Energy use (kg of oil equivalent per capita)

Data - WDI

Author

Info

Related energy datasets

source	dataset	Title	Download	Compile
wdi	EG.USE.PCAP.KG.OE	Energy use (kg of oil equivalent per capita)	2024-09-18	[2024-09-15]
ec	WOB	Weekly Oil Bulletin	2024-08-25	[2024-09-15]
eurostat	ei_isen_m	Energy - monthly data	2024-09-14	[2024-09-15]
eurostat	nrg_bal_c	Complete energy balances	2024-09-15	[2023-12-31]
eurostat	nrg_pc_202	Gas prices for household consumers - bi-annual data (from 2007 onwards)	2024-09-18	[2024-09-15]
eurostat	nrg_pc_203	Gas prices for non-household consumers - bi-annual data (from 2007 onwards)	2024-09-15	[2023-06-11]
eurostat	nrg_pc_203_c	Gas prices components for non-household consumers - annual data	2024-09-15	[2024-09-15]
eurostat	nrg_pc_203_h	Gas prices for industrial consumers - bi-annual data (until 2007)	2024-09-15	[2024-09-15]
eurostat	nrg_pc_203_v	Non-household consumption volumes of gas by consumption bands	2024-09-18	[2024-09-15]
eurostat	nrg_pc_204	Electricity prices for household consumers - bi-annual data (from 2007 onwards)	2024-09-15	[2024-09-15]
eurostat	nrg_pc_205	Electricity prices for non-household consumers - bi-annual data (from 2007 onwards)	2024-09-18	[2023-06-11]
fred	energy	Energy	2024-09-14	[2024-09-14]
iea	world_energy_balances_highlights_2022	World Energy Balances Highlights (2022 edition)	2023-04-24	[2024-06-20]
wb	CMO	World Bank Commodity Price Data (The Pink Sheet)	2024-05-23	[2024-06-20]
wdi	EG.GDP.PUSE.KO.PP.KD	GDP per unit of energy use (constant 2017 PPP $ per kg of oil equivalent)	2024-09-18	[2024-09-18]
yahoo	energy	Energy	2024-09-18	[2024-09-18]

Nobs - Javascript

Code

EG.USE.PCAP.KG.OE %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  mutate(value = round(value, 2)) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `GDP per unit of energy use 1` = first(value),
            `Year 2` = last(year),
            `GDP per unit of energy use 2` = last(value)) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

France, Germany, Italy

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("IT", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))

Japan, Switzerland

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("JP", "CH")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))

China, United States

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("CN", "US")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))

China, France, Germany

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("CN", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))

Spain, United Kingdom, United States

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("US", "GB", "ES")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))

Argentina, Chile, Venezuela

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("AR", "CL", "VE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))

Greece, Hong Kong, Mexico

Code

EG.USE.PCAP.KG.OE %>%
  filter(iso2c %in% c("GR", "HK", "MX")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = Iso2c, linetype = Iso2c) +
  xlab("") + ylab("GDP per unit of energy use") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-60, 100, 2))