Tilbage

---

Delmål 14: Livet i havet

Forbrug af havets ressourcer

---

GS Forbrug af havets ressourcer

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    time > year(Sys.time()) - 6,
    species == unique(FIX020_raw[[1]])[1],
    area %in% unique(FIX020_raw[[2]])[1:2]
    ) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>% fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab["species"] %>% table()) %>% 
  pack_rows(index = tab["area"] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$ton[language] %>% unlist(), notation = "symbol")

	2020	2021	2022
Rejer
Vestgrønland
Fangst	107.860	108.352	112.659
Kvote	108.383	113.777	113.777
Rådgivning	108.383	113.777	113.777
Østgrønland
Fangst	3.172	3.071	5.510
Kvote	4.750	7.000	6.850
Rådgivning	2.000	3.000	3.000
* Ton

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    time > year(Sys.time()) - 6,
    species == unique(FIX020_raw[[1]])[2],
    area != unique(FIX020_raw[[2]])[3]
    ) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>% fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab["species"] %>% table()) %>% 
  pack_rows(index = tab["area"] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$ton[language] %>% unlist(), notation = "symbol")

	2020	2021	2022
Hellefisk
Vestgrønland
Fangst	18.146	17.989	18.112
Kvote	18.184	18.184	18.185
Rådgivning	18.184	18.184	18.185
Østgrønland
Fangst	7.046	8.255	8.933
Kvote	8.031	8.847	10.020
Rådgivning	8.010	8.847	10.020
* Ton

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    time > year(Sys.time()) - 6,
    species == unique(FIX020_raw[[1]])[3],
    area %in% unique(FIX020_raw[[2]])[c(1, 3)]
    ) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>% fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab["species"] %>% table()) %>% 
  pack_rows(index = tab["area"] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$ton[language] %>% unlist(), notation = "symbol")

	2020	2021	2022
Torsk
Vest- Østgrønland
Fangst	15.807	16.146	21.487
Kvote	18.824	26.091	21.630
Rådgivning	3.409	6.091	8.708
Vestgrønland
Fangst	NA	NA	NA
Kvote	NA	NA	NA
Rådgivning	NA	NA	NA
* Ton

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[6],
    area != unique(FIX020_raw[[2]])[3]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Narhval
Vestgrønland
Fangst	84	235
Kvote	251	251
Rådgivning	251	251
Qaanaaq
Fangst	93	94
Kvote	103	118
Rådgivning	103	98
Melville bugt
Fangst	52	70
Kvote	70	70
Rådgivning	70	70
Østgrønland
Fangst	57	20
Kvote	50	60
Rådgivning	0	0
* Antal

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[5],
    area %in% unique(FIX020_raw[[2]])[1:2]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Isbjørn
Vestgrønland
Fangst	80	86
Kvote	92	92
Rådgivning	92	92
Østgrønland
Fangst	73	51
Kvote	64	64
Rådgivning	54	54
* Antal

Forbrug af havets ressourcer - 2

GS Forbrug af havets ressourcer - 2

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[4],
    area %in% unique(FIX020_raw[[2]])[c(1, 4)]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Hvidhval
Vestgrønland
Fangst	182	139
Kvote	320	265
Rådgivning	320	265
Qaanaaq
Fangst	12	9
Kvote	20	29
Rådgivning	20	37
* Antal

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[1],
    area %in% unique(FIX020_raw[[2]])[c(1)]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Finhval
Vestgrønland
Fangst	3	2
Kvote	19	19
Rådgivning	19	19
* Antal

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[2],
    area %in% unique(FIX020_raw[[2]])[c(1)]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Grønlandshval
Vestgrønland
Fangst	0	0
Kvote	2	2
Rådgivning	2	2
* Antal

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter() %>% 
  filter(
    species == unique(FIX020[[1]])[3],
    area %in% unique(FIX020_raw[[2]])[1:3]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Hvalros
Nordvandet
Fangst	21	48
Kvote	79	79
Rådgivning	84	84
Vestgrønland
Fangst	75	67
Kvote	74	74
Rådgivning	86	86
Østgrønland
Fangst	8	12
Kvote	17	17
Rådgivning	19	19
* Antal

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[7],
        area %in% unique(FIX020_raw[[2]])[c(1)]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Pukkelhval
Vestgrønland
Fangst	4	7
Kvote	10	10
Rådgivning	10	10
* Antal

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

Vis tabel

tab <- 
  FIX020_raw %>% 
  filter(
    species == unique(FIX020[[1]])[8],
    area %in% unique(FIX020_raw[[2]])[1:2]
    ) %>% 
  mutate(area = fct_reorder(area, value, .fun = sum, .desc = TRUE)) %>% 
  filter(time > year(Sys.time()) - 6) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>%  fct_inorder()) %>% 
  spread(time, value)

tab %>% 
  select(-c(species, area)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[["species"]] %>% table) %>% 
  pack_rows(index = tab[["area"]] %>% table()) %>% 
  add_footnote(sdg14$figs$fig0$units$antal[language] %>% unlist(), notation = "symbol")

	2020	2021
Vågehval
Vestgrønland
Fangst	138	177
Kvote	164	164
Rådgivning	164	164
Østgrønland
Fangst	20	21
Kvote	20	20
Rådgivning	20	20
* Antal

Bruttoværditilvækst for brancher under fiskeri

---

GS Bruttoværditilvækst for brancher under fiskeri

# 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

Vis tabel

table <- 
  NRX0418_raw %>% 
  mutate(industry = industry %>% str_remove_all("[:digit:]") %>% trimws() %>% fct_inorder()) %>% 
  mutate(time = time %>% as.numeric()) %>% 
  filter(!time %in% 2019:2020) %>% 
  filter(time >= max(time) - 7) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>% as.character() %>% fct_inorder()) %>% 
  mutate(value = round(value / 1000, 1)) %>% 
  spread(time, value)

table %>% 
  select(-units) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = table[1] %>% table()) %>% 
  add_footnote(sdg14$figs$fig9$y_lab[language], notation = "symbol")

	2016	2017	2018	2021	2022	2023
2010-priser, kædede værdier
Bruttoværditilvækst i alt	14,7	14,8	15,0	15,8	16,1	16,3
Kystnært fiskeri	0,3	0,3	0,4	NA	NA	NA
Udenskærs fiskeri	1,0	1,1	1,1	NA	NA	NA
Fiskeri i øvrigt	0,3	0,2	0,2	NA	NA	NA
* Milliarder kroner

NRX13_raw <- 
  statgl_url("NRX13", lang = language) %>% 
  statgl_fetch(
    Kode  = c("VBVT0301", "VBVT0302", "VBVT0303"),
    time      = 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

Vis tabel

NRX13_raw %>% 
  drop_na() %>% 
  mutate(industry = industry %>% str_remove_all("[:digit:]") %>% trimws() %>% fct_rev()) %>% 
  mutate(time = time %>% as.numeric()) %>% 
  filter(time >= max(time) -5) %>% 
  #arrange(desc(time)) %>% 
  mutate(time = time %>% as.character() %>% fct_inorder()) %>% 
  spread(time, value) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(sdg14$figs$fig11$y_lab[language], notation = "symbol")

	2015	2016	2017	2018	2019	2020
Udenskærs fiskeri	-1,59	1,43	1,05	-0,39	0,45	0,12
Kystnært fiskeri	-1,84	1,28	-0,02	0,55	0,26	-0,41
Fiskeri i øvrigt	0,04	0,43	-0,43	-0,11	0,22	-0,41
* Procentpoint