update naming

library(zoo)

library(ggplot2)

library(plotly)

# # -> 0) load data structure for qna

# dataset <- "QNA"

# url <- paste0("https://stats.oecd.org/restsdmx/sdmx.ashx/GetDataStructure/", dataset)

# data_structure <- readsdmx::read_sdmx(url)

# data_structure %>%

#   filter(id == c("CL_QNA_SUBJECT"),

#          value %in% c("B1G", "B1GVA", "B1GVB_E", "B1GVF", "B1GVG_I", "B1GVJ", "B1GVK", "B1GVL", "B1GVM_N", "B1GVO_Q", "B1GVR_U")) %>%

#   select(value, en_description) %>%

#   kable(col.names = c("Code", "Description"))

# 

# # -> 1) load data

# 

# dataset <- "QNA"

# start_time <- as.Date("2010-01-01")

# end_time <- as.Date("2023-10-01")

# # Note: Q1: 2020-01-01; Q2: 2020-04-01; Q3: 2020-07-01; Q4: 2020-10-01

# filter = list(LOCATION = c("DEU", "FRA"),

#               SUBJECT = c("B1G", "B1GVA", "B1GVB_E", "B1GVF", "B1GVG_I", "B1GVJ", "B1GVK", "B1GVL", "B1GVM_N", "B1GVO_Q", "B1GVR_U"),

#               MEASURE = c("LNBQRSA"),

#               FREQUENCY = c("Q"))

# 

# qna_dat <- get_dataset(dataset, filter, start_time, end_time)

library(readsdmx)

url <- "https://sdmx.oecd.org/public/rest/data/OECD.SDD.NAD,DSD_NAMAIN1@DF_QNA_EXPENDITURE_INDICES,1.1/Q............"

url <- "https://sdmx.oecd.org/public/rest/data/OECD.SDD.NAD,DSD_NAMAIN1@DF_QNA_EXPENDITURE_NATIO_CURR,1.1/Q............"

qna_dat <- read_sdmx(path = url)

library(dplyr)

qna_dat <- qna_dat %>%

  filter(REF_AREA %in% c("DEU", "FRA"),

         TRANSACTION %in% c("B1GQ", "P3", "P51G", "P6", "P7"),

         PRICE_BASE %in% c("LR"))

         PRICE_BASE %in% c("L"))

# check

head(qna_dat)

# save transformed data ----

save(qna_dat, file = "./01_data/qna_dat_01_updated.RData")

load("./01_data/qna_dat_01.RData")