Household consumption volumes of gas by consumption bands

Data - Eurostat

Author

François Geerolf

Info

LAST_COMPILE

LAST_COMPILE
2024-11-05

Last

Code 
nrg_pc_202_v %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2023 91

Info

  • 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_v %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  group_by(nrg_cons, Nrg_cons) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
nrg_cons Nrg_cons Nobs
GJ20-199 Consumption from 20 GJ to 199 GJ - band D2 225
GJ_LT20 Consumption less than 20 GJ - band D1 225
GJ_GE200 Consumption 200 GJ or over - band D3 213

geo

Code 
nrg_pc_202_v %>%
  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_v %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()
time Nobs
2023 91
2022 95
2021 94
2020 97
2019 101
2018 97
2017 88

Example

France

Code 
nrg_pc_202_v %>%
  filter(geo == "FR") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(1, 100, 1)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())

Germany

Code 
nrg_pc_202_v %>%
  filter(geo == "DE") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(1, 100, 1)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())

Italy

Code 
nrg_pc_202_v %>%
  filter(geo == "IT") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(1, 100, 1)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())

Spain

Code 
nrg_pc_202_v %>%
  filter(geo == "ES") %>%
  left_join(nrg_cons, by = "nrg_cons") %>%
  select_if(~ n_distinct(.) > 1) %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values, color = Nrg_cons)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(1, 100, 1)) +
  theme(legend.position = c(0.45, 0.7),
        legend.title = element_blank())