Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/nrg_ind_ren.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2026-01-30 |
Data - Eurostat
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/nrg_ind_ren.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2026-01-30 |
| LAST_COMPILE |
|---|
| 2026-01-31 |
nrg_ind_ren %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2024 | 169 |
nrg_ind_ren %>%
left_join(nrg_bal, by = "nrg_bal") %>%
group_by(nrg_bal, Nrg_bal) %>%
summarise(Nobs = n()) %>%
print_table_conditional()| nrg_bal | Nrg_bal | Nobs |
|---|---|---|
| REN | Renewable energy sources | 773 |
| REN_ELC | Renewable energy sources in electricity | 773 |
| REN_HEAT_CL | Renewable energy sources in heating and cooling | 773 |
| REN_HEAT_CL_WHC | Renewable energy sources in heating and cooling - waste heat and cold | 32 |
| REN_TRA | Renewable energy sources in transport | 773 |
| REN_WHC_DHEAT_DCL | Renewable energy sources and waste heat and cold - district heating and cooling | 36 |
nrg_ind_ren %>%
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_ind_ren %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2024 | 169 |
| 2023 | 173 |
| 2022 | 173 |
| 2021 | 173 |
| 2020 | 148 |
| 2019 | 148 |
| 2018 | 148 |
| 2017 | 148 |
| 2016 | 148 |
| 2015 | 148 |
| 2014 | 148 |
| 2013 | 144 |
| 2012 | 144 |
| 2011 | 144 |
| 2010 | 144 |
| 2009 | 144 |
| 2008 | 144 |
| 2007 | 144 |
| 2006 | 144 |
| 2005 | 144 |
| 2004 | 140 |
nrg_ind_ren %>%
filter(time == "2020") %>%
left_join(nrg_bal, by = "nrg_bal") %>%
left_join(geo, by = "geo") %>%
select(geo, Geo, Nrg_bal, values) %>%
spread(Nrg_bal, values) %>%
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_ind_ren %>%
filter(time == "2019") %>%
left_join(nrg_bal, by = "nrg_bal") %>%
left_join(geo, by = "geo") %>%
select(geo, Geo, Nrg_bal, values) %>%
spread(Nrg_bal, values) %>%
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 .}