Complete energy balances
Data - Eurostat
François Geerolf
Info
LAST_DOWNLOAD
| source | dataset | Title | Download | Compile |
|---|---|---|---|---|
| eurostat | nrg_pc_204 | Electricity prices for household consumers - bi-annual data (from 2007 onwards) | 2023-12-31 | 2023-06-08 |
| ec | WOB | Weekly Oil Bulletin | 2023-11-16 | 2023-11-16 |
| eurostat | ei_isen_m | Energy - monthly data | 2023-12-24 | 2023-12-31 |
| eurostat | nrg_bal_c | Complete energy balances | 2023-12-24 | 2023-12-24 |
| eurostat | nrg_pc_202 | Gas prices for household consumers - bi-annual data (from 2007 onwards) | 2023-12-24 | 2023-06-08 |
| eurostat | nrg_pc_203 | Gas prices for non-household consumers - bi-annual data (from 2007 onwards) | 2023-12-24 | 2023-06-11 |
| eurostat | nrg_pc_203_c | Gas prices components for non-household consumers - annual data | 2023-12-24 | 2023-12-24 |
| eurostat | nrg_pc_203_h | Gas prices for industrial consumers - bi-annual data (until 2007) | 2023-12-24 | 2023-12-24 |
| eurostat | nrg_pc_203_v | Non-household consumption volumes of gas by consumption bands | 2023-12-24 | 2023-12-24 |
| eurostat | nrg_pc_205 | Electricity prices for non-household consumers - bi-annual data (from 2007 onwards) | 2023-12-24 | 2023-06-11 |
| fred | energy | Energy | 2023-12-31 | 2023-12-31 |
| iea | world_energy_balances_highlights_2022 | World Energy Balances Highlights (2022 edition) | 2023-04-24 | 2023-04-24 |
| wb | CMO | World Bank Commodity Price Data (The Pink Sheet) | 2023-06-11 | 2022-11-15 |
| wdi | EG.GDP.PUSE.KO.PP.KD | GDP per unit of energy use (constant 2017 PPP $ per kg of oil equivalent) | 2023-04-26 | 2023-12-24 |
| wdi | EG.USE.PCAP.KG.OE | Energy use (kg of oil equivalent per capita) | 2023-04-26 | 2023-12-24 |
| yahoo | energy | Energy | 2023-11-16 | 2023-11-16 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2023-12-31 |
Last
nrg_bal_c %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2021 | 1148634 |
nrg_bal
siec
unit
List
nrg_bal_c %>%
left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| unit | Unit | Nobs |
|---|---|---|
| GWH | Gigawatt-hour | 11944080 |
| KTOE | Thousand tonnes of oil equivalent | 11944080 |
| TJ | Terajoule | 11944080 |
geo
nrg_bal_c %>%
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 .}time
Share of fuels in the final energy consumption in the residential sector, 2019 (%)
Interactive
nrg_bal_c %>%
filter(time == "2020",
nrg_bal == "FC_OTH_HH_E",
siec %in% c("E7000", "G3000", "FE", "RA000", "H8000", "TOTAL"),
unit == "GWH") %>%
select(-time, -nrg_bal, -unit) %>%
left_join(siec, by = "siec") %>%
group_by(geo) %>%
mutate(values = round(100*values/values[siec == "TOTAL"], 1)) %>%
filter(siec != "TOTAL") %>%
select(-siec) %>%
spread(Siec, values) %>%
left_join(geo, by = "geo") %>%
ungroup %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
select(-geo) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, Geo, `Natural gas`, everything()) %>%
arrange(-`Natural gas`) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}