FIX020_raw <-
statgl_url("FIX021", lang = language) %>%
statgl_fetch(
species = px_all(),
area = px_all(),
form = px_all(),
time = px_all(),
.col_code = TRUE
) %>%
as_tibble()
vec <- 7:8
names(vec) <- c(sdg14$figs$fig0$cols$col1[language], sdg14$figs$fig0$cols$col2[language])
FIX020 <-
FIX020_raw %>%
mutate(
species = species %>% fct_inorder(),
form = form %>% fct_inorder(),
time = time %>% as.numeric()
) %>%
spread(form, value) %>%
rename(
"Rådgivning" = 4,
"Kvotex" = 5,
"Fangstx" = 6
) %>%
filter(Kvotex > 0) %>%
mutate(
Kvoteafvigelse = Kvotex - Rådgivning,
Fangstafvigelse = Fangstx - Rådgivning
) %>%
rename(vec) %>%
select(-c(4:6)) %>%
gather(key, value, -(1:3)) %>%
mutate(value = value / 1000)
FIX020 %>%
filter(species == unique(FIX020[[1]])[1]) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
scale_y_continuous(breaks= scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
facet_wrap(~ area) +
labs(
title = unique(FIX020[[1]])[1],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$units$`1000_ton`[language] %>% unlist(),
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap_fish[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[2]) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
facet_wrap(~ area) +
labs(
title = unique(FIX020[[1]])[2],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$units$`1000_ton`[language] %>% unlist(),
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap_fish[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[3]) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
facet_wrap(~ area) +
labs(
title = unique(FIX020[[1]])[3],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$units$`1000_ton`[language] %>% unlist(),
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap_fish[language]
)
Statistikbanken
FIX020_raw <-
statgl_url("FIX020", lang = language) %>%
statgl_fetch(
species = px_all(),
area = px_all(),
form = px_all(),
time = px_all(),
.col_code = TRUE
) %>%
as_tibble()
vec <- 7:8
names(vec) <- c(sdg14$figs$fig0$cols$col1[language], sdg14$figs$fig0$cols$col2[language])
FIX020 <-
FIX020_raw %>%
mutate(
form = form %>% fct_inorder(),
area = area %>% fct_inorder(),
time = time %>% as.numeric()
) %>%
spread(form, value) %>%
rename(
"Rådgivning" = 4,
"Kvote" = 5,
"Fangst" = 6
) %>%
mutate(
Kvoteafvigelse = Kvote - Rådgivning,
Fangstafvigelse = Fangst - Rådgivning
) %>%
rename(vec) %>%
filter(Kvote > 0) %>%
select(-(4:6)) %>%
gather(key, value, -c(species, area, time))
FIX020 %>%
filter(species == unique(FIX020[[1]])[6]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[6],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[5]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[5],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[4]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[4],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[1]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[1],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[2]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[2],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[3]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[3],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[7]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[7],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
FIX020 %>%
filter(species == unique(FIX020[[1]])[8]) %>%
mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>%
ggplot(aes(
x = time,
y = value,
color = key
)) +
geom_hline(yintercept = 0, color = "red", size = 3, linetype = "dotted") +
geom_line(size = 2) +
facet_wrap( ~ area) +
scale_y_continuous(breaks = scales:: pretty_breaks()) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = unique(FIX020[[1]])[8],
subtitle = sdg14$figs$fig0$sub[language],
y = sdg14$figs$fig0$y_lab[language],
x = " ",
color = " ",
caption = sdg14$figs$fig0$cap[language]
)
Statistikbanken
# Import
NRX0418_raw <-
statgl_url("NRX0418", lang = language) %>%
statgl_fetch(
units = "K",
industry = c("BVTTOT", "BVT0301", "BVT0302", "BVT0303"),
time = px_all(),
.col_code = TRUE
) %>%
as_tibble()
NRX0418_raw %>%
mutate(time = time %>% as.numeric()) %>%
mutate(industry = industry %>% str_remove_all("[:digit:]") %>% trimws()) %>%
ggplot(aes(
x = time,
y = value/1e3,
color = industry
)) +
geom_line(size = 2) +
facet_wrap(~ industry, scales = "free") +
theme_statgl() +
theme(legend.position = "none") +
scale_color_statgl() +
labs(
title = sdg14$figs$fig9$title[language],
subtitle = NRX0418_raw %>% pull(units) %>% unique(),
y = sdg14$figs$fig9$y_lab[language],
x = " ",
caption = sdg14$figs$fig9$cap[language]
)
Statistikbanken NRX13_raw <-
statgl_url("NRX13", lang = language) %>%
statgl_fetch(
Kode = c("VBVT0301", "VBVT0302", "VBVT0303"),
Aar = px_all(),
.col_code = TRUE
) %>%
as_tibble() %>%
rename("industry" = 1, "time" = 2)
NRX13_raw %>%
drop_na() %>%
mutate(industry = industry %>% str_remove_all("[:digit:]") %>% trimws() %>% fct_rev()) %>%
mutate(time = time %>% as.numeric()) %>%
ggplot(aes(
x = time,
y = value,
color = industry
)) +
geom_line(size = 2) +
geom_hline(yintercept = 0, linetype = "dashed") +
facet_wrap(~ industry, scales = "free", ncol = 1) +
scale_y_continuous(labels = scales::percent_format(
scale = 1
)) +
theme_statgl() +
theme(legend.position = "none") +
scale_color_statgl() +
labs(
title = sdg14$figs$fig11$title[language],
y = sdg14$figs$fig11$y_lab[language],
x = " ",
caption = sdg14$figs$fig11$cap[language]
)
Statistikbanken