sdg2020

Anguniagaq 8: Suliffiit naapertuuttut aningaasarsiornikkullu siuariartorneq

BNP innuttaasumut ataatsimut

FN 8.1.1 Ukiumut innuttaasumut ataatsimut BNP-p ineriartornera

# Import
NRX10_raw <- 
  statgl_url("NRX10", lang = language) %>% 
  statgl_fetch(
    units     = "K",
    account   = "02",
    Aar       = px_all(),
    .col_code = TRUE
               ) %>% 
  as_tibble()

# transform 
NRX10 <- 
  NRX10_raw %>% 
  rename("time" = "Aar") %>% 
  mutate(time = time %>% as.numeric()) %>% 
  mutate(value = (value - lag(value)) / lag(value))


NRX10 %>% 
  ggplot(aes(
    x = time,
    y = value,
    fill = account
  )) +
  geom_col() +
  scale_fill_statgl() + 
  theme_statgl() +
  theme(legend.position = "none") +
  scale_y_continuous(labels = scales::percent_format(
    scale        = 100, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  labs(
    title    = sdg8$fig$fig1$title[language],
    subtitle = NRX10[[1]][1],
    x        = " ",
    y        = sdg8$fig$fig1$y_lab[language],
    fill     = " ",
    caption  = sdg8$fig$fig1$cap[language]
  )

Kisitsisaataasivik, BNP

Kisitsisaataasivik, suliffillit

tab <- 
  NRX10 %>% 
  mutate(value = value*100) %>% 
  filter(time >= max(time) - 5) %>% 
  arrange(desc(time)) %>% 
  select(-account) %>% 
  mutate(time = time %>% as.character())


if(language != "en"){
  
  table <- 
    tab %>% 
    select(-units) %>% 
    mutate(value = value %>% round(1)) %>% 
    rename(" " = 1, "Realvækst" = value) %>% 
    statgl_table() %>% 
    pack_rows(index = tab[[1]] %>% table()) %>% 
    add_footnote(sdg8$fig$fig1$foot1[language], notation = "symbol")
  
} else {
  
   table <- 
    tab %>% 
    select(-units) %>% 
    mutate(value = value %>% round(1)) %>% 
    rename(" " = 1, "Real growth rate" = value) %>% 
    statgl_table() %>% 
    pack_rows(index = tab[[1]] %>% table()) %>% 
    add_footnote(sdg8$fig$fig1$foot1[language], notation = "symbol")

}


table

	Realvækst
Akiusimasunit kisitat (2010-imi akit)
2021	0,7
2020	0,0
2019	2,6
2018	0,6
2017	0,0
2016	4,9
^* Ineriartorneq procentinngorlugu (2010-mi akit, akiusimasunit kisitat)

Suliffillit

GS Innuttaasunut tamanut naleqqiullugu suliffillit annertussusaat

# Import

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/AR/AR30/ARXBFB05.px")

ARXBFB05_raw <-
  url |> 
  statgl_fetch(
    time                 = px_all(),
    municipality         = px_all(),
    "inventory variable" = "H",
    .col_code            = T
  ) |> 
  as_tibble()


# Transform
ARXBFB05 <- 
  ARXBFB05_raw %>% 
  mutate(time = time %>% make_date(),
         municipality = municipality %>% factor(levels = unique(municipality)))

# Plot
ARXBFB05 %>% 
  filter(municipality == ARXBFB05[[1]][1]) %>% 
  ggplot(aes(
    x     = time,
    y     = value,
    color = municipality
    )) +
  geom_line(size = 2) +
  facet_wrap(~ municipality, scales = "free") +
    scale_y_continuous(labels = scales::percent_format(
      scale      = 1, 
      accuracy   = 0.1, 
      big.mark   = ".",
      decimal.mark = ","
      )) +
  theme_statgl() + 
  scale_color_statgl() +
  theme(legend.position = "none") +
  labs(
    title    = sdg8$fig$fig2$title[language],
    subtitle = ARXBFB05[[1]][1],
    x        = " ",
    y        = " ",
    caption  = sdg8$fig$fig2$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
ARXBFB05 <- 
  ARXBFB05_raw %>% 
  filter(
    municipality == ARXBFB05_raw[[1]][1],
    time         >= year(Sys.time()) - 7
    ) %>% 
  arrange(desc(time))

vec        <- 1:2
names(vec) <- c(" ", sdg8$fig$fig2$cols$col2[language])

# Table
ARXBFB05 %>% 
  select(2, ncol(.)) %>% 
  rename(vec) %>% 
  statgl_table() %>% 
  pack_rows(index = ARXBFB05[[3]] %>% table()) %>% 
  add_footnote(ARXBFB05[[1]][1], notation = "symbol")

	Suliffillit annertussusaat
Agguaqatigiissillugu qaammammut suliffillit innuttaasut amerlassusaannut naleqqiullugit (pct.)
2022	66,9
2021	66,7
2020	66,0
2019	66,6
2018	66,1
2017	65,3
^* Nuna tamakkerlugu (kommunit avataanni inissisimasut ilanngullugit)

Suliffissaaleqineq

FN 8.5.2 Ukiut malillugit suliffissaaleqinerup annertussusaa

# Import

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/AR/AR40/ARXLED3.px")

ARXLED3_raw <-
  url |> 
  statgl_fetch(
    time                 = px_all(),
    district             = "AA",
    age                  = "1",
    "inventory variable" = "P",
    .col_code            = TRUE
    ) %>% 
  as_tibble()

# Transform
ARXLED3 <-
  ARXLED3_raw %>% 
  mutate(time = time %>% make_date()) %>% 
  unite(combi, 1, 2, 4, sep = ", ")

# Plot
ARXLED3 %>% 
  ggplot(aes(
    x     = time,
    y     = value,
    color = combi
    )) +
  geom_line(size = 2) +
  theme_statgl() + 
  scale_color_statgl() +
  theme(legend.position = "none") +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 1, 
    accuracy     = 0.1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  labs(
    title    = sdg8$fig$fig3$title[language],
    subtitle = ARXLED3[[1]][1],
    x        = " ",
    y        = " ",
    color    = " ",
    caption  = sdg8$fig$fig3$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform

ARXLED3 %>% 
  mutate(time = time %>% year()) %>% 
  filter(time > year(Sys.time()) - 8) %>% 
  spread(time, value) %>% 
  mutate(combi = sdg8$fig$fig3$cols$ncol[language][[1]]) %>% 
  rename(" " = 1) %>% 
  statgl_table()

	2017	2018	2019	2020	2021	2022
Suliffissaaleqineq procentinngorlugu	5,9	5	4,3	4,5	3,7	3,2

# Import

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/AR/AR40/ARXLED3.px")

ARXLED4_raw <-
  url |> 
  statgl_fetch(
    time                 = px_all(),
    district             = "AA",
    "inventory variable" = "P",
    age                  = px_all(),
    .col_code            = T
    ) %>% 
  as_tibble()

# Transform
ARXLED4 <- 
  ARXLED4_raw %>% 
  filter(age != ARXLED4_raw[[2]][1]) %>% 
  arrange(desc(time)) %>% 
  mutate(age = age %>% factor(levels = unique(age)),
         time = time %>% make_date()) %>% 
  unite(combi, 1, 4, sep = ", ")

# Plot
ARXLED4 %>% 
  ggplot(aes(
    x     = time, 
    y     = value,
    color = age
    )) +
  geom_line(size = 1.5) +
  theme_statgl() + 
  scale_color_statgl() +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 1, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  labs(
    title    = sdg8$fig$fig4$title[language],
    subtitle = ARXLED4[[1]][1],
    x        = " ",
    y        = " ",
    color    = " ",
    caption  = sdg8$fig$fig4$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
ARXLED4 <- 
  ARXLED4_raw %>% 
  filter(
    age != ARXLED4_raw[[2]][1],
    time >= year(Sys.time()) - 6
    ) %>% 
  arrange(desc(time)) %>% 
  mutate(
    age = age %>% factor(levels = unique(age)),
    time = time %>% factor(levels = unique(time))
    ) %>% 
  unite(combi, 1, 2, sep = ", ") %>% 
  spread(3, ncol(.))

vec        <- ARXLED4[[2]] %>% length()
names(vec) <- sdg8$fig$fig4$index[language]


# Table
ARXLED4 %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = vec) %>% 
  pack_rows(index = table(ARXLED4$combi)) |> 
  add_footnote(ARXLED4_raw[[1]][1], notation = "symbol")

	Agguaqatigiissillugu qaammammut suliffissaaleqineq pct.-inngorlugu
Suliffissaaleqineq procentinngorlugu
Nuna tamakkerlugu, 18-19-inik ukiullit
2022	5,0
2021	6,8
2020	8,5
2019	7,6
2018	12,2
Nuna tamakkerlugu, 20-24-nik ukiullit
2022	4,2
2021	4,8
2020	6,1
2019	6,2
2018	7,8
Nuna tamakkerlugu, 25-29-nik ukiullit
2022	3,1
2021	3,2
2020	4,5
2019	4,7
2018	5,3
Nuna tamakkerlugu, 30-34-nik ukiullit
2022	3,2
2021	3,3
2020	4,4
2019	4,0
2018	4,6
Nuna tamakkerlugu, 35-39-nik ukiullit
2022	2,8
2021	3,2
2020	4,2
2019	4,0
2018	4,6
Nuna tamakkerlugu, 40-44-nik ukiullit
2022	2,7
2021	3,4
2020	3,9
2019	3,7
2018	4,0
Nuna tamakkerlugu, 45-49-nik ukiullit
2022	2,4
2021	2,9
2020	3,9
2019	4,0
2018	4,3
Nuna tamakkerlugu, 50-54-inik ukiullit
2022	3,4
2021	4,0
2020	4,4
2019	3,9
2018	4,3
Nuna tamakkerlugu, 55-59-inik ukiullit
2022	3,2
2021	3,9
2020	4,3
2019	3,7
2018	4,3
Nuna tamakkerlugu, 60-inik ukiullit-soraarneruss. ukiussarititat
2022	3,5
2021	3,6
2020	4,2
2019	4,2
2018	4,6
^* Nuna tamakkerlugu

GS Najugaq malillugu suliffissaaleqineq procentinngorlugu

# Import

url <- paste0("https://bank.stat.gl/api/v1/", language, "/Greenland/AR/AR40/ARXLED3.px")

ARXLED3_raw <-
  url |> 
  statgl_fetch(
    time                 = px_all(),
    district             = "AA",
    age                  = "1",
    "inventory variable" = "P",
    "place of residence" = px_all(),
    .col_code            = TRUE
    ) %>% 
  as_tibble()

# Transform
ARXLED3 <- 
  ARXLED3_raw %>% 
  mutate(time = time %>% make_date())

# Plot
ARXLED3 %>% 
  ggplot(aes(
    x     = time,
    y     = value, 
    color = `place of residence`
    )) +
  geom_line(size = 2) +
  theme_statgl() + 
  scale_color_statgl() +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 1, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  labs(
    title    = sdg8$fig$fig5$title[language],
    subtitle = ARXLED4[[2]][1],
    x        = " ",
    y        = " ",
    color    = " ",
    caption  = sdg8$fig$fig5$cap[language]
    )

Kisitsisaataasivik

Periaaseq

# Transform
ARXLED3 <- 
  ARXLED3_raw %>% 
  filter(time >= year(Sys.time()) - 6) %>% 
  arrange(time) %>% 
  mutate(time = time %>% factor(levels = unique(time))) %>% 
  unite(combi, district, age, sep = ", ") %>% 
  spread(1, ncol(.))

vec        <- ARXLED3[[1]] %>% length()
names(vec) <- sdg8$fig$fig5$index[language]

# Table
ARXLED3 %>% 
  select(-c(1, 3)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(ARXLED3[[1]][1], notation = "symbol") %>% 
  row_spec(1, bold = TRUE) %>% 
  pack_rows(index = vec) |> 
  pack_rows(index = table(ARXLED3$`place of residence`))

	Nuna tamakkerlugu, Katillugit
Suliffissaaleqineq procentinngorlugu
Illoqarfiit
2018	4,8
2019	4,1
2020	4,3
2021	3,4
2022	3,0
Katillugit
2018	5,0
2019	4,3
2020	4,5
2021	3,7
2022	3,2
Nunaqarfiit il.il.
2018	6,9
2019	6,1
2020	6,5
2021	5,3
2022	4,9
^* Illoqarfiit

Ilisimatusarneq ineriartortitsinerlu

GS Ilisimatusarnermut ineriartortitsinermullu aningaasartuutit BNP-mi annertussusaat

# Import
NRX09_raw <-
  statgl_url("NRX09", lang = language) %>%
  statgl_fetch(
    "units"   = "L",
    "account" = px_all(),
    "time"    = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

NRX09_raw <- NRX09_raw %>% filter(account %in% unique(NRX09_raw %>% pull(account))[7])

NRX10_raw <-
  statgl_url("NRX10", lang = language) %>% 
  statgl_fetch(
    "units"    = "L",
    "account"  = "01",
    "Aar"      = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
RD_GDP <- 
  NRX10_raw %>% 
  select(3:4) %>% 
  rename(
    "time" = 1,
    "GDP"  = 2
    ) %>% 
  left_join(
    NRX09_raw %>% 
      mutate(account = account %>% str_remove_all("[:digit:]") %>% trimws()) %>% 
      select(3:4) %>% 
      rename("RD" = 2)
    ) %>% 
  mutate(pct = RD / GDP) %>% 
  filter(pct != "NA")

# Plot
RD_GDP %>% 
  ggplot(aes(
    x    = time,
    y    = pct,
    fill = time
    )) +
  geom_col() +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 100, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl() + 
  scale_fill_statgl() +
  theme(legend.position = "none") +
  labs(
    title    = sdg8$fig$fig6$title[language],
    subtitle = NRX09_raw[[1]][1],
    x        = " ",
    y        = sdg8$fig$fig6$y_lab[language],
    caption  = sdg8$fig$fig6$cap[language]
  )

Kisitsisaataasivik, aningaasaliinerit (ilisimatusarneq ineriartortitsinerlu)

Kisitsisaataasivik, BNP

# Transform
tab <- 
  RD_GDP %>% 
  #arrange(desc(time)) %>% 
  filter(time >= year(Sys.time()) - 7) %>% 
  mutate(
    time = time %>% fct_inorder(),
    pct  = pct * 100,
    pct  = pct %>% round(1),
    var  = sdg8$fig$fig6$cols$col1[language]
    ) %>% 
  select(-(2:3)) %>% 
  spread(1, 2)

# Table
tab %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = table(NRX09_raw[[1]][1])) %>% 
  add_footnote(sdg8$fig$fig6$foot[language], notation = "symbol")

	2017	2018	2019	2020	2021
Akit ingerlaavartut, mio. kr.
Ilisimatusarnermut ineriartortitsinermullu aningaasartuutit	2,1	1,8	1,8	1,6	1,6
^* BNP-mi procentinngorlugu

Nunanut allanut angalasut

GS Timmisartumik ilaasartaammik nunanut allanut angalasut amerlassusaat

# Import
TUXUPAX_raw <-
  statgl_url("TUXUPAX", lang = language) %>%
  statgl_fetch(airport   = 0,
               month     = 0,
               time      = px_all(),
               .col_code = TRUE) %>% 
  as_tibble()

# Transform
TUXUPAX <-
  TUXUPAX_raw %>% 
  mutate(value = value / 1000,
         time = time %>% make_date())

# Plot
TUXUPAX %>% 
  ggplot(aes(
    x    = time,
    y    = value, 
    fill = airport
    )) +
  geom_col() +
  theme_statgl() + 
  scale_fill_statgl() +
  theme(plot.margin = margin(10, 10, 10, 10),
        legend.position = "none") +
  labs(
    title = sdg8$fig$fig7$title[language],
    x = " ",
    y = sdg8$fig$fig7$y_lab[language],
    caption = sdg8$fig$fig7$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
TUXUPAX <-
  TUXUPAX_raw %>% 
  mutate(value = value) %>% 
  filter(time >= year(Sys.time()) - 7,
         value != "NA") %>% 
  arrange(desc(time))

vec <- 1:2
names(vec) <- c(" ",  sdg8$fig$fig7$cols$col2[language])


# Table
TUXUPAX %>% 
  select(-(1:2)) %>% 
  rename(vec) %>% 
  statgl_table() %>% 
  add_footnote(sdg8$fig$fig7$foot[language],
               notation = "symbol")

	Timmisartumik ilaasartaammik nunanut allanut angalasut
2023	96.362
2022	85.484
2021	39.293
2020	30.785
2019	86.989
2018	85.306
2017	83.487
^* Ilaasut tuusintilikkuutaarlugit.

Inuusuttut sullinniakkat

GS Inuusuttut sullinniakkat

UDXUMG3_raw <- 
  statgl_url("UDXUMG3", lang = language) %>%
  statgl_fetch(
    alder        = px_all(),
    registrering = 5:7,
    aar          = px_all(),
    .col_code    = TRUE
  ) %>% 
  as_tibble()

#sdg8 <- read_yaml("S:/STATGS/VM/SDG_dokument/input/text/txt_08.yml")

lab_vec        <- 1:5
names(lab_vec) <- 
  c(
    "age",
    "time",
    sdg8$fig$fig8$tags$tag1[language] %>% unlist(),
    sdg8$fig$fig8$tags$tag2[language] %>% unlist(),
    sdg8$fig$fig8$tags$tag3[language] %>% unlist()
)


UDXUMG3 <-
  UDXUMG3_raw %>% 
  rename("status" = registrering, "age" = alder, "time" = aar) |> 
  mutate(status = status %>% fct_inorder()) %>% 
  spread(status, value) %>% 
  rename(
    "age"   = 1,
    "time"  = 2,
    "work"  = 3,
    "none"  = 4,
    "total" = 5
  ) %>% 
  mutate(edu = total - work - none) %>% 
  select(-total) %>% 
  rename(lab_vec) %>% 
  gather(status, value, -c(age, time)) %>% 
  mutate(time = time %>% as.numeric()) %>% 
  filter(time %in% c(min(time), mean(time), max(time))) %>%
  mutate(time = time %>% as.character() %>% fct_rev())
  

UDXUMG3 %>%
  ggplot(aes(
    x    = parse_number(age),
    y    = value,
    fill = status
  )) +
  geom_col(position = "fill") +
  facet_wrap(~ time) + 
  scale_x_continuous(labels = function(x) round(x)) +
  scale_y_continuous(labels = scales:: percent) + 
  scale_fill_statgl(reverse = TRUE) +
  theme_statgl() + 
  labs(
    title    = sdg8$fig$fig8$title[language],
    subtitle = sdg8$fig$fig8$sub[language],
    x        = sdg8$fig$fig8$x_lab[language],
    y        = " ",
    color    = colnames(UDXUMG3_raw)[2] %>% str_to_title(),
    caption  = sdg8$fig$fig8$cap[language]
)

Kisitsisaataasivik

Periaaseq

tab <- 
  UDXUMG3 %>% 
  mutate(age = age %>% fct_inorder()) %>% 
  arrange(age, time, status) %>% 
  unite(combi, time, status, sep = ",") %>% 
  mutate(combi = combi %>% fct_inorder()) %>% 
  spread(combi, value)

vec      <- tab %>% select(-1) %>% colnames() %>% str_split(",") %>% unlist()
head_vec <- vec[c(TRUE, FALSE)] %>% table() %>% rev()
col_vec  <- vec[c(FALSE, TRUE)]

tab %>% 
  statgl_table(col.names = c(" ", col_vec)) %>% 
  add_header_above(c(" ", head_vec)) %>% 
  add_footnote(sdg8$fig$fig8$foot[language], notation = "symbol")

	2022			2019			2016
age	2022,Ilinniakkamik ingerlatsisut	2022,Suliffeqanngitsut ilinnianngitsullu	2022,Suliffillit	2019,Ilinniakkamik ingerlatsisut	2019,Suliffeqanngitsut ilinnianngitsullu	2019,Suliffillit	2016,Ilinniakkamik ingerlatsisut	2016,Suliffeqanngitsut ilinnianngitsullu	2016,Suliffillit
16-inik ukiullit	347	292	68	314	317	84	390	295	70
17-inik ukiullit	299	325	136	290	358	141	275	362	127
18-inik ukiullit	303	260	174	278	271	220	298	325	176
19-inik ukiullit	238	218	266	230	205	288	274	318	300
20-nik ukiullit	167	221	388	150	221	372	171	264	374
21-nik ukiullit	176	215	360	159	225	397	205	242	389
22-nik ukiullit	149	177	363	174	236	462	219	233	411
23-nik ukiullit	161	198	390	169	189	452	223	221	472
24-nik ukiullit	187	199	404	195	181	482	227	197	476
25-nik ukiullit	158	199	519	194	173	496	230	186	487
^* Inuit amerlassusaat