R/prepare_ilo.r
In dbescond/Ariane: Ariane package internal functions for ILO Statistics department
Defines functions
prepare_segment_ilo
prepare_segment_ilo2
prepare_codelist_ilo
prepare_setting_ilo
Documented in
prepare_segment_ilo
#' Prepare ilo packages
#'
#' fix utf-8 encoding bug
#'
#' Helper function to efficiently query data from ILOSTAT SDMX API.
#'
#' @param X data frame.
#' @param DELETE in deletion format, default is FALSE.
#' @param LABEL add label to the notes, default is FALSE.
#' @author ILO bescond
#' @keywords ILO, R
#' @export
#' @rdname prepare_ilo
prepare_segment_ilo <- function(FREQ, DBNAme, query, cou){
e <- new.env()
for (i in 1:length(cou)){
X <- readRDS(paste0(ilo:::path$sys, 'ILO_Data/ORA/',query, '_', cou[i],'_',FREQ, '.rds'))%>%
mutate_all(funs(as.character))%>%
mutate(obs_value = as.numeric(obs_value)) %>%
select(-sex_version, -classif1_version, -classif2_version)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
if(nrow(X)>0){
X <- X %>%
select(source, indicator, sex:obs_status, note_classif, note_indicator, note_source, info)
if(!FREQ %in% c('M','Q') ){
X <- X %>% mutate(time = as.numeric(time))
}
invisible(gc(reset = TRUE))
assign(cou[i],X ,e)
print(cou[i])
}
rm(X)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
}
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
getwd()
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
aa <- file.size(paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdb'))
print(aa)
if(aa == 0){
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdb'))
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdx'))
} else{
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdb'), to = paste0(ilo:::path$tools, 'R/data/data/cou/', DBNAme, '.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdx'), to = paste0(ilo:::path$tools, 'R/data/data/cou/', DBNAme, '.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
invisible(gc(reset = TRUE))
}
}
#' @export
prepare_segment_ilo2 <- function(FREQ, DBNAme, query, cou){
e <- new.env()
DB <- NULL
for (i in 1:length(cou)){
X <- readRDS(paste0(ilo:::path$sys, 'ILO_Data/ORA/',query, '_', cou[i],'_',FREQ, '.rds'))%>%
mutate_all(funs(as.character))%>%
mutate(obs_value = as.numeric(obs_value)) %>%
select(-sex_version, -classif1_version, -classif2_version)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
if(nrow(X)>0){
X <- X %>%
select(ref_area, source, indicator, sex:obs_status, note_classif, note_indicator, note_source, info)
if(!FREQ %in% c('M','Q') ){
X <- X %>% mutate(time = as.numeric(time))
}
invisible(gc(reset = TRUE))
#
DB <- bind_rows(DB, X)
}
rm(X)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
}
test <- DB %>% count(indicator) %>% left_join(Ariane:::CODE_ORA$T_IND_INDICATOR %>% select(indicator = IND_CODE, IND_SORT), by = 'indicator') %>% arrange(IND_SORT) %>% .$indicator
for (i in 1:length(test)){
X <- DB %>% filter(indicator %in% test[i]) %>% select(-indicator)
assign(test[i],X ,e)
rm(X)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
DB <- DB %>% filter(!indicator %in% test[i])
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
print(test[i])
}
rm(DB)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
getwd()
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
aa <- file.size(paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdb'))
print(aa)
if(aa == 0){
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdb'))
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdx'))
} else{
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdb'), to = paste0(ilo:::path$tools, 'R/data/data/ind/', DBNAme, '.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdx'), to = paste0(ilo:::path$tools, 'R/data/data/ind/', DBNAme, '.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
invisible(gc(reset = TRUE))
}
}
#' @export
prepare_codelist_ilo <- function(){
e <- new.env()
CODE <- Ariane:::CODE_ORA
code <- c("T_CLA_CLASSIF",
"T_DTS_DATASET",
"T_CIS_COL_IND_SRC",
"T_CIN_COL_IND",
"T_CIC_COL_IND_CLV",
"T_COL_COLLECTION",
"T_CLT_CODELIST",
"T_CLV_CLASSIF_VERSION",
"T_CLY_CLASSIF_TYPE",
"T_COU_COUNTRY",
"T_CUR_CURRENCY",
"T_GRP_GROUP",
"T_CBG_COUNTRY_BY_GROUP",
"T_IND_INDICATOR",
"T_NTE_NOTE",
"T_NTY_NOTE_TYPE",
"T_SRC_SOURCE",
"T_SUR_SURVEY",
"T_TOP_TOPIC",
"T_USR_USER",
"T_RVA_REPRESENTED_VARIABLE",
"T_SGR_SRC_GROUP",
"T_SUI_SUBJECT_INDICATOR",
"T_DCO_DATASET_COLLECTION",
"T_SUB_SUBJECT",
"T_NRD_NOTE_REMOVED_DISSEM"
)
CODE <- CODE[names(CODE) %in% code]
COU <- readxl::read_excel(paste0(ilo:::path$sys, 'ILO_Meta/REGION.xlsx'), sheet = 'Consolidation') %>% select(ilo_code, ISO3_CODE)
CODE$T_DCO_DATASET_COLLECTION <- CODE$T_DCO_DATASET_COLLECTION %>%
left_join(CODE$T_DTS_DATASET %>% select(DCO_DATASET_ID = DTS_ID, dataset = DTS_CODE)) %>%
left_join(CODE$T_COL_COLLECTION %>% select(DCO_COLLECTION_ID = COL_ID, collection = COL_CODE)) %>% select(-contains('_ID'))
CL_DTS_DATASET <- CODE$T_DTS_DATASET %>% select(-contains("_ID")) %>%
rename( code = DTS_CODE,
label_en = DTS_TEXT_EN,
label_fr = DTS_TEXT_FR,
label_es = DTS_TEXT_SP,
description_en = DTS_DESCR_EN,
description_fr = DTS_DESCR_FR,
description_es = DTS_DESCR_SP,
sort = DTS_SORT ) %>%
mutate(sort = as.numeric(sort),
code = str_sub(code, 1,2)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_USR_USER <- CODE$T_USR_USER %>% select(USR_ID, USR_LASTNAME) %>%
rename( code = USR_ID,
label_en = USR_LASTNAME ) %>%
mutate(sort = 1:n(),
label_en = tolower(paste0(str_sub(label_en, 1,1), str_sub(label_en, -2,-1), sep = ''))) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_CLV_CLASSIF_VERSION <- CODE$T_CLV_CLASSIF_VERSION %>% select(-contains("_ID"), -contains("CLV_SHORT"), -CLV_CLASSIF_TYPE_CODE, -contains("CLV_DESCR"), -CLV_IS_EDITABLE, -CLV_IS_DISSEMINATED) %>%
mutate_all(funs(as.character) ) %>%
mutate(CLV_SORT = as.numeric(CLV_SORT)) %>%
rename( code = CLV_CODE,
label_en = CLV_TEXT_EN,
label_fr = CLV_TEXT_FR,
label_es = CLV_TEXT_SP,
sort = CLV_SORT ) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_CLA_CLASSIF <- CODE$T_CLA_CLASSIF %>% select(-contains("_ID"), -contains("CLA_LEVEL"), -CLA_DETAILS, -CLA_IS_DEFAULT, -CLA_IS_TOTAL ,-CLA_IS_VALIDATE ) %>%
mutate_all(funs(as.character) ) %>%
mutate(CLA_SORT = as.numeric(CLA_SORT)) %>%
rename( code = CLA_CODE,
label_en_1 = CLA_TEXT_EN,
label_fr_1 = CLA_TEXT_FR,
label_es_1 = CLA_TEXT_SP,
sort = CLA_SORT ) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
left_join(select(CODE$T_CLV_CLASSIF_VERSION,
CLA_VERSION_CODE = code,
label_en_T = label_en,
label_fr_T = label_fr,
label_es_T = label_es),
by = 'CLA_VERSION_CODE') %>%
unite(label_en, label_en_T, label_en_1, sep=": ", remove = TRUE) %>%
unite(label_fr, label_fr_T, label_fr_1, sep=": ", remove = TRUE) %>%
unite(label_es, label_es_T, label_es_1, sep=": ", remove = TRUE) %>%
select(-CLA_VERSION_CODE) %>%
mutate(sort = 1:n())
CODE$T_CLY_CLASSIF_TYPE <- CODE$T_CLY_CLASSIF_TYPE %>% select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
mutate(CLY_SORT = as.numeric(CLY_SORT)) %>%
rename( code = CLY_CODE,
label_en = CLY_TEXT_EN,
label_fr = CLY_TEXT_FR,
label_es = CLY_TEXT_SP,
description_en = CLY_DESCR_EN,
description_fr = CLY_DESCR_FR,
description_es = CLY_DESCR_SP,
sort = CLY_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_COU_COUNTRY <- CODE$T_COU_COUNTRY %>%
select(-contains("_ID"), -COU_IS_ILOMEMBER, -COU_IS_RECEIVING_QUEST, -COU_CALLING_CODE)%>%
mutate_all(funs(as.character)) %>%
rename( code = COU_ISO3_CODE,
label_en = COU_TEXT_EN,
label_fr = COU_TEXT_FR,
label_es = COU_TEXT_SP,
sort = COU_SORT_EN) %>%
mutate(sort = as.numeric(sort),
code_iso2 = COU_ISO2_CODE,
code_iso3n = as.numeric(as.character(COU_ISO3N_CODE))) %>%
arrange(sort) %>% select(-COU_SORT_FR, -COU_SORT_SP, -COU_ONU_CODE, -COU_ISO3N_CODE, -COU_ISO2_CODE) %>%
mutate(sort = 1:n()) %>%
left_join(COU %>% select(code = ISO3_CODE, ilo_code))
CODE$T_GRP_GROUP <- CODE$T_GRP_GROUP %>% select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
rename( code = GRP_CODE,
label_en = GRP_TEXT_EN,
label_fr = GRP_TEXT_FR,
label_es = GRP_TEXT_SP
) %>% mutate(sort = 1:n(), sort = as.numeric(sort))
CODE$T_CBG_COUNTRY_BY_GROUP <- CODE$T_CBG_COUNTRY_BY_GROUP %>%
select(-contains("_ID")) %>%
mutate_all(funs(as.character)) %>%
rename( code = CBG_GROUP_CODE,
code_country = CBG_COUNTRY_CODE)
CL_COL_IND_SRC <- CODE$T_CIS_COL_IND_SRC %>%
left_join(CODE$T_CIN_COL_IND %>%
select(CIS_CIN_ID = CIN_ID, CIN_COLLECTION_ID, CIN_INDICATOR_ID), by = "CIS_CIN_ID") %>%
left_join(CODE$T_IND_INDICATOR %>%
select(CIN_INDICATOR_ID = IND_ID, IND_CODE), by = c("IND_CODE", "CIN_INDICATOR_ID")) %>%
left_join(CODE$T_COL_COLLECTION %>%
select(CIN_COLLECTION_ID = COL_ID, COL_CODE ), by = c("COL_CODE", "CIN_COLLECTION_ID")) %>%
left_join(CODE$T_SRC_SOURCE %>%
select(CIS_SOURCE_ID = SRC_ID, SRC_CODE ), by = c("CIS_SOURCE_ID", "SRC_CODE")) %>%
select(contains('_CODE')) %>%
rename(indicator = IND_CODE, collection = COL_CODE, source = SRC_CODE)
CL_COL_IND_CLV <- CODE$T_CIC_COL_IND_CLV %>%
select(contains('_CODE'), CIC_IS_DISSEM)
colnames(CL_COL_IND_CLV) <- c('collection','indicator','classif_vs', 'dissem')
CL_SUB_IND <- CODE$T_SUI_SUBJECT_INDICATOR %>%
left_join(CODE$T_IND_INDICATOR %>%
select(SUI_INDICATOR_ID = IND_ID, IND_CODE), by = c("SUI_INDICATOR_ID", "IND_CODE")) %>%
left_join(CODE$T_SUB_SUBJECT %>%
select(SUI_SUBJECT_ID = SUB_ID, SUB_CODE ), by = c("SUI_SUBJECT_ID", "SUB_CODE")) %>%
select(contains('CODE')) %>%
rename(indicator = IND_CODE, subject = SUB_CODE)
CL_COL_IND <- CL_COL_IND_CLV %>% distinct(collection, indicator)
CODE$T_IND_INDICATOR <- CODE$T_IND_INDICATOR %>%
select(-contains("_ID"), -contains("_LEVEL"), -IND_UNIT_MULT_CODE)%>%
mutate_all(funs(as.character) ) %>%
mutate(IND_SORT = as.numeric(IND_SORT)) %>%
select(-IND_IS_LABORSTA, -IND_INSTR_EN, -IND_INSTR_FR, -IND_INSTR_SP, -IND_HOT_INDICATOR_RANKING, -IND_HEADER_EN, -IND_HEADER_FR, -IND_HEADER_SP, -IND_UNIT_MEASURE_TYPE_CODE) %>%
rename( code = IND_CODE,
label_en = IND_TEXT_EN,
label_fr = IND_TEXT_FR,
label_es = IND_TEXT_SP,
description_en = IND_DESCR_EN,
description_fr = IND_DESCR_FR,
description_es = IND_DESCR_SP,
decimal = IND_DECIMAL,
code_Measure = IND_UNIT_MEASURE_CODE,
sort = IND_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_TOP_TOPIC <- CODE$T_TOP_TOPIC %>% select(-contains("_ID"), -contains("_INSTR_")) %>%
mutate_all(funs(as.character) ) %>%
mutate(TOP_SORT = as.numeric(TOP_SORT)) %>%
rename( code = TOP_CODE,
label_en = TOP_TEXT_EN,
label_fr = TOP_TEXT_FR,
label_es = TOP_TEXT_SP,
description_en = TOP_DESCR_EN,
description_fr = TOP_DESCR_FR,
description_es = TOP_DESCR_SP,
sort = TOP_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_RVA_REPRESENTED_VARIABLE <- CODE$T_RVA_REPRESENTED_VARIABLE %>%
select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
mutate(RVA_SORT = as.numeric(RVA_SORT)) %>%
rename( code = RVA_CODE,
label_en = RVA_TEXT_EN,
label_fr = RVA_TEXT_FR,
label_es = RVA_TEXT_SP,
description_en = RVA_DESCR_EN,
description_fr = RVA_DESCR_FR,
description_es = RVA_DESCR_SP,
sort = RVA_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_INDICATOR_UNIT <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "UNIT_MEASURE") %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate( sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_INDICATOR_TYPE <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "UNIT_MEASURE_TYPE") %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate( sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_INDICATOR_COLLECTION <- CODE$T_COL_COLLECTION %>%
rename( code = COL_CODE,
label_en = COL_TEXT_EN,
label_fr = COL_TEXT_FR,
label_es = COL_TEXT_SP)%>%
mutate(sort = 1:n(), sort = as.numeric(sort)) %>%
arrange(sort) %>%
select(code, label_en, label_fr, label_es, sort) %>%
mutate(sort = 1:n())
CODE$T_SRC_SOURCE <- CODE$T_SRC_SOURCE %>%
select(-contains("_ID"), -contains("_DESCR_"), -SRC_GROUP_CODE) %>%
mutate_all(funs(as.character) ) %>%
rename( code = SRC_CODE,
label_en = SRC_TEXT_EN,
label_fr = SRC_TEXT_FR,
label_es = SRC_TEXT_SP,
acronym_en = SRC_ACRONYM_EN,
acronym_fr = SRC_ACRONYM_FR,
acronym_es = SRC_ACRONYM_SP ) %>%
mutate(sort = as.numeric(SRC_SORT)) %>%
arrange(sort) %>%
mutate(sort = 1:n()) %>%
select(-SRC_SORT)
CODE$T_SUR_SURVEY <- CODE$T_SUR_SURVEY %>%
mutate( SUR_SURVEY_TITLE_EN = ifelse(SUR_SURVEY_TITLE_EN %in% NA, SUR_ORIGINAL_SURVEY_TITLE, SUR_SURVEY_TITLE_EN ),
SUR_SURVEY_TITLE_FR = ifelse(SUR_SURVEY_TITLE_FR %in% NA, SUR_ORIGINAL_SURVEY_TITLE, SUR_SURVEY_TITLE_FR ),
SUR_SURVEY_TITLE_SP = ifelse(SUR_SURVEY_TITLE_SP %in% NA, SUR_ORIGINAL_SURVEY_TITLE, SUR_SURVEY_TITLE_SP )) %>%
rename( code = SUR_ID,
label_en = SUR_SURVEY_TITLE_EN,
label_fr = SUR_SURVEY_TITLE_SP,
label_es = SUR_SURVEY_TITLE_FR,
sort = SUR_SORT,
code_Geo = SUR_COUNTRY_CODE,
code_Source = SUR_SOURCE_CODE) %>%
mutate(sort = as.numeric(sort)) %>%
select(-SUR_COUNTRY_ID, -SUR_SOURCE_ID, -SUR_ACRONYM) %>%
arrange(code_Geo, sort) %>%
select(-SUR_ORIGINAL_SURVEY_TITLE) %>%
left_join(select(CODE$T_SRC_SOURCE, code_Source = code,acronym_en, acronym_fr, acronym_es ), by = 'code_Source') %>%
mutate( label_en = str_c(code_Geo,acronym_en, label_en, sep = ' - '),
label_fr = str_c(code_Geo,acronym_fr, label_fr, sep = ' - '),
label_es = str_c(code_Geo,acronym_es, label_es, sep = ' - '),
code = str_c(code_Source, code, sep = ':')
) %>%
select(-acronym_en, -acronym_fr, -acronym_es, -code_Source, -code_Geo) %>%
mutate(sort = 1:n())
CODE$T_SGR_SRC_GROUP <- CODE$T_SGR_SRC_GROUP %>%
mutate_all(funs(as.character)) %>%
select(-SGR_ID) %>%
rename( code = SGR_CODE,
label_en = SGR_TEXT_EN,
label_fr = SGR_TEXT_FR,
label_es = SGR_TEXT_SP,
sort = SGR_SORT ) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_CUR_CURRENCY <- CODE$T_CUR_CURRENCY %>%
mutate(code_Type = "T30") %>%
unite(code1, CUR_ID, sep= "", remove = TRUE) %>%
unite(code, code_Type, code1, sep= ":", remove = TRUE) %>%
select(-contains("_ID"), -CUR_END_DATE, -CUR_IS_CURRENT, -CUR_SYMBOL) %>%
rename( label_en = CUR_TEXT_EN,
label_fr = CUR_TEXT_FR,
label_es = CUR_TEXT_SP,
code_Geo = CUR_COUNTRY_CODE
) %>%
mutate( label_en = paste0("Local currency: ",code_Geo, ' - ',label_en, '(', CUR_CODE, ')'),
label_fr = paste0("Monnaie local: ",code_Geo, ' - ',label_fr, '(', CUR_CODE, ')'),
label_es = paste0("Moneda local: ",code_Geo, ' - ',label_es, '(', CUR_CODE, ')')
) %>%
mutate(sort = 1:n(), sort = as.numeric(sort))
CODE$T_NTY_NOTE_TYPE <- CODE$T_NTY_NOTE_TYPE %>% rename(type = NTY_GROUP_ID) %>%
select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
rename( code = NTY_CODE,
label_en = NTY_TEXT_EN,
label_fr = NTY_TEXT_FR,
label_es = NTY_TEXT_SP,
sort = NTY_SORT ) %>%
mutate(sort = as.numeric(sort) ) %>%
arrange(sort)
pass <- CODE$T_NTY_NOTE_TYPE %>% slice(1) %>%
mutate( code = "I0",
label_en = "Local currency",
label_fr = "Monnaie local",
label_es = "Moneda local",
sort = 0,
type = "297")
CODE$T_NTY_NOTE_TYPE <- bind_rows(pass, CODE$T_NTY_NOTE_TYPE) %>% arrange(sort) %>%
mutate(sort = 1:n())%>%
mutate(type = type %>% plyr:::mapvalues(from= c("296","297","298"), to = c('src','ind','cla')))
CL_FLAG <- CODE$T_CLT_CODELIST %>% filter(CLT_COLUMN_NAME %in% "VALUE_STATUS") %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_NTE_NOTE <- CODE$T_NTE_NOTE %>%
rename(NTE_CODE = NTE_ID) %>%
select(-contains("_ID"), -NTE_IS_GENERAL, -NTE_IS_VALIDATE, -contains("NTE_DESCR"))%>%
mutate_all(funs(as.character) ) %>%
rename( sort = NTE_SORT ) %>%
mutate( sort = as.numeric(sort)) %>%
left_join(select(CODE$T_NTY_NOTE_TYPE,
NTE_TYPE_CODE = code,
label_en_T = label_en,
label_fr_T = label_fr,
label_es_T = label_es,
sort_T = sort),
by = 'NTE_TYPE_CODE') %>%
arrange(sort_T, sort) %>%
unite(code, NTE_TYPE_CODE, NTE_CODE, sep=":", remove = TRUE) %>%
unite(label_en, label_en_T, NTE_TEXT_EN, sep=": ", remove = TRUE) %>%
unite(label_fr, label_fr_T, NTE_TEXT_FR, sep=": ", remove = TRUE) %>%
unite(label_es, label_es_T, NTE_TEXT_SP, sep=": ", remove = TRUE) %>%
select(-sort_T) %>% bind_rows(select(CODE$T_CUR_CURRENCY, -code_Geo),CL_FLAG ) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_FREQ <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "FREQ", CLT_COLUMN_CODE %in% c('A','Q','M')) %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_LANG <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "FREQ" ) %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate( code = tolower(code),
code = ifelse(code %in% "sp", "es", code))
CL_ZZZ <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% c('DATA_CHANNEL', 'WORKFLOW_STATUS', 'LOAD_MODE') ) %>%
select(-CLT_COLUMN_NAME, -CLT_COLUMN_CODE) %>%
rename( code = CLT_ID,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate( code = tolower(code),
code = ifelse(code %in% "sp", "es", code)) %>%
bind_rows(CODE$T_USR_USER)
CODE$T_SUB_SUBJECT <- CODE$T_SUB_SUBJECT %>%
select(-contains('_ID')) %>%
rename(code = SUB_CODE,label_en = SUB_TEXT_EN,
label_fr = SUB_TEXT_FR,
label_es = SUB_TEXT_SP )
CODE$T_NRD_NOTE_REMOVED_DISSEM <- CODE$T_NRD_NOTE_REMOVED_DISSEM %>%
left_join(select(CODE$T_NTY_NOTE_TYPE, NTE_TYPE_CODE = code, type), by = "NTE_TYPE_CODE") %>%
mutate(note = paste0(NTE_TYPE_CODE, ':', NRD_NOTE_ID)) %>%
rename(indicator = IND_CODE) %>%
select(-contains('_ID'), -NTE_TYPE_CODE)
assign("cl_classif",CODE$T_CLA_CLASSIF,e)
assign("cl_dataset",CL_DTS_DATASET,e)
assign("cl_classif_type",CODE$T_CLY_CLASSIF_TYPE,e)
assign("cl_classif_version",CODE$T_CLV_CLASSIF_VERSION,e)
assign("cl_country",CODE$T_COU_COUNTRY,e)
assign("cl_country_group",CODE$T_GRP_GROUP,e)
assign("cl_country_by_group",CODE$T_CBG_COUNTRY_BY_GROUP,e)
assign("cl_indicator",CODE$T_IND_INDICATOR,e)
assign("cl_indicator_topic",CODE$T_TOP_TOPIC,e)
assign("cl_indicator_variable",CODE$T_RVA_REPRESENTED_VARIABLE,e)
assign("cl_indicator_unit",CL_INDICATOR_UNIT,e)
assign("cl_indicator_type",CL_INDICATOR_TYPE,e)
assign("cl_indicator_collection",CL_INDICATOR_COLLECTION,e)
assign("cl_survey",CODE$T_SUR_SURVEY,e)
assign("cl_source",CODE$T_SRC_SOURCE,e)
assign("cl_source_group",CODE$T_SGR_SRC_GROUP,e)
assign("cl_dts_col",CODE$T_DCO_DATASET_COLLECTION,e)
assign("cl_col_ind",CL_COL_IND,e)
assign("cl_col_ind_clv",CL_COL_IND_CLV,e)
assign("cl_col_ind_scr",CL_COL_IND_SRC,e)
assign("cl_sub_ind",CL_SUB_IND,e)
assign("cl_subject",CODE$T_SUB_SUBJECT,e)
assign("cl_note_currency",CODE$T_CUR_CURRENCY,e)
assign("cl_note",CODE$T_NTE_NOTE,e)
assign("cl_note_type",CODE$T_NTY_NOTE_TYPE,e)
assign("cl_note_delete",CODE$T_NRD_NOTE_REMOVED_DISSEM,e)
assign("cl_freq",CL_FREQ,e)
assign("cl_lang",CL_LANG,e)
assign("cl_status",CL_FLAG,e)
assign("cl_z",CL_ZZZ,e)
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, 'Tmp/data/settings/cl'))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/cl.rdb'), to = paste0(ilo:::path$tools, 'R/data/settings/cl.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/cl.rdx'), to = paste0(ilo:::path$tools, 'R/data/settings/cl.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
}
#' @export
prepare_setting_ilo <- function(){ # repare settings
e <- new.env()
LastUpdate <- Sys.time()
assign("lastupdate",LastUpdate,e)
seg <- c(list.files(paste0(ilo:::path$sys, 'Tmp/data/data/cou')) %>% .[str_detect(.,fixed('.rdb'))]) %>% str_sub(., 1, nchar(.)-4)
seg <- cbind(files = seg, size = file.size(paste0(ilo:::path$sys, 'Tmp/data/data/', seg, '.zip'))) %>% as.data.frame %>% as.tbl %>%
mutate( collection = str_split_fixed(files, fixed('_'), n = 2)[,1],
freq = str_split_fixed(files, fixed('_'), n = 2)[,2],
size = as.numeric(as.character(size))/1000) %>%
filter(!substr(collection,1,4) %in% "init") %>%
arrange(desc(size)) %>%
mutate_if(is.character, funs(factor))
assign("segment",seg,e)
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, 'Tmp/data/settings/set'))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/set.rdb'), to = paste0(ilo:::path$tools, 'R/data/settings/set.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/set.rdx'), to = paste0(ilo:::path$tools, 'R/data/settings/set.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
}
dbescond/Ariane documentation built on Dec. 10, 2019, 10:01 a.m.
R Package Documentation
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Defines functions prepare_segment_ilo prepare_segment_ilo2 prepare_codelist_ilo prepare_setting_ilo
Documented in prepare_segment_ilo
#' Prepare ilo packages
#'
#' fix utf-8 encoding bug
#'
#' Helper function to efficiently query data from ILOSTAT SDMX API.
#'
#' @param X data frame.
#' @param DELETE in deletion format, default is FALSE.
#' @param LABEL add label to the notes, default is FALSE.
#' @author ILO bescond
#' @keywords ILO, R
#' @export
#' @rdname prepare_ilo
prepare_segment_ilo <- function(FREQ, DBNAme, query, cou){
e <- new.env()
for (i in 1:length(cou)){
X <- readRDS(paste0(ilo:::path$sys, 'ILO_Data/ORA/',query, '_', cou[i],'_',FREQ, '.rds'))%>%
mutate_all(funs(as.character))%>%
mutate(obs_value = as.numeric(obs_value)) %>%
select(-sex_version, -classif1_version, -classif2_version)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
if(nrow(X)>0){
X <- X %>%
select(source, indicator, sex:obs_status, note_classif, note_indicator, note_source, info)
if(!FREQ %in% c('M','Q') ){
X <- X %>% mutate(time = as.numeric(time))
}
invisible(gc(reset = TRUE))
assign(cou[i],X ,e)
print(cou[i])
}
rm(X)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
}
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
getwd()
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
aa <- file.size(paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdb'))
print(aa)
if(aa == 0){
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdb'))
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdx'))
} else{
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdb'), to = paste0(ilo:::path$tools, 'R/data/data/cou/', DBNAme, '.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/cou/", DBNAme, '.rdx'), to = paste0(ilo:::path$tools, 'R/data/data/cou/', DBNAme, '.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
invisible(gc(reset = TRUE))
}
}
#' @export
prepare_segment_ilo2 <- function(FREQ, DBNAme, query, cou){
e <- new.env()
DB <- NULL
for (i in 1:length(cou)){
X <- readRDS(paste0(ilo:::path$sys, 'ILO_Data/ORA/',query, '_', cou[i],'_',FREQ, '.rds'))%>%
mutate_all(funs(as.character))%>%
mutate(obs_value = as.numeric(obs_value)) %>%
select(-sex_version, -classif1_version, -classif2_version)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
if(nrow(X)>0){
X <- X %>%
select(ref_area, source, indicator, sex:obs_status, note_classif, note_indicator, note_source, info)
if(!FREQ %in% c('M','Q') ){
X <- X %>% mutate(time = as.numeric(time))
}
invisible(gc(reset = TRUE))
#
DB <- bind_rows(DB, X)
}
rm(X)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
}
test <- DB %>% count(indicator) %>% left_join(Ariane:::CODE_ORA$T_IND_INDICATOR %>% select(indicator = IND_CODE, IND_SORT), by = 'indicator') %>% arrange(IND_SORT) %>% .$indicator
for (i in 1:length(test)){
X <- DB %>% filter(indicator %in% test[i]) %>% select(-indicator)
assign(test[i],X ,e)
rm(X)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
DB <- DB %>% filter(!indicator %in% test[i])
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
print(test[i])
}
rm(DB)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
getwd()
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
aa <- file.size(paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdb'))
print(aa)
if(aa == 0){
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdb'))
file.remove(paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdx'))
} else{
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdb'), to = paste0(ilo:::path$tools, 'R/data/data/ind/', DBNAme, '.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, "Tmp/data/data/ind/", DBNAme, '.rdx'), to = paste0(ilo:::path$tools, 'R/data/data/ind/', DBNAme, '.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
invisible(gc(reset = TRUE))
}
}
#' @export
prepare_codelist_ilo <- function(){
e <- new.env()
CODE <- Ariane:::CODE_ORA
code <- c("T_CLA_CLASSIF",
"T_DTS_DATASET",
"T_CIS_COL_IND_SRC",
"T_CIN_COL_IND",
"T_CIC_COL_IND_CLV",
"T_COL_COLLECTION",
"T_CLT_CODELIST",
"T_CLV_CLASSIF_VERSION",
"T_CLY_CLASSIF_TYPE",
"T_COU_COUNTRY",
"T_CUR_CURRENCY",
"T_GRP_GROUP",
"T_CBG_COUNTRY_BY_GROUP",
"T_IND_INDICATOR",
"T_NTE_NOTE",
"T_NTY_NOTE_TYPE",
"T_SRC_SOURCE",
"T_SUR_SURVEY",
"T_TOP_TOPIC",
"T_USR_USER",
"T_RVA_REPRESENTED_VARIABLE",
"T_SGR_SRC_GROUP",
"T_SUI_SUBJECT_INDICATOR",
"T_DCO_DATASET_COLLECTION",
"T_SUB_SUBJECT",
"T_NRD_NOTE_REMOVED_DISSEM"
)
CODE <- CODE[names(CODE) %in% code]
COU <- readxl::read_excel(paste0(ilo:::path$sys, 'ILO_Meta/REGION.xlsx'), sheet = 'Consolidation') %>% select(ilo_code, ISO3_CODE)
CODE$T_DCO_DATASET_COLLECTION <- CODE$T_DCO_DATASET_COLLECTION %>%
left_join(CODE$T_DTS_DATASET %>% select(DCO_DATASET_ID = DTS_ID, dataset = DTS_CODE)) %>%
left_join(CODE$T_COL_COLLECTION %>% select(DCO_COLLECTION_ID = COL_ID, collection = COL_CODE)) %>% select(-contains('_ID'))
CL_DTS_DATASET <- CODE$T_DTS_DATASET %>% select(-contains("_ID")) %>%
rename( code = DTS_CODE,
label_en = DTS_TEXT_EN,
label_fr = DTS_TEXT_FR,
label_es = DTS_TEXT_SP,
description_en = DTS_DESCR_EN,
description_fr = DTS_DESCR_FR,
description_es = DTS_DESCR_SP,
sort = DTS_SORT ) %>%
mutate(sort = as.numeric(sort),
code = str_sub(code, 1,2)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_USR_USER <- CODE$T_USR_USER %>% select(USR_ID, USR_LASTNAME) %>%
rename( code = USR_ID,
label_en = USR_LASTNAME ) %>%
mutate(sort = 1:n(),
label_en = tolower(paste0(str_sub(label_en, 1,1), str_sub(label_en, -2,-1), sep = ''))) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_CLV_CLASSIF_VERSION <- CODE$T_CLV_CLASSIF_VERSION %>% select(-contains("_ID"), -contains("CLV_SHORT"), -CLV_CLASSIF_TYPE_CODE, -contains("CLV_DESCR"), -CLV_IS_EDITABLE, -CLV_IS_DISSEMINATED) %>%
mutate_all(funs(as.character) ) %>%
mutate(CLV_SORT = as.numeric(CLV_SORT)) %>%
rename( code = CLV_CODE,
label_en = CLV_TEXT_EN,
label_fr = CLV_TEXT_FR,
label_es = CLV_TEXT_SP,
sort = CLV_SORT ) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_CLA_CLASSIF <- CODE$T_CLA_CLASSIF %>% select(-contains("_ID"), -contains("CLA_LEVEL"), -CLA_DETAILS, -CLA_IS_DEFAULT, -CLA_IS_TOTAL ,-CLA_IS_VALIDATE ) %>%
mutate_all(funs(as.character) ) %>%
mutate(CLA_SORT = as.numeric(CLA_SORT)) %>%
rename( code = CLA_CODE,
label_en_1 = CLA_TEXT_EN,
label_fr_1 = CLA_TEXT_FR,
label_es_1 = CLA_TEXT_SP,
sort = CLA_SORT ) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
left_join(select(CODE$T_CLV_CLASSIF_VERSION,
CLA_VERSION_CODE = code,
label_en_T = label_en,
label_fr_T = label_fr,
label_es_T = label_es),
by = 'CLA_VERSION_CODE') %>%
unite(label_en, label_en_T, label_en_1, sep=": ", remove = TRUE) %>%
unite(label_fr, label_fr_T, label_fr_1, sep=": ", remove = TRUE) %>%
unite(label_es, label_es_T, label_es_1, sep=": ", remove = TRUE) %>%
select(-CLA_VERSION_CODE) %>%
mutate(sort = 1:n())
CODE$T_CLY_CLASSIF_TYPE <- CODE$T_CLY_CLASSIF_TYPE %>% select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
mutate(CLY_SORT = as.numeric(CLY_SORT)) %>%
rename( code = CLY_CODE,
label_en = CLY_TEXT_EN,
label_fr = CLY_TEXT_FR,
label_es = CLY_TEXT_SP,
description_en = CLY_DESCR_EN,
description_fr = CLY_DESCR_FR,
description_es = CLY_DESCR_SP,
sort = CLY_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_COU_COUNTRY <- CODE$T_COU_COUNTRY %>%
select(-contains("_ID"), -COU_IS_ILOMEMBER, -COU_IS_RECEIVING_QUEST, -COU_CALLING_CODE)%>%
mutate_all(funs(as.character)) %>%
rename( code = COU_ISO3_CODE,
label_en = COU_TEXT_EN,
label_fr = COU_TEXT_FR,
label_es = COU_TEXT_SP,
sort = COU_SORT_EN) %>%
mutate(sort = as.numeric(sort),
code_iso2 = COU_ISO2_CODE,
code_iso3n = as.numeric(as.character(COU_ISO3N_CODE))) %>%
arrange(sort) %>% select(-COU_SORT_FR, -COU_SORT_SP, -COU_ONU_CODE, -COU_ISO3N_CODE, -COU_ISO2_CODE) %>%
mutate(sort = 1:n()) %>%
left_join(COU %>% select(code = ISO3_CODE, ilo_code))
CODE$T_GRP_GROUP <- CODE$T_GRP_GROUP %>% select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
rename( code = GRP_CODE,
label_en = GRP_TEXT_EN,
label_fr = GRP_TEXT_FR,
label_es = GRP_TEXT_SP
) %>% mutate(sort = 1:n(), sort = as.numeric(sort))
CODE$T_CBG_COUNTRY_BY_GROUP <- CODE$T_CBG_COUNTRY_BY_GROUP %>%
select(-contains("_ID")) %>%
mutate_all(funs(as.character)) %>%
rename( code = CBG_GROUP_CODE,
code_country = CBG_COUNTRY_CODE)
CL_COL_IND_SRC <- CODE$T_CIS_COL_IND_SRC %>%
left_join(CODE$T_CIN_COL_IND %>%
select(CIS_CIN_ID = CIN_ID, CIN_COLLECTION_ID, CIN_INDICATOR_ID), by = "CIS_CIN_ID") %>%
left_join(CODE$T_IND_INDICATOR %>%
select(CIN_INDICATOR_ID = IND_ID, IND_CODE), by = c("IND_CODE", "CIN_INDICATOR_ID")) %>%
left_join(CODE$T_COL_COLLECTION %>%
select(CIN_COLLECTION_ID = COL_ID, COL_CODE ), by = c("COL_CODE", "CIN_COLLECTION_ID")) %>%
left_join(CODE$T_SRC_SOURCE %>%
select(CIS_SOURCE_ID = SRC_ID, SRC_CODE ), by = c("CIS_SOURCE_ID", "SRC_CODE")) %>%
select(contains('_CODE')) %>%
rename(indicator = IND_CODE, collection = COL_CODE, source = SRC_CODE)
CL_COL_IND_CLV <- CODE$T_CIC_COL_IND_CLV %>%
select(contains('_CODE'), CIC_IS_DISSEM)
colnames(CL_COL_IND_CLV) <- c('collection','indicator','classif_vs', 'dissem')
CL_SUB_IND <- CODE$T_SUI_SUBJECT_INDICATOR %>%
left_join(CODE$T_IND_INDICATOR %>%
select(SUI_INDICATOR_ID = IND_ID, IND_CODE), by = c("SUI_INDICATOR_ID", "IND_CODE")) %>%
left_join(CODE$T_SUB_SUBJECT %>%
select(SUI_SUBJECT_ID = SUB_ID, SUB_CODE ), by = c("SUI_SUBJECT_ID", "SUB_CODE")) %>%
select(contains('CODE')) %>%
rename(indicator = IND_CODE, subject = SUB_CODE)
CL_COL_IND <- CL_COL_IND_CLV %>% distinct(collection, indicator)
CODE$T_IND_INDICATOR <- CODE$T_IND_INDICATOR %>%
select(-contains("_ID"), -contains("_LEVEL"), -IND_UNIT_MULT_CODE)%>%
mutate_all(funs(as.character) ) %>%
mutate(IND_SORT = as.numeric(IND_SORT)) %>%
select(-IND_IS_LABORSTA, -IND_INSTR_EN, -IND_INSTR_FR, -IND_INSTR_SP, -IND_HOT_INDICATOR_RANKING, -IND_HEADER_EN, -IND_HEADER_FR, -IND_HEADER_SP, -IND_UNIT_MEASURE_TYPE_CODE) %>%
rename( code = IND_CODE,
label_en = IND_TEXT_EN,
label_fr = IND_TEXT_FR,
label_es = IND_TEXT_SP,
description_en = IND_DESCR_EN,
description_fr = IND_DESCR_FR,
description_es = IND_DESCR_SP,
decimal = IND_DECIMAL,
code_Measure = IND_UNIT_MEASURE_CODE,
sort = IND_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_TOP_TOPIC <- CODE$T_TOP_TOPIC %>% select(-contains("_ID"), -contains("_INSTR_")) %>%
mutate_all(funs(as.character) ) %>%
mutate(TOP_SORT = as.numeric(TOP_SORT)) %>%
rename( code = TOP_CODE,
label_en = TOP_TEXT_EN,
label_fr = TOP_TEXT_FR,
label_es = TOP_TEXT_SP,
description_en = TOP_DESCR_EN,
description_fr = TOP_DESCR_FR,
description_es = TOP_DESCR_SP,
sort = TOP_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_RVA_REPRESENTED_VARIABLE <- CODE$T_RVA_REPRESENTED_VARIABLE %>%
select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
mutate(RVA_SORT = as.numeric(RVA_SORT)) %>%
rename( code = RVA_CODE,
label_en = RVA_TEXT_EN,
label_fr = RVA_TEXT_FR,
label_es = RVA_TEXT_SP,
description_en = RVA_DESCR_EN,
description_fr = RVA_DESCR_FR,
description_es = RVA_DESCR_SP,
sort = RVA_SORT) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_INDICATOR_UNIT <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "UNIT_MEASURE") %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate( sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_INDICATOR_TYPE <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "UNIT_MEASURE_TYPE") %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate( sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_INDICATOR_COLLECTION <- CODE$T_COL_COLLECTION %>%
rename( code = COL_CODE,
label_en = COL_TEXT_EN,
label_fr = COL_TEXT_FR,
label_es = COL_TEXT_SP)%>%
mutate(sort = 1:n(), sort = as.numeric(sort)) %>%
arrange(sort) %>%
select(code, label_en, label_fr, label_es, sort) %>%
mutate(sort = 1:n())
CODE$T_SRC_SOURCE <- CODE$T_SRC_SOURCE %>%
select(-contains("_ID"), -contains("_DESCR_"), -SRC_GROUP_CODE) %>%
mutate_all(funs(as.character) ) %>%
rename( code = SRC_CODE,
label_en = SRC_TEXT_EN,
label_fr = SRC_TEXT_FR,
label_es = SRC_TEXT_SP,
acronym_en = SRC_ACRONYM_EN,
acronym_fr = SRC_ACRONYM_FR,
acronym_es = SRC_ACRONYM_SP ) %>%
mutate(sort = as.numeric(SRC_SORT)) %>%
arrange(sort) %>%
mutate(sort = 1:n()) %>%
select(-SRC_SORT)
CODE$T_SUR_SURVEY <- CODE$T_SUR_SURVEY %>%
mutate( SUR_SURVEY_TITLE_EN = ifelse(SUR_SURVEY_TITLE_EN %in% NA, SUR_ORIGINAL_SURVEY_TITLE, SUR_SURVEY_TITLE_EN ),
SUR_SURVEY_TITLE_FR = ifelse(SUR_SURVEY_TITLE_FR %in% NA, SUR_ORIGINAL_SURVEY_TITLE, SUR_SURVEY_TITLE_FR ),
SUR_SURVEY_TITLE_SP = ifelse(SUR_SURVEY_TITLE_SP %in% NA, SUR_ORIGINAL_SURVEY_TITLE, SUR_SURVEY_TITLE_SP )) %>%
rename( code = SUR_ID,
label_en = SUR_SURVEY_TITLE_EN,
label_fr = SUR_SURVEY_TITLE_SP,
label_es = SUR_SURVEY_TITLE_FR,
sort = SUR_SORT,
code_Geo = SUR_COUNTRY_CODE,
code_Source = SUR_SOURCE_CODE) %>%
mutate(sort = as.numeric(sort)) %>%
select(-SUR_COUNTRY_ID, -SUR_SOURCE_ID, -SUR_ACRONYM) %>%
arrange(code_Geo, sort) %>%
select(-SUR_ORIGINAL_SURVEY_TITLE) %>%
left_join(select(CODE$T_SRC_SOURCE, code_Source = code,acronym_en, acronym_fr, acronym_es ), by = 'code_Source') %>%
mutate( label_en = str_c(code_Geo,acronym_en, label_en, sep = ' - '),
label_fr = str_c(code_Geo,acronym_fr, label_fr, sep = ' - '),
label_es = str_c(code_Geo,acronym_es, label_es, sep = ' - '),
code = str_c(code_Source, code, sep = ':')
) %>%
select(-acronym_en, -acronym_fr, -acronym_es, -code_Source, -code_Geo) %>%
mutate(sort = 1:n())
CODE$T_SGR_SRC_GROUP <- CODE$T_SGR_SRC_GROUP %>%
mutate_all(funs(as.character)) %>%
select(-SGR_ID) %>%
rename( code = SGR_CODE,
label_en = SGR_TEXT_EN,
label_fr = SGR_TEXT_FR,
label_es = SGR_TEXT_SP,
sort = SGR_SORT ) %>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_CUR_CURRENCY <- CODE$T_CUR_CURRENCY %>%
mutate(code_Type = "T30") %>%
unite(code1, CUR_ID, sep= "", remove = TRUE) %>%
unite(code, code_Type, code1, sep= ":", remove = TRUE) %>%
select(-contains("_ID"), -CUR_END_DATE, -CUR_IS_CURRENT, -CUR_SYMBOL) %>%
rename( label_en = CUR_TEXT_EN,
label_fr = CUR_TEXT_FR,
label_es = CUR_TEXT_SP,
code_Geo = CUR_COUNTRY_CODE
) %>%
mutate( label_en = paste0("Local currency: ",code_Geo, ' - ',label_en, '(', CUR_CODE, ')'),
label_fr = paste0("Monnaie local: ",code_Geo, ' - ',label_fr, '(', CUR_CODE, ')'),
label_es = paste0("Moneda local: ",code_Geo, ' - ',label_es, '(', CUR_CODE, ')')
) %>%
mutate(sort = 1:n(), sort = as.numeric(sort))
CODE$T_NTY_NOTE_TYPE <- CODE$T_NTY_NOTE_TYPE %>% rename(type = NTY_GROUP_ID) %>%
select(-contains("_ID")) %>%
mutate_all(funs(as.character) ) %>%
rename( code = NTY_CODE,
label_en = NTY_TEXT_EN,
label_fr = NTY_TEXT_FR,
label_es = NTY_TEXT_SP,
sort = NTY_SORT ) %>%
mutate(sort = as.numeric(sort) ) %>%
arrange(sort)
pass <- CODE$T_NTY_NOTE_TYPE %>% slice(1) %>%
mutate( code = "I0",
label_en = "Local currency",
label_fr = "Monnaie local",
label_es = "Moneda local",
sort = 0,
type = "297")
CODE$T_NTY_NOTE_TYPE <- bind_rows(pass, CODE$T_NTY_NOTE_TYPE) %>% arrange(sort) %>%
mutate(sort = 1:n())%>%
mutate(type = type %>% plyr:::mapvalues(from= c("296","297","298"), to = c('src','ind','cla')))
CL_FLAG <- CODE$T_CLT_CODELIST %>% filter(CLT_COLUMN_NAME %in% "VALUE_STATUS") %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CODE$T_NTE_NOTE <- CODE$T_NTE_NOTE %>%
rename(NTE_CODE = NTE_ID) %>%
select(-contains("_ID"), -NTE_IS_GENERAL, -NTE_IS_VALIDATE, -contains("NTE_DESCR"))%>%
mutate_all(funs(as.character) ) %>%
rename( sort = NTE_SORT ) %>%
mutate( sort = as.numeric(sort)) %>%
left_join(select(CODE$T_NTY_NOTE_TYPE,
NTE_TYPE_CODE = code,
label_en_T = label_en,
label_fr_T = label_fr,
label_es_T = label_es,
sort_T = sort),
by = 'NTE_TYPE_CODE') %>%
arrange(sort_T, sort) %>%
unite(code, NTE_TYPE_CODE, NTE_CODE, sep=":", remove = TRUE) %>%
unite(label_en, label_en_T, NTE_TEXT_EN, sep=": ", remove = TRUE) %>%
unite(label_fr, label_fr_T, NTE_TEXT_FR, sep=": ", remove = TRUE) %>%
unite(label_es, label_es_T, NTE_TEXT_SP, sep=": ", remove = TRUE) %>%
select(-sort_T) %>% bind_rows(select(CODE$T_CUR_CURRENCY, -code_Geo),CL_FLAG ) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_FREQ <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "FREQ", CLT_COLUMN_CODE %in% c('A','Q','M')) %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate(sort = 1:n())
CL_LANG <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% "FREQ" ) %>%
select(-CLT_ID, -CLT_COLUMN_NAME) %>%
rename( code = CLT_COLUMN_CODE,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate( code = tolower(code),
code = ifelse(code %in% "sp", "es", code))
CL_ZZZ <- CODE$T_CLT_CODELIST %>%
filter(CLT_COLUMN_NAME %in% c('DATA_CHANNEL', 'WORKFLOW_STATUS', 'LOAD_MODE') ) %>%
select(-CLT_COLUMN_NAME, -CLT_COLUMN_CODE) %>%
rename( code = CLT_ID,
label_en = CLT_TEXT_EN,
label_fr = CLT_TEXT_FR,
label_es = CLT_TEXT_SP,
sort = CLT_SORT )%>%
mutate(sort = as.numeric(sort)) %>%
arrange(sort) %>%
mutate( code = tolower(code),
code = ifelse(code %in% "sp", "es", code)) %>%
bind_rows(CODE$T_USR_USER)
CODE$T_SUB_SUBJECT <- CODE$T_SUB_SUBJECT %>%
select(-contains('_ID')) %>%
rename(code = SUB_CODE,label_en = SUB_TEXT_EN,
label_fr = SUB_TEXT_FR,
label_es = SUB_TEXT_SP )
CODE$T_NRD_NOTE_REMOVED_DISSEM <- CODE$T_NRD_NOTE_REMOVED_DISSEM %>%
left_join(select(CODE$T_NTY_NOTE_TYPE, NTE_TYPE_CODE = code, type), by = "NTE_TYPE_CODE") %>%
mutate(note = paste0(NTE_TYPE_CODE, ':', NRD_NOTE_ID)) %>%
rename(indicator = IND_CODE) %>%
select(-contains('_ID'), -NTE_TYPE_CODE)
assign("cl_classif",CODE$T_CLA_CLASSIF,e)
assign("cl_dataset",CL_DTS_DATASET,e)
assign("cl_classif_type",CODE$T_CLY_CLASSIF_TYPE,e)
assign("cl_classif_version",CODE$T_CLV_CLASSIF_VERSION,e)
assign("cl_country",CODE$T_COU_COUNTRY,e)
assign("cl_country_group",CODE$T_GRP_GROUP,e)
assign("cl_country_by_group",CODE$T_CBG_COUNTRY_BY_GROUP,e)
assign("cl_indicator",CODE$T_IND_INDICATOR,e)
assign("cl_indicator_topic",CODE$T_TOP_TOPIC,e)
assign("cl_indicator_variable",CODE$T_RVA_REPRESENTED_VARIABLE,e)
assign("cl_indicator_unit",CL_INDICATOR_UNIT,e)
assign("cl_indicator_type",CL_INDICATOR_TYPE,e)
assign("cl_indicator_collection",CL_INDICATOR_COLLECTION,e)
assign("cl_survey",CODE$T_SUR_SURVEY,e)
assign("cl_source",CODE$T_SRC_SOURCE,e)
assign("cl_source_group",CODE$T_SGR_SRC_GROUP,e)
assign("cl_dts_col",CODE$T_DCO_DATASET_COLLECTION,e)
assign("cl_col_ind",CL_COL_IND,e)
assign("cl_col_ind_clv",CL_COL_IND_CLV,e)
assign("cl_col_ind_scr",CL_COL_IND_SRC,e)
assign("cl_sub_ind",CL_SUB_IND,e)
assign("cl_subject",CODE$T_SUB_SUBJECT,e)
assign("cl_note_currency",CODE$T_CUR_CURRENCY,e)
assign("cl_note",CODE$T_NTE_NOTE,e)
assign("cl_note_type",CODE$T_NTY_NOTE_TYPE,e)
assign("cl_note_delete",CODE$T_NRD_NOTE_REMOVED_DISSEM,e)
assign("cl_freq",CL_FREQ,e)
assign("cl_lang",CL_LANG,e)
assign("cl_status",CL_FLAG,e)
assign("cl_z",CL_ZZZ,e)
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, 'Tmp/data/settings/cl'))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/cl.rdb'), to = paste0(ilo:::path$tools, 'R/data/settings/cl.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/cl.rdx'), to = paste0(ilo:::path$tools, 'R/data/settings/cl.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
}
#' @export
prepare_setting_ilo <- function(){ # repare settings
e <- new.env()
LastUpdate <- Sys.time()
assign("lastupdate",LastUpdate,e)
seg <- c(list.files(paste0(ilo:::path$sys, 'Tmp/data/data/cou')) %>% .[str_detect(.,fixed('.rdb'))]) %>% str_sub(., 1, nchar(.)-4)
seg <- cbind(files = seg, size = file.size(paste0(ilo:::path$sys, 'Tmp/data/data/', seg, '.zip'))) %>% as.data.frame %>% as.tbl %>%
mutate( collection = str_split_fixed(files, fixed('_'), n = 2)[,1],
freq = str_split_fixed(files, fixed('_'), n = 2)[,2],
size = as.numeric(as.character(size))/1000) %>%
filter(!substr(collection,1,4) %in% "init") %>%
arrange(desc(size)) %>%
mutate_if(is.character, funs(factor))
assign("segment",seg,e)
tools:::makeLazyLoadDB(e, paste0(ilo:::path$sys, 'Tmp/data/settings/set'))
rm(e)
invisible(gc(reset = TRUE))
invisible(gc(reset = TRUE))
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/set.rdb'), to = paste0(ilo:::path$tools, 'R/data/settings/set.rdb'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
file.copy(from = paste0(ilo:::path$sys, 'Tmp/data/settings/set.rdx'), to = paste0(ilo:::path$tools, 'R/data/settings/set.rdx'), overwrite = TRUE, recursive = FALSE, copy.mode = TRUE, copy.date = FALSE)
}
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