Financial transactions - nasa_10_f_tr

Data - Eurostat

Author

Info

Sector Accounts Dedicated Webpage. html
Sector accounts. html

LAST_DOWNLOAD

Code

tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/nasa_10_nf_tr.RData")$mtime)) %>%
  print_table_conditional()

LAST_DOWNLOAD
2024-10-08

LAST_COMPILE

LAST_COMPILE
2024-11-05

Last

Code

nasa_10_f_tr %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()

time	Nobs
2023	179615

unit

Code

nasa_10_f_tr %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

unit	Unit	Nobs
MIO_NAC	Million units of national currency	2510677
MIO_EUR	Million euro	2426923
PC_GDP	Percentage of gross domestic product (GDP)	2410898
PCH_PRE	Percentage change on previous period	667568
PC_LE	NA	1248

co_nco

Code

nasa_10_f_tr %>%
  left_join(co_nco, by = "co_nco") %>%
  group_by(co_nco, Co_nco) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

co_nco	Co_nco	Nobs
NCO	Non-consolidated	4094125
CO	Consolidated	3923189

sector

Code

nasa_10_f_tr %>%
  left_join(sector, by = "sector") %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

finpos

Code

nasa_10_f_tr %>%
  left_join(finpos, by = "finpos") %>%
  group_by(finpos, Finpos) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

finpos	Finpos	Nobs
ASS	Assets	4070398
LIAB	Liabilities	3946916

na_item

Code

load_data("eurostat/na_item.RData")
nasa_10_f_tr %>%
  left_join(na_item, by = "na_item") %>%
  group_by(na_item, Na_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

geo

Code

nasa_10_f_tr %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}