og",
grepl("\\(b\\).+iron.*ore", data_item_description, ignore.case=TRUE)
~ "_divb_fe",
grepl("\\(b\\).+other.*mining", data_item_description, ignore.case=TRUE)
~ "_divb_ot",
grepl("\\(b\\).+mining.*excluding.*exploration", data_item_description,
ignore.case=TRUE)
~ "_divb_mn",
grepl("\\(b\\).+exploration.*support", data_item_description,
ignore.case=TRUE)
~ "_divb_es",
grepl("\\(b\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divb_tot",
## Division C - Manufacturing
grepl("\\(c\\).+food.*beverage", data_item_description, ignore.case=TRUE)
~ "_divc_fb",
grepl("\\(c\\).+petroleum.*coal", data_item_description, ignore.case=TRUE)
~ "_divc_pc",
grepl("\\(c\\).+metal.*products", data_item_description, ignore.case=TRUE)
~ "_divc_mt",
grepl("\\(c\\).+machinery.*equipment", data_item_description, ignore.case=TRUE)
~ "_divc_mc",
grepl("\\(c\\).+other.*manufacturing", data_item_description,
ignore.case=TRUE)
~ "_divc_ot",
grepl("\\(c\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divc_tot",
## Division D - Utilities
grepl("\\(d\\).+electricity", data_item_description, ignore.case=TRUE)
~ "_divd_el",
grepl("\\(d\\).+gas", data_item_description, ignore.case=TRUE)
~ "_divd_gs",
grepl("\\(d\\).+water.*supply", data_item_description, ignore.case=TRUE)
~ "_divd_wt",
grepl("\\(d\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divd_tot",
## Division E - Construction
grepl("\\(e\\).+building.*construction", data_item_description, ignore.case=TRUE)
~ "_dive_bc",
grepl("\\(e\\).+civil.*engineering", data_item_description, ignore.case=TRUE)
~ "_dive_ce",
grepl("\\(e\\).+construction.*services", data_item_description, ignore.case=TRUE)
~ "_dive_cs",
grepl("\\(e\\).+;$", data_item_description, ignore.case=TRUE)
~ "_dive_tot",
## Division F - Wholesale trade
grepl("\\(f\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divf_tot",
## Division G - Retail trade
grepl("\\(g\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divg_tot",
## Division H - Accommodation & food services
grepl("\\(h\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divh_tot",
## Division I - Transport
grepl("\\(i\\).+road", data_item_description, ignore.case=TRUE)
~ "_divi_rd",
grepl("\\(i\\).+air.*space", data_item_description, ignore.case=TRUE)
~ "_divi_as",
grepl("\\(i\\).+rail.*pipeline", data_item_description, ignore.case=TRUE)
~ "_divi_rl",
grepl("\\(i\\).+postal.*storage", data_item_description, ignore.case=TRUE)
~ "_divi_ps",
grepl("\\(i\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divi_tot",
## Division J - Telecommunications
grepl("\\(j\\).+telecommunications", data_item_description, ignore.case=TRUE)
~ "_divj_tl",
grepl("\\(j\\).+other.*information", data_item_description, ignore.case=TRUE)
~ "_divj_ot",
grepl("\\(j\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divj_tot",
## Division K - Finance & insurance
grepl("\\(k\\).+finance", data_item_description, ignore.case=TRUE)
~ "_divk_fn",
grepl("\\(k\\).+other.*financial", data_item_description, ignore.case=TRUE)
~ "_divk_ot",
grepl("\\(k\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divk_tot",
## Division L - Rental, hiring & real estate
grepl("\\(l\\).+rental.*hiring", data_item_description, ignore.case=TRUE)
~ "_divl_rh",
grepl("\\(l\\).+real.*estate", data_item_description, ignore.case=TRUE)
~ "_divl_re",
grepl("\\(l\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divl_tot",
## Division M - Professional and scientific services
grepl("\\(m\\).+computer.*system", data_item_description, ignore.case=TRUE)
~ "_divm_cs",
grepl("\\(m\\).+other.*professional", data_item_description, ignore.case=TRUE)
~ "_divm_op",
grepl("\\(m\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divm_tot",
## Division N - Administrative & support services
grepl("\\(n\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divn_tot",
## Division O - Public administration & safety
grepl("\\(o\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divo_tot",
## Division P - Education and training
grepl("\\(p\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divp_tot",
## Division Q - Health care & social assistance
grepl("\\(q\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divq_tot",
## Division R - Arts and recreation services
grepl("\\(r\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divr_tot",
## Division S - Other services
grepl("\\(s\\).+;$", data_item_description, ignore.case=TRUE)
~ "_divs_tot",
## Ownership of dwellings
grepl("ownership.*dwellings", data_item_description, ignore.case=TRUE)
~ "_dwell",
grepl("taxes less subsidies", data_item_description, ignore.case=TRUE)
~ "_nettax",
grepl("gross value added at basi prices taxes less", data_item_description,
ignore.case=TRUE)
~ "_nettax",
## Household Final Consumption Expenditure items
grepl("Food", data_item_description, ignore.case=TRUE)
~ "_01_food",
grepl("Alcoholic.*beverage.*cigarettes.*tobacco", data_item_description,
ignore.case=TRUE)
~ "_02_albt",
grepl("Cigarettes.*tobacco", data_item_description, ignore.case=TRUE)
~ "_02a_tabc",
grepl("Alcoholic.*beverage", data_item_description, ignore.case=TRUE)
~ "_02b_abev",
grepl("Clothing.*footwear", data_item_description, ignore.case=TRUE)
~ "_03_clft",
grepl("Housing.*water.*electricity.*gas", data_item_description, ignore.case=TRUE)
~ "_04_hhsv",
grepl("Rent.*other.*dwelling.*services", data_item_description, ignore.case=TRUE)
~ "_04a_rnts",
grepl("Actual.*imputed.*rent", data_item_description, ignore.case=TRUE)
~ "_04b_rent",
grepl("Electricity.*gas.*other.*fuel", data_item_description, ignore.case=TRUE)
~ "_04c_util",
grepl("Water.*sewerage.*charges", data_item_description, ignore.case=TRUE)
~ "_04d_watr",
grepl("Furnishings.*household.*equip", data_item_description, ignore.case=TRUE)
~ "_05_furn",
grepl("Furniture.*floor.*coverings", data_item_description, ignore.case=TRUE)
~ "_05a_furn",
grepl("Household.*appliances", data_item_description, ignore.case=TRUE)
~ "_05b_appl",
grepl("Household.*tools", data_item_description, ignore.case=TRUE)
~ "_05c_tool",
grepl("Health", data_item_description, ignore.case=TRUE)
~ "_06_hlth",
grepl("Medicines", data_item_description, ignore.case=TRUE)
~ "_06a_hlth",
grepl("Total.*health.*services", data_item_description, ignore.case=TRUE)
~ "_06b_hlth",
grepl("Purchase.*vehicles", data_item_description, ignore.case=TRUE)
~ "_07a_vcpx",
grepl("Operation.*vehicles", data_item_description, ignore.case=TRUE)
~ "_07b_vopx",
grepl("Transport.*services", data_item_description, ignore.case=TRUE)
~ "_07c_tran",
grepl("Transport", data_item_description, ignore.case=TRUE)
~ "_07_tran",
grepl("Communications", data_item_description, ignore.case=TRUE)
~ "_08_comm",
grepl("Goods.*for.*recreation.*culture", data_item_description, ignore.case=TRUE)
~ "_09a_recg",
grepl("^Recreational.*cultural.*services", data_item_description,
ignore.case=TRUE)
~ "_09b_recs",
grepl("Sporting.*recreational.*cultural.*services", data_item_description,
ignore.case=TRUE)
~ "_09c_sprt",
grepl("Net.*losses.*gambling", data_item_description, ignore.case=TRUE)
~ "_09d_gamb",
grepl("Newspapers.*books.*stationery", data_item_description, ignore.case=TRUE)
~ "_09e_news",
grepl("Recreation.*culture", data_item_description, ignore.case=TRUE)
~ "_09_recc",
grepl("Education.*services", data_item_description, ignore.case=TRUE)
~ "_10_educ",
grepl("Hotels.*cafes.*restaurants", data_item_description, ignore.case=TRUE)
~ "_11_acrs",
grepl("Catering.*services", data_item_description, ignore.case=TRUE)
~ "_11a_cats",
grepl("Accommodation.*services", data_item_description, ignore.case=TRUE)
~ "_11b_accs",
grepl("Miscellaneous.*goods.*services", data_item_description, ignore.case=TRUE)
~ "_12_misc",
grepl("Other.*goods", data_item_description, ignore.case=TRUE)
~ "_12a_othg",
grepl("Insurance.*financial.*services", data_item_description, ignore.case=TRUE)
~ "_12b_fins",
grepl("Other.*services", data_item_description, ignore.case=TRUE)
~ "_12c_oths",
grepl("Net.*expenditure.*overseas", data_item_description, ignore.case=TRUE)
~ "_neo",
grepl("Final.*consumption.*expenditure", data_item_description, ignore.case=TRUE)
~ "_totc",
TRUE ~ "")),
##
## Per capita/hour worked series
series_abb = paste0(series_abb,
case_when(grepl("per capita", data_item_description, ignore.case=TRUE)
~ "pc",
grepl("per hour", data_item_description, ignore.case=TRUE)
~ "ph",
TRUE ~ "")),
##
## Households, government, private, public
series_abb = paste0(series_abb,
case_when(grepl("general government", data_item_description, ignore.case=TRUE)
~ "_gov",
TRUE ~ "")),
## -- General government options
series_abb = paste0(series_abb,
case_when(grepl("general government",
data_item_description, ignore.case=TRUE) ~ "_gov",
grepl("general government.+national",
data_item_description, ignore.case=TRUE) ~ "_nat",
grepl("general government.+national.+non-defence",
data_item_description, ignore.case=TRUE) ~ "_ndf",
grepl("general government.+national.+defence",
data_item_description, ignore.case=TRUE) ~ "_def",
grepl("general government.+state and local",
data_item_description, ignore.case=TRUE) ~ "_stl",
grepl("households",
data_item_description, ignore.case=TRUE) ~ "_hhld",
grepl("all sectors",
data_item_description, ignore.case=TRUE) ~ "_tot",
grepl("private",
data_item_description, ignore.case=TRUE) ~ "_priv",
grepl("public", data_item_description, ignore.case=TRUE)
~ "_pub",
TRUE ~ "")),
##
## States/territories
series_abb = paste0(series_abb,
case_when(grepl("new south wales",
data_item_description, ignore.case=TRUE)
~ "_nsw",
grepl("victoria", data_item_description, ignore.case=TRUE)
~ "_vic",
grepl("queensland", data_item_description, ignore.case=TRUE)
~ "_qld",
grepl("south australia", data_item_description, ignore.case=TRUE)
~ "_sa",
grepl("western australia", data_item_description, ignore.case=TRUE)
~ "_wa",
grepl("tasmania", data_item_description, ignore.case=TRUE)
~ "_tas",
grepl("northern territory", data_item_description, ignore.case=TRUE)
~ "_nt",
grepl("australian capital territory", data_item_description, ignore.case=TRUE)
~ "_act",
TRUE ~ "")),
##
## Chain volume/current prices
series_abb = paste0(series_abb,
case_when(grepl("chain volume measures", data_item_description, ignore.case=TRUE) |
grepl("chain volume measures", table_title, ignore.case=TRUE)
~ "_cv",
grepl("current prices", data_item_description, ignore.case=TRUE) |
grepl("current prices", table_title, ignore.case=TRUE)
~ "_cp",
grepl("price indexes", data_item_description, ignore.case=TRUE) |
grepl("price indexes", table_title, ignore.case=TRUE)
~ "_ix",
grepl("implicit price deflators", data_item_description, ignore.case=TRUE) |
grepl("implicit price deflators", table_title, ignore.case=TRUE)
~ "_pd",
TRUE ~ "")),
##
## Original/seasonally adjusted/trend/index
series_abb = paste0(series_abb,
case_when(grepl("original", series_type, ignore.case=TRUE)
~ "_or",
grepl("seasonally adjusted", series_type, ignore.case=TRUE)
~ "_sa",
grepl("trend", series_type, ignore.case=TRUE)
~ "_tr",
TRUE ~ "")),
##
## Percentage change/ratio/index
series_abb = paste0(series_abb,
case_when(grepl("percent", unit, ignore.case=TRUE)
~ "_pc",
grepl("\\$.*(million)*", unit, ignore.case=TRUE)
~ "_aud",
grepl("index", unit, ignore.case=TRUE)
~ "_ix",
grepl("proportion", unit, ignore.case=TRUE)
~ "_rt",
TRUE ~ ""))
);
}
## ana_series_abb <- function(x) {
## x %>%
## ## Series abbreviations
## mutate(series_abb = ifelse(grepl("^gross domestic product", data_item_description, ignore.case=TRUE),
## "gdp", "")) %>%
## mutate(series_abb = ifelse(grepl("^gdp", data_item_description, ignore.case=TRUE),
## "gdp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("^gross value added", data_item_description, ignore.case=TRUE),
## "gva", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("^net domestic product", data_item_description, ignore.case=TRUE),
## "ndp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("^net domestic product", data_item_description, ignore.case=TRUE),
## "ndp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross domestic income", data_item_description, ignore.case=TRUE),
## "gdi", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross national income", data_item_description, ignore.case=TRUE),
## "gni", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("net national disposable income", data_item_description, ignore.case=TRUE),
## "ndi", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("terms of trade", data_item_description, ignore.case=TRUE),
## "tot", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross national expenditure", data_item_description, ignore.case=TRUE),
## "gne", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("exports of goods and services", data_item_description, ignore.case=TRUE),
## "exp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("imports of goods and services", data_item_description, ignore.case=TRUE),
## "imp", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("final consumption expenditure", data_item_description, ignore.case=TRUE),
## "fce", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("gross fixed capital formation", data_item_description, ignore.case=TRUE),
## "gfcf", series_abb)) %>%
## mutate(series_abb = ifelse(grepl("state final demand", data_item_description, ignore.case=TRUE),
## "sfd", series_abb)) %>%
## ##
## ## Per capita series
## mutate(series_abb = ifelse(grepl("per capita", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "pc"), series_abb)) %>%
## ##
## ## Households, government, private, public
## mutate(series_abb = ifelse(grepl("general government", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_gov"), series_abb)) %>%
## ## -- General government options
## mutate(series_abb = ifelse(grepl("general government.+national",
## data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_nat"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("general government.+national.+defence",
## data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_def"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("general government.+national.+non-defence",
## data_item_description, ignore.case=TRUE),
## sub("_def", "_ndf", series_abb), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("general government.+state and local",
## data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_stl"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("households", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_hhld"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("all sectors", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_tot"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("private", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_priv"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("public", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_pub"), series_abb)) %>%
## ##
## ## States/territories
## mutate(series_abb = ifelse(grepl("new south wales", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_nsw"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("victoria", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_vic"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("queensland", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_qld"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("south australia", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_sa"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("western australia", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_wa"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("tasmania", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_tas"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("northern territory", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_nt"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("australian capital territory", data_item_description, ignore.case=TRUE),
## paste0(series_abb, "_act"), series_abb)) %>%
## ##
## ## Chain volume/current prices
## mutate(series_abb = ifelse(grepl("chain volume measures", data_item_description, ignore.case=TRUE) |
## grepl("chain volume measures", table_title, ignore.case=TRUE),
## paste0(series_abb, "_cv"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("current prices", data_item_description, ignore.case=TRUE) |
## grepl("current prices", table_title, ignore.case=TRUE),
## paste0(series_abb, "_cp"), series_abb)) %>%
## ##
## ## Original/seasonally adjusted/trend/index
## mutate(series_abb = ifelse(grepl("original", series_type, ignore.case=TRUE),
## paste0(series_abb, "_or"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("seasonally adjusted", series_type, ignore.case=TRUE),
## paste0(series_abb, "_sa"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("trend", series_type, ignore.case=TRUE),
## paste0(series_abb, "_tr"), series_abb)) %>%
## ##
## ## Percentage change/ratio/index
## mutate(series_abb = ifelse(grepl("percent", unit, ignore.case=TRUE),
## paste0(series_abb, "_pc"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("\\$.*million", unit, ignore.case=TRUE),
## paste0(series_abb, "_aud"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("index", unit, ignore.case=TRUE),
## paste0(series_abb, "_ix"), series_abb)) %>%
## mutate(series_abb = ifelse(grepl("proportion", unit, ignore.case=TRUE),
## paste0(series_abb, "_rt"), series_abb))
## }
## ppi_series_abb <- function(x) {
## x %>%
## ## Publication abbreviations
## mutate(series_abb = ifelse(grepl("^producer price indexes", publication_title, ignore.case=TRUE),
## "ppi", "")) %>%
## ## Sector abbreviations
## mutate(series_abb = ifelse(grepl("transport.+warehousing", table_title, ignore.case=TRUE),
## paste0(series_abb, "_tr"), series_abb)) %>%
## ## Series abbreviations
## mutate(series_abb =
## paste0(series_abb,
## case_when(grepl("road freight", data_item_description, ignore.case=TRUE) ~ "_rdfrt",
## grepl("urban bus", data_item_description, ignore.case=TRUE) ~ "_ubus",
## grepl("taxi", data_item_description, ignore.case=TRUE) ~ "_taxi",
## grepl("rail freight", data_item_description, ignore.case=TRUE) ~ "_rlfrt",
## grepl("water freight", data_item_description, ignore.case=TRUE) ~ "_wtfrt",
## grepl("pipeline", data_item_description, ignore.case=TRUE) ~ "_pipe",
## grepl("postal and courier", data_item_description, ignore.case=TRUE) ~ "_pstl",
## grepl("courier pick-up", data_item_description, ignore.case=TRUE) ~ "_cour",
## grepl("water transport support", data_item_description, ignore.case=TRUE) ~ "_wtspt",
## grepl("stevedoring", data_item_description, ignore.case=TRUE) ~ "_wtstv",
## grepl("port and water transport", data_item_description, ignore.case=TRUE) ~ "_wtprt",
## grepl("other water", data_item_description, ignore.case=TRUE) ~ "_wtoth",
## grepl("airport operations", data_item_description, ignore.case=TRUE) ~ "_arprt",
## grepl("customs agency", data_item_description, ignore.case=TRUE) ~ "_svcust",
## grepl("warehousing and storage", data_item_description, ignore.case=TRUE) ~ "_whgen",
## grepl("grain storage", data_item_description, ignore.case=TRUE) ~ "_whgrn",
## grepl("other warehousing", data_item_description, ignore.case=TRUE) ~ "_whoth",
## TRUE ~ ""))
## ) %>%
## ## Percentage change/ratio/index
## mutate(series_abb =
## paste0(series_abb,
## case_when(grepl("percent", unit, ignore.case=TRUE) ~ "_pc",
## grepl("\\$.*million", unit, ignore.case=TRUE) ~ "_aud",
## grepl("index", unit, ignore.case=TRUE) ~ "_ix",
## grepl("proportion", unit, ignore.case=TRUE) ~ "_rt",
## TRUE ~ ""))
## );
## }
## =============================== EOF =====================================
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.