Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/env_ac_aigg_q.RData")$mtime)) %>%
print_table_conditional()
LAST_DOWNLOAD |
---|
2024-10-08 |
Data - Eurostat
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/env_ac_aigg_q.RData")$mtime)) %>%
print_table_conditional()
LAST_DOWNLOAD |
---|
2024-10-08 |
LAST_COMPILE |
---|
2024-11-05 |
%>%
env_ac_aigg_q group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2024Q1 | 110 |
%>%
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) | 6176 |
%>%
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 | 4673 |
A | Agriculture, forestry and fishing | 167 |
B | Mining and quarrying | 167 |
C | Manufacturing | 167 |
D | Electricity, gas, steam and air conditioning supply | 167 |
E | Water supply; sewerage, waste management and remediation activities | 167 |
F | Construction | 167 |
G-U_X_H | Services (except transportation and storage) | 167 |
H | Transportation and storage | 167 |
HH | Total activities by households | 167 |
%>%
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 | 2109 |
T_HAB | Tonnes per capita | 2106 |
PCH_SM | Percentage change compared to same period in previous year | 1961 |
%>%
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 .} {