demo ready

demo.R

-# When the package will be finished, install via CRAN
-# install.packages("fso.metadata")
 
-# Currently use:
+### Preparation ###
 devtools::install_url("https://renkulab.io/gitlab/dscc/metadata-auto-r-library/-/archive/v002/metadata-auto-r-library-v002.tar.gz")
-library("fso.metadata")
+library(fso.metadata)
+library(ggplot2)
+library(tidyverse)
 
-
-## Get a codelist
+### 1. Get a codelist ###
 # All languages
 codelist <- get_codelist(identifier='CL_NOGA_SECTION')
-names(codelist)
-head(codelist)
+head(codelist, 3)
 
 # In french
-codelist <- get_codelist(identifier='CL_NOGA_SECTION', language='fr')
-names(codelist)
-
-head(codelist$label.fr)
-head(codelist$id)
+codelist_fr <- get_codelist(identifier='CL_NOGA_SECTION', language='fr')
+head(codelist_fr, 3)
 
 
-## Get a nomenclature of one level
+### 2. Get a nomenclature of one level ###
 # All language: Level 1
 nomenclature <- get_nomenclature_one_level(
-  identifier='HCL_CH_ISCO_19_PROF', level_number=2
+  identifier='HCL_CH_ISCO_19_PROF', 
+  level_number=2
 )
-names(nomenclature)
-head(nomenclature, 5)
+head(nomenclature, 3)
 
 # French: Level 2
 nomenclature_fr <- get_nomenclature_one_level(
-  identifier='HCL_CH_ISCO_19_PROF', level_number=1, language='fr'
+  identifier='HCL_CH_ISCO_19_PROF', 
+  level_number=1, 
+  language='fr'
 )
-names(nomenclature_fr)
 head(nomenclature_fr, 5)
 
-nomenclature_de <- get_nomenclature_one_level(
-  identifier='HCL_CH_ISCO_19_PROF', level_number=1, language='de'
-)
-names(nomenclature_de)
-head(nomenclature_de, 5)
 
-## Get a nomenclature of multiple levels
+
+### 3. Get a nomenclature of multiple levels ###
 # French
 multi_nomenclature_fr <- get_nomenclature_multiple_levels(
   identifier='HCL_CH_ISCO_19_PROF', 
   level_from=1, 
-  level_to=5, 
+  level_to=6, 
   language='fr'
 )
-head(multi_nomenclature_fr, 5)
+head(multi_nomenclature_fr, 10)
 
-# German
-multi_nomenclature_de <- get_nomenclature_multiple_levels(
-  identifier='HCL_CH_ISCO_19_PROF', 
-  level_from=2, 
-  level_to=3, 
-  language='de'
-)
-head(multi_nomenclature_de, 5)
 
+
+### 4. Concrete example from Mr. van Nieuwkoop with Noga Data
+load("data/pkagg.Rdata")
+head(pk_agg$A88)
+
+noga2 <- as_tibble(get_codelist(identifier='CL_NOGA_DIVISION', language='it'))
+names(noga2) <- c('id', 'label', 'name')
+head(noga2)
+
+# Get the completely disaggregated production accounts
+#  and join them with the noga2 descriptions
+a88 <- pk_agg$A88 %>% 
+  left_join(noga2, by = c("Code" = "id")) 
+
+head(a88)
+
+# Filter and prepare data
+a88_filtered <- a88 %>% 
+  select(-Beschreibung, -name) %>% 
+  relocate(label, .after = Code) %>% 
+  rename(Department = label, Year = Jahr, Component = Komponent) %>% 
+  select(Code, Department, Component, Year, Nominal) %>% 
+  filter( Nominal > 0) %>% 
+  filter(!is.na(Department)) %>%        # keep 
+  filter(Code %in% c("01","02", "03")) # keep first 3 department
+
+# Plot the intermediate consumption (CI), the value added (VA), and the 
+# production value (VP) for the section A (agriculture)
+ggplot(a88_filtered, aes(Year, Nominal, color = Component)) + 
+  geom_line() + 
+  ylab("in Mio. CHF") +
+  facet_wrap(~Department,  scales = "free")

install.R

@@ -2,6 +2,7 @@ install.packages(c(
   "devtools", "roxygen2", "document", "styler", "httr", "jsonlite", "glue",
   "pkgdown"
 ))
+install.packages("ggplot")
 devtools::install_github("opensdmx/rsdmx")
 
 ## Load and test library