Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/env_ac_aigg_q.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2026-01-30 |
Data - Eurostat
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/env_ac_aigg_q.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2026-01-30 |
| LAST_COMPILE |
|---|
| 2026-01-31 |
env_ac_aigg_q %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2025Q2 | 222 |
env_ac_aigg_q %>%
left_join(airpol, by = "airpol") %>%
group_by(airpol, Airpol) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| airpol | Airpol | Nobs |
|---|---|---|
| GHG | Greenhouse gases (CO2, N2O in CO2 equivalent, CH4 in CO2 equivalent, HFC in CO2 equivalent, PFC in CO2 equivalent, SF6 in CO2 equivalent, NF3 in CO2 equivalent) | 13468 |
env_ac_aigg_q %>%
left_join(nace_r2, by = "nace_r2") %>%
group_by(nace_r2, Nace_r2) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| nace_r2 | Nace_r2 | Nobs |
|---|---|---|
| TOTAL_HH | All NACE activities plus households | 10192 |
| A | Agriculture, forestry and fishing | 364 |
| B | Mining and quarrying | 364 |
| C | Manufacturing | 364 |
| D | Electricity, gas, steam and air conditioning supply | 364 |
| E | Water supply; sewerage, waste management and remediation activities | 364 |
| F | Construction | 364 |
| G-U_X_H | Services (except transportation and storage) | 364 |
| H | Transportation and storage | 364 |
| HH | Total activities by households | 364 |
env_ac_aigg_q %>%
left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| unit | Unit | Nobs |
|---|---|---|
| THS_T | Thousand tonnes | 4588 |
| T_HAB | Tonnes per capita | 4588 |
| PCH_SM | Percentage change compared to same period in previous year | 4292 |
env_ac_aigg_q %>%
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 .}