Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/nrg_ti_gasm.RData")$mtime)) %>%
print_table_conditional()
LAST_DOWNLOAD |
---|
2024-10-08 |
Data - Eurostat
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/nrg_ti_gasm.RData")$mtime)) %>%
print_table_conditional()
LAST_DOWNLOAD |
---|
2024-10-08 |
LAST_COMPILE |
---|
2024-11-22 |
%>%
nrg_ti_gasm group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2024M09 | 634 |
%>%
nrg_ti_gasm left_join(siec, by = "siec") %>%
group_by(siec, Siec) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
siec | Siec | Nobs |
---|---|---|
G3000 | Natural gas | 1057899 |
G3200 | Liquefied natural gas | 927809 |
%>%
nrg_ti_gasm left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
unit | Unit | Nobs |
---|---|---|
TJ_GCV | Terajoule (gross calorific value - GCV) | 1059172 |
MIO_M3 | Million cubic metres | 926536 |
%>%
nrg_ti_gasm 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 .} {
%>%
nrg_ti_gasm group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
print_table_conditional()