Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/nasa_10_nf_tr.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2026-02-02 |
Data - Eurostat
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/nasa_10_nf_tr.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2026-02-02 |
| LAST_COMPILE |
|---|
| 2026-02-03 |
nasa_10_f_tr %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2024 | 327000 |
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 | 3073485 |
| MIO_EUR | Million euro | 3019994 |
| PC_GDP | Percentage of gross domestic product (GDP) | 3002728 |
| PCH_PRE | Percentage change on previous period | 1080807 |
| PC_LE | NA | 1333 |
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 | 5195145 |
| CO | Consolidated | 4983202 |
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 .}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 |
|---|---|---|
| LIAB | Liabilities | 5116467 |
| ASS | Assets | 5061880 |
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 .}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 .}