Cross-classification of gross fixed capital formation by industry and by asset (flows) - nama_10_nfa_fl

Data - Eurostat

Author

asset10

Code

nama_10_nfa_fl %>%
  left_join(asset10, by = "asset10") %>%
  group_by(asset10, Asset10) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

nace_r2

Code

nama_10_nfa_fl %>%
  left_join(nace_r2, by = "nace_r2") %>%
  group_by(nace_r2, Nace_r2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

unit

Code

nama_10_nfa_fl %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

geo

Code

nama_10_nfa_fl %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Tables

France

Code

nama_10_nfa_fl %>%
  filter(geo %in% c("FR"),
         time == "2019", 
         unit == "CP_MEUR") %>%
  left_join(nace_r2, by = "nace_r2") %>%
  select(nace_r2, asset10, Nace_r2, values) %>%
  spread(asset10, values) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Germany

Code

nama_10_nfa_fl %>%
  filter(geo %in% c("DE"),
         time == "2018", 
         unit == "CP_MEUR") %>%
  left_join(nace_r2, by = "nace_r2") %>%
  select(nace_r2, asset10, Nace_r2, values) %>%
  spread(asset10, values) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}