tibble(DOWNLOAD_TIME = as.Date(file.info("~/Dropbox/website/data/eurostat/tec00016.RData")$mtime)) %>%
print_table_conditional()
DOWNLOAD_TIME |
---|
2023-04-16 |
%>%
tec00016 group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2022 | 68 |
%>%
tec00016 left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
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 .} {
%>%
tec00016 left_join(na_item, by = "na_item") %>%
group_by(na_item, Na_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
na_item | Na_item | Nobs |
---|---|---|
D2X3 | Taxes on production and imports less subsidies | 916 |
%>%
tec00016 left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
unit | Unit | Nobs |
---|---|---|
CP_MEUR | Current prices, million euro | 461 |
PC_GDP | Percentage of gross domestic product (GDP) | 455 |
%>%
tec00016 group_by(time) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
time | Nobs |
---|---|
2011 | 77 |
2012 | 77 |
2013 | 79 |
2014 | 79 |
2015 | 79 |
2016 | 79 |
2017 | 78 |
2018 | 78 |
2019 | 78 |
2020 | 74 |
2021 | 70 |
2022 | 68 |
%>%
tec00016 filter(time == "2020",
== "PC_GDP") %>%
unit select_if(~ n_distinct(.) > 1) %>%
left_join(geo, by = "geo") %>%
print_table_conditional