LAST_COMPILE |
---|
2023-06-11 |
nrg_pc_205 %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2022S2 | 2496 |
nrg_pc_205 %>%
left_join(consom, by = "consom") %>%
group_by(consom, Consom) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
consom | Consom | Nobs |
---|---|---|
4162901 | Band IA : Consumption < 20 MWh | 10008 |
4162902 | Band IB : 20 MWh < Consumption < 500 MWh | 10002 |
4162903 | Band IC : 500 MWh < Consumption < 2 000 MWh | 10140 |
4162904 | Band ID : 2 000 MWh < Consumption < 20 000 MWh | 9990 |
4162905 | Band IE : 20 000 MWh < Consumption < 70 000 MWh | 9792 |
4162906 | Band IF : 70 000 MWh < Consumption < 150 000 MWh | 9225 |
4162907 | Band IG : Consumption > 150 000 MWh | 5550 |
TOT_KWH | Consumption of kWh - all bands | 864 |
nrg_pc_205 %>%
left_join(currency, by = "currency") %>%
group_by(currency, Currency) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
currency | Currency | Nobs |
---|---|---|
EUR | Euro | 22690 |
NAC | National currency | 21685 |
PPS | Purchasing Power Standard | 21196 |
nrg_pc_205 %>%
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 | 21892 |
X_VAT | Excluding VAT and other recoverable taxes and levies | 21892 |
X_TAX | Excluding taxes and levies | 21787 |
nrg_pc_205 %>%
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_pc_205 %>%
filter(geo %in% c("FR", "DE", "EA", "ES"),
consom == "4162901",
currency == "EUR",
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 = c(0.2, 0.9),
legend.title = element_blank()) +
scale_fill_manual(values = viridis(3)[1:3]) +
scale_y_continuous(breaks = seq(-30, 30, .1),
labels = dollar_format(a = .1, pre = "", su = "€/kWh"),
limits = c(0, 0.6)) +
xlab("Semester") + ylab("") +
ggtitle("Electricity price, LOW Consumption")
nrg_pc_205 %>%
filter(geo %in% c("FR", "DE", "EA", "ES"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162901",
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, 2025, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("Electricity Prices - C < 1 000 kWh") +
scale_y_log10(breaks = seq(-30, 30, .1),
labels = dollar_format(a = .1, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo %in% c("FR", "DE", "EA", "ES"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162901",
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, 2025, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("Band DA : Consumption < 1 000 kWh") +
scale_y_log10(breaks = seq(-30, 30, .1),
labels = dollar_format(a = .1, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo %in% c("FR", "DE", "IT", "ES"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162901",
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, 2025, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("Electricity Prices - C < 1 000 kWh") +
scale_y_log10(breaks = seq(-30, 30, .1),
labels = dollar_format(a = .1, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo %in% c("NL"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162901",
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_2flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.3),
legend.title = element_blank()) +
xlab("") + ylab("Electricity Prices - C < 1 000 kWh") +
scale_y_continuous(breaks = seq(-30, 30, .1),
labels = dollar_format(a = .1, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo %in% c("EL", "BE", "AT", "PT"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162901",
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, 2025, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.9),
legend.title = element_blank()) +
xlab("") + ylab("Electricity Prices - C < 1 000 kWh") +
scale_y_log10(breaks = seq(-30, 30, .1),
labels = dollar_format(a = .1, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo %in% c("FR", "DE", "IT", "ES"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162902",
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, 2025, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.9),
legend.title = element_blank()) +
xlab("") + ylab("Electricity Prices - 1 000 kWh < C < 2 500 kWh") +
scale_y_log10(breaks = c(0.12, 0.15, 0.18, 0.2, 0.25, 0.3, 0.35),
labels = dollar_format(a = .01, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo %in% c("FR", "DE", "EA", "ES"),
consom == "4162907",
currency == "EUR",
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, .1),
labels = dollar_format(a = .1, pre = "", su = "€/kWh"),
limits = c(0, 0.6)) +
xlab("Semester") + ylab("") +
ggtitle("Electricity price, HIGH Consumption")
nrg_pc_205 %>%
filter(geo %in% c("FR", "DE", "EA", "ES"),
tax %in% c("I_TAX", "X_TAX"),
consom == "4162907",
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, 2025, 1), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("Band DE : Consumption > 15 000 kWh") +
scale_y_log10(breaks = seq(-30, 30, .05),
labels = dollar_format(a = .01, pre = "", su = "€"))
nrg_pc_205 %>%
filter(geo == "EA",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "EA",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
filter(date >= as.Date("2020-01-01")) %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
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(0, 1, 0.01)) +
theme(legend.position = c(0.45, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "FR",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
ggplot + geom_line(aes(x = date, y = values, color = Consom, linetype = Tax)) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "FR",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
filter(date >= as.Date("2020-01-01")) %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "DE",
unit == "KWH",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "IT",
unit == "KWH",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "ES",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))
nrg_pc_205 %>%
filter(geo == "NL",
currency == "EUR") %>%
left_join(tax, by = "tax") %>%
left_join(consom, by = "consom") %>%
select_if(~ n_distinct(.) > 1) %>%
semester_to_date %>%
ggplot + geom_line(aes(x = date, y = values, color = paste0(Tax, " - ", Consom))) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1920, 2025, 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, 0.5),
legend.title = element_blank(),
legend.text = element_text(size = 8),
legend.key.size = unit(0.9, 'lines'))