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---

Goal 14: Life below water

Consumption of marine resources

---

GS Consumption of marine resources

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]
  )

StatBank

Show table

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")

	2021	2022
Prawns
Eastgreenland
Advice	3.000	3.000
Catch	3.071	5.510
Kvota	7.000	6.850
Westgreenland
Advice	113.777	113.777
Catch	108.352	112.659
Kvota	113.777	113.777
* 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]
  )

StatBank

Show table

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")

	2021	2022
Grenland halibut
Eastgreenland
Advice	8.847	10.020
Catch	8.255	8.933
Kvota	8.847	10.020
Westgreenland
Advice	18.184	18.185
Catch	17.989	18.112
Kvota	18.184	18.185
* 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]
  )

StatBank

Show table

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")

	2021	2022
Atlantic cod
West- Eastgreenland
Advice	6.091	8.708
Catch	16.146	21.487
Kvota	26.091	21.630
Westgreenland
Advice	NA	NA
Catch	NA	NA
Kvota	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]
  )

StatBank

Show table

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")

	2021
Peluga
Westgreenland
Advice	265
Catch	139
Kvota	265
Qaanaaq
Advice	37
Catch	9
Kvota	29
Eastgreenland
Advice	0
Catch	0
Kvota	0
Melville Bay
Advice	0
Catch	0
Kvota	0
* Quantity

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]
  )

StatBank

Show table

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")

	2021
Narwhale
Westgreenland
Advice	251
Catch	235
Kvota	251
Eastgreenland
Advice	0
Catch	20
Kvota	60
* Quantity

Consumption of marine resources -2

GS Consumption of marine resources -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]
  )

StatBank

Show table

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")

	2021
Minke whale
Westgreenland
Advice	164
Catch	177
Kvota	164
Qaanaaq
Advice	0
Catch	0
Kvota	0
* Quantity

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]
  )

StatBank

Show table

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")

	2021
Bowhead whale
Westgreenland
Advice	2
Catch	0
Kvota	2
* Quantity

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]
  )

StatBank

Show table

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")

	2021
Fin whale
Westgreenland
Advice	19
Catch	2
Kvota	19
* Quantity

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]
  )

StatBank

Show table

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")

	2021
Humpback whale
Westgreenland
Advice	10
Catch	7
Kvota	10
Eastgreenland
Advice	0
Catch	0
Kvota	0
Northern water
Advice	0
Catch	0
Kvota	0
* Quantity

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]
  )

StatBank

Show table

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")

	2021
Polar bear
Westgreenland
Advice	92
Catch	86
Kvota	92
* Quantity

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]
  )

StatBank

Show table

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")

	2021
Walrus
Westgreenland
Advice	86
Catch	67
Kvota	74
Eastgreenland
Advice	19
Catch	12
Kvota	17
* Quantity

Gross value added for fishing industries

---

GS Gross value added for fishing industries

# 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]
  )

StatBank

Show table

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-prices, chained values
Gross value added total	14,7	14,8	15,0	15,8	16,1	16,3
Inshore fishing	0,3	0,3	0,4	NA	NA	NA
Offshore fisheries	1,0	1,1	1,1	NA	NA	NA
Fishing, other	0,3	0,2	0,2	NA	NA	NA
* Billions (DKK)

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]
  )

StatBank

Show table

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
Offshore fisheries	-1,59	1,43	1,05	-0,39	0,45	0,12
Inshore fishing	-1,84	1,28	-0,02	0,55	0,26	-0,41
Fishing, other	0,04	0,43	-0,43	-0,11	0,22	-0,41
* Percentage point