Gas prices for household consumers - bi-annual data (from 2007 onwards)

Data - Eurostat

Author

François Geerolf

Info

source dataset Title .html .rData
eurostat nrg_pc_202 Gas prices for household consumers - bi-annual data (from 2007 onwards) 2025-10-10 2025-10-10

Data on energy

source dataset Title .html .rData
eurostat nrg_pc_202 Gas prices for household consumers - bi-annual data (from 2007 onwards) 2025-10-10 2025-10-10
ec WOB Weekly Oil Bulletin 2025-08-28 2024-08-25
eurostat ei_isen_m Energy - monthly data 2025-10-10 2025-09-26
eurostat nrg_bal_c Complete energy balances 2023-12-31 2025-10-10
eurostat nrg_pc_203 Gas prices for non-household consumers - bi-annual data (from 2007 onwards) 2023-06-11 2025-10-09
eurostat nrg_pc_203_c Gas prices components for non-household consumers - annual data 2025-10-10 2025-10-10
eurostat nrg_pc_203_h Gas prices for industrial consumers - bi-annual data (until 2007) 2025-10-10 2025-10-09
eurostat nrg_pc_203_v Non-household consumption volumes of gas by consumption bands 2025-10-10 2025-10-10
eurostat nrg_pc_204 Electricity prices for household consumers - bi-annual data (from 2007 onwards) 2025-10-10 2025-10-11
eurostat nrg_pc_205 Electricity prices for non-household consumers - bi-annual data (from 2007 onwards) 2023-06-11 2025-10-10
fred energy Energy 2025-10-09 2025-10-09
iea world_energy_balances_highlights_2022 World Energy Balances Highlights (2022 edition) 2024-06-20 2023-04-24
wb CMO World Bank Commodity Price Data (The Pink Sheet) 2025-08-24 2025-08-24
wdi EG.GDP.PUSE.KO.PP.KD GDP per unit of energy use (constant 2017 PPP $ per kg of oil equivalent) 2025-10-10 2025-09-27
wdi EG.USE.PCAP.KG.OE Energy use (kg of oil equivalent per capita) 2025-10-10 2025-09-27
yahoo energy Energy 2025-09-22 2025-10-11

LAST_COMPILE

LAST_COMPILE
2025-10-11

Last

Code 
nrg_pc_202 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2025S1 918

Info

  • Electricity and gas prices stabilise in 2023. html

  • Electricity and gas prices in the first half of 2022. html / png

Code 
include_graphics("https://ec.europa.eu/eurostat/documents/4187653/14185664/Gas+and+Electricity+Prices+S1_2022.png")

nrg_cons

Code 
nrg_pc_202 %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  group_by(nrg_cons, Nrg_cons) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
nrg_cons Nrg_cons Nobs
GJ20-199 Consumption from 20 GJ to 199 GJ - band D2 19386
GJ_GE200 Consumption 200 GJ or over - band D3 18904
GJ_LT20 Consumption less than 20 GJ - band D1 19350
TOT_GJ Consumption of GJ - all bands 618

currency

Code 
nrg_pc_202 %>%
  left_join(currency, by = "currency") %>%
  group_by(currency, Currency) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
currency Currency Nobs
EUR Euro 20236
NAC National currency 19260
PPS Purchasing Power Standard 18762

tax

Code 
nrg_pc_202 %>%
  left_join(tax, by = "tax") %>%
  group_by(tax, Tax) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
tax Tax Nobs
I_TAX All taxes and levies included 19420
X_TAX Excluding taxes and levies 19419
X_VAT Excluding VAT and other recoverable taxes and levies 19419

unit

Code 
nrg_pc_202 %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
unit Unit Nobs
KWH Kilowatt-hour 29130
GJ_GCV Gigajoule (gross calorific value - GCV) 29128

geo

Code 
nrg_pc_202 %>%
  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

Code 
nrg_pc_202 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()

Band D1 : Consumption < 20 GJ

France, Germany, Italy, Spain

All

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2016-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

France, Germany, Europe, Spain

Bar

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         nrg_cons == "GJ_LT20",
         currency == "EUR",
         unit == "KWH",
         time %in% c("2021S2", "2022S1", "2022S2", "2023S1")) %>%
  select_if(~n_distinct(.) > 1) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  spread(tax, values) %>%
  transmute(time, Geo,
            ` Taxes except VAT` = X_VAT-X_TAX,
            `  VAT` = I_TAX-X_VAT,
            `Excluding taxes` = X_TAX) %>%
  gather(Tax, values, - time, -Geo) %>%
  ggplot(., aes(x = time, y = values, fill = Tax)) + 
  geom_bar(stat = "identity",
           position = "stack") +
  facet_grid(~ Geo) + theme_minimal() +
theme(legend.position = "none",
      legend.title = element_blank()) +
  scale_fill_manual(values = viridis(3)[1:3]) +
  scale_y_continuous(breaks = seq(-30, 30, .05),
                labels = dollar_format(a = .01, pre = "", su = "€/kWh"),
                limits = c(0, 0.2))  +
  xlab("Semester") + ylab("") +
  ggtitle("Natural gas price, LOW Consumption")

All

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2016-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2020-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2020-01-01")) %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

Greece, Belgium, Austria, Portugal

All

Code 
nrg_pc_202 %>%
  filter(geo %in% c("EL", "BE", "AT", "PT"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2016-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("EL", "BE", "AT", "PT"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_LT20",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Band D1 : Consumption < 20 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

Band D2 : 20 GJ < Consumption < 200 GJ

France, Germany, Italy, Spain

All

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ20-199",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("20 GJ < Consumption < 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.12, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2016-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ20-199",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("20 GJ < Consumption < 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.12, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

Band D3 : Consumption > 200 GJ

France, Germany, Italy, Spain

All

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_GE200",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Consumption > 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.12, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2016-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_GE200",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Consumption > 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.12, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2020-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "IT", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_GE200",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2020-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Consumption > 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.12, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

France, Germany, Europe, Spain

Bar

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         nrg_cons == "GJ_GE200",
         currency == "EUR",
         unit == "KWH",
         time %in% c("2021S2", "2022S1", "2022S2")) %>%
  select_if(~n_distinct(.) > 1) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  spread(tax, values) %>%
  transmute(time, Geo,
            ` Taxes except VAT` = X_VAT-X_TAX,
            `  VAT` = I_TAX-X_VAT,
            `Excluding taxes` = X_TAX) %>%
  gather(Tax, values, - time, -Geo) %>%
  ggplot(., aes(x = time, y = values, fill = Tax)) + 
  geom_bar(stat = "identity",
           position = "stack") +
  facet_grid(~ Geo) + theme_minimal() +
theme(legend.position = "none",
      legend.title = element_blank()) +
  scale_fill_manual(values = viridis(3)[1:3]) +
  scale_y_continuous(breaks = seq(-30, 30, .05),
                labels = dollar_format(a = .01, pre = "", su = "€/kWh"))  +
  xlab("") + ylab("") +
  ggtitle("Natural gas price, HIGH Consumption")

All

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_GE200",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Consumption > 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2016-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_GE200",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2016-01-01")) %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Consumption > 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

2020-

Code 
nrg_pc_202 %>%
  filter(geo %in% c("FR", "DE", "EA", "ES"),
         tax %in% c("I_TAX", "X_TAX"),
         unit == "KWH",
         nrg_cons == "GJ_GE200",
         currency == "EUR") %>%
  left_join(geo, by = "geo") %>%
  left_join(tax, by = "tax") %>%
  semester_to_date %>%
  filter(date >= as.Date("2020-01-01")) %>%
  mutate(Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color, linetype = Tax)) +
  scale_color_identity() + theme_minimal()  + add_8flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Consumption > 200 GJ") +
  scale_y_log10(breaks = seq(0.02, 0.2, 0.01),
                labels = dollar_format(a = .01, pre = "", su = "€"))

Example

France

Code 
nrg_pc_202 %>%
  filter(geo == "FR",
         unit == "KWH",
         currency == "EUR") %>%
  left_join(tax, by = "tax") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  semester_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons, linetype = Tax)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 1, 0.01)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())

Germany

Code 
nrg_pc_202 %>%
  filter(geo == "DE",
         unit == "KWH",
         currency == "EUR") %>%
  left_join(tax, by = "tax") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  semester_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons, linetype = Tax)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 1, 0.01)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())

Italy

Code 
nrg_pc_202 %>%
  filter(geo == "IT",
         unit == "KWH",
         currency == "EUR") %>%
  left_join(tax, by = "tax") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  semester_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons, linetype = Tax)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 1, 0.01)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())

Spain

Code 
nrg_pc_202 %>%
  filter(geo == "ES",
         unit == "KWH",
         currency == "EUR") %>%
  left_join(tax, by = "tax") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  semester_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons, linetype = Tax)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 1, 0.01)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())