Utertiguk

---

Anguniagaq 9: Suliffissuit, nutaaliorneq attaveqaasersuutillu

Ilisimatuut

---

FN 9.5.2 Ph.D-mik ilisimatuutullu ilinniarsimasut amerlassusaat

# Import
UDXISCPROD_raw <-
  statgl_url("UDXISCPROD", lang = language) %>% 
  statgl_fetch(
    ISCED11_level = 80,
    Sex           = px_all(),
    Aar           = px_all(),
    .col_code     = TRUE
    ) %>% 
  as_tibble()
 
# Transform
UDXISCPROD <- 
  UDXISCPROD_raw %>% 
  mutate(
    Aar = Aar %>% make_date(),
    Sex = Sex %>% fct_inorder()
    )

# Plot
UDXISCPROD %>% 
  ggplot(aes(
    x    = Aar,
    y    = value,
    fill = Sex
  )) +
  geom_col() +
  #facet_wrap(~ gender) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE) +
  theme(plot.margin = margin(10, 10, 10, 10)) +
  labs(
    title   = sdg9$figs$fig1$title[language],
    x       = " ",
    y       = sdg9$figs$fig1$y_lab[language],
    fill    = " ",
    caption = sdg9$figs$fig1$cap[language]
  )

Kisitsisaataasivik

Periaaseq

Tabel nuisiguk

# Transform
UDXISCPROD <- 
  UDXISCPROD_raw %>% 
  filter(Aar >= year(Sys.time()) - 5) %>% 
  #arrange(desc(time)) %>% 
  mutate(Aar = Aar %>% factor(levels = unique(Aar))) %>% 
  spread(3, 4)

# Table
UDXISCPROD %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = UDXISCPROD[[1]] %>% table())

	2020	2021	2022	2023	2024
Ilisimatuunngorniarneq
Angutit	27	30	27	26	23
Arnat	27	32	35	39	37

Inuussutissarsiutit aaqqissuussaanerat

---

GS Akissarsialiornerit annertussusaat malillugit suliffeqarfiit amerlassusaat

# Import
ESD6A_raw <-
  statgl_url("ESX6A", lang = language) %>% 
  statgl_fetch(
    aar         = px_all(),
    ai2         = px_all(),
    section     = "total",
    .col_code   = TRUE
  ) %>% 
    as_tibble() |> 
  filter(ai2 != "Total")

# transform
ESD6A <- 
  ESD6A_raw %>%
  mutate(
    ai2 = ai2 %>% str_remove_all("[A-K]|\\.") %>% trimws() %>% fct_inorder() %>% fct_rev(),
    aar = aar %>% make_date()
  )


# legend ...
fill_lab <- colnames(statgl_url("ESX6A", lang = language) %>% statgl_fetch() %>% as_tibble())[1] %>% str_to_sentence()

# Plot
ESD6A %>% 
  ggplot(aes(
    x    = aar,
    y    = value,
    fill = ai2
  )) +
  geom_area() +
  theme_statgl() +
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = TRUE)) +
  labs(
    title    = sdg9$figs$fig2$title[language],
    subtitle = sdg9$figs$fig2$sub[language],
    x        = " ",
    y        = ESD6A[["unit"]][1],
    fill     = fill_lab,
    caption  = sdg9$figs$fig2$cap[language]
  )

Kisitsisaataasivik

Periaaseq

Tabel nuisiguk

# col lab
col_lab        <- 1
names(col_lab) <- fill_lab


# transform
ESD6A <- 
  ESD6A_raw %>%
  mutate(
    ai2 = ai2 %>% 
      str_remove_all("[A-K]|\\.") %>% 
      trimws() %>% 
      fct_inorder() %>% 
      fct_rev(),
    ) %>% 
  filter(aar >= Sys.time() %>% year() - 5) %>% 
  mutate(aar = aar %>% fct_inorder() %>% fct_rev()) %>% 
  spread(aar, value) %>% 
  arrange(desc(ai2)) %>% 
  rename(col_lab)

# table
ESD6A %>%  
  statgl_table() %>% 
  add_footnote(ESD6A[["unit"]][1], notation = "symbol")

Akissarsialiussaqassuseq	section	2022	2021	2020
00-10	Katillugit	359	354	310
10-50	Katillugit	585	680	510
50-100	Katillugit	473	557	461
100-250	Katillugit	785	818	751
250-500	Katillugit	590	613	641
500-1000	Katillugit	407	372	368
1000-5000	Katillugit	517	477	479
5000-10000	Katillugit	88	81	84
10000-it sinnerlugit	Katillugit	110	111	100
atillugit	Katillugit	3.914	4.063	3.704

# Import
ESX5A_raw <-
  statgl_url("ESX5A", lang = language) %>% 
  statgl_fetch(
    nykom      = 1:5,
    ai2        = px_all(),
    aar        = px_all(),
    .col_code  = TRUE
    ) %>% 
  as_tibble() |> 
  filter(ai2 != "Total")

ESX5A <- 
  ESX5A_raw %>% 
  rename(lonsum = ai2) %>% 
  mutate(
    aar    = aar %>% make_date(),
    lonsum = lonsum %>% str_remove_all("[A-K]|\\.") %>% trimws() %>% fct_inorder() %>% fct_rev()
  )


# Plot
ESX5A %>% 
  ggplot(aes(
    x    = aar,
    y    = value,
    fill = lonsum
  )) +
  geom_area() +
  facet_wrap(~ nykom, scales = "free") +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = TRUE)) +
  labs(
    title    = sdg9$figs$fig3$title[language],
    subtitle = sdg9$figs$fig3$sub[language],
    x        = " ",
    y        = ESX5A[[3]][1],
    fill     = fill_lab,
    caption  = sdg9$figs$fig3$cap[language]
  )

Kisitsisaataasivik

Periaaseq

Tabel nuisiguk

ESX5A <- 
  ESX5A_raw %>% 
  rename(lonsum = ai2) %>% 
  filter(aar >= Sys.time() %>% year() - 5) %>% 
  mutate(
    aar    = aar %>% fct_inorder() %>% fct_rev(),
    nykom  = nykom %>% fct_inorder(),
    lonsum = lonsum %>% str_remove_all("[A-K]|\\.") %>% trimws() %>% fct_inorder() %>% fct_rev()
    ) %>% 
  spread(aar, value) %>% 
  arrange(nykom, desc(lonsum))

ESX5A %>% 
  select(nykom) %>% 
  rename(col_lab) %>% 
  statgl_table() %>% 
  pack_rows(index = ESX5A[["nykom"]] %>% table())

Akissarsialiussaqassuseq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Kommuneqarfik Sermersooq
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Qeqqata Kommunia
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Kujalleq
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Kommune Qeqertalik
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia
Avannaata Kommunia

Aalisakkat saniatigut nunanut allanut tunisat allat

---

GS Nunanut allanut tunisinermi aalisarnermut tunngasut annertussusaat

# Import
IEXSITC_raw <-
  statgl_url("IEXSITC", lang = language) %>% 
  statgl_fetch(quarter     = 0,
               processing  = c("G11", "3"),
               transaction = 2,
               time        = px_all(),
               .col_code   = TRUE
               ) %>% 
    as_tibble()

# Transform
step <-
  IEXSITC_raw %>% 
  mutate(processing = processing %>% str_remove_all("[:digit:]|\\-") %>% trimws(which = "left")) %>% 
  arrange(time, processing)

IEXSITC <- 
  step %>% 
  mutate(export = fct_reorder(processing, -value, sum, na.rm = TRUE),
         time = make_date(time),
         value = value / 10^9) 
# Plot
IEXSITC %>% 
  ggplot(aes(
    x = time,
    y = value, 
    fill = export
  )) +
  geom_area(position = "identity") +
  theme_statgl() +
  scale_fill_statgl(reverse = TRUE) +
  labs(
    title = sdg9$figs$fig4$title[language],
    y     = sdg9$figs$fig4$y_lab[language],
    x     = " ",
    fill  = " ",
    caption = sdg9$figs$fig4$cap[language]
  )

Kisitsisaataasivik

Periaaseq

Tabel nuisiguk

# Transform
IEXSITC <- 
  step %>% 
  mutate(
    export = fct_reorder(processing, -value, sum, na.rm = TRUE),
    value = value / 10^9
    ) 

tab <- 
  IEXSITC %>% 
  select(-2, -3) %>% 
  #arrange(desc(time)) %>% 
  filter(time >= year(Sys.time()) - 5) %>% 
  mutate(time = time %>% factor(levels = unique(time))) %>% 
  spread(time, value)

# Table
tab %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = tab[[1]] %>% table()) %>% 
  row_spec(1, bold = TRUE) %>% 
  add_footnote(sdg9$figs$fig4$foot[language], notation = "symbol")

	2020	2021	2022	2023	2024	2025
Ukioq tamaat
Katillugit	5,30	5,06	5,88	6,21	5,21	NA
Aalisagaq, peqquk qaleruaqanngitsullu	4,85	4,78	5,64	5,86	5,08	NA
* Koruunit milliardinngorlugit

# Import
IEXSITC_raw <-
  statgl_url("IEXSITC", lang = language) %>%
  statgl_fetch(processing  = px_all(),
               transaction = 2,
               time        = px_all(),
               .col_code   = TRUE
               ) %>% 
    as_tibble()

# Transform
IEXSITC <- 
  IEXSITC_raw %>% 
  filter(processing %in% unique(IEXSITC_raw[[1]])[c(16, 26, 45, 55, 65, 74)]) %>% 
  mutate(
    time       = time %>% make_date(),
    value      = value / 10^6,
    processing = processing %>% str_remove_all("[:digit:]|\\-") %>% trimws()
    )

# Plot
IEXSITC %>% 
  ggplot(aes(
    x = time, 
    y = value,
    fill = processing
    )) +
  geom_area() + 
  facet_wrap(~ processing, labeller = label_wrap_gen(30)) +
  scale_fill_statgl() +
  theme_statgl() +
  theme(plot.margin = margin(10, 10, 10, 10)) +
  theme(legend.position = "none") +
  labs(
    title = sdg9$figs$fig5$title[language],
    x = " ", 
    y = sdg9$figs$fig5$y_lab[language],
    fill = " ",
    caption = sdg9$figs$fig4$cap[language]
 )

Kisitsisaataasivik

Periaaseq

Tabel nuisiguk

# Transform
IEXSITC <- 
  IEXSITC_raw %>% 
  filter(processing %in% unique(IEXSITC_raw[[1]])[c(16, 26, 45, 55, 65, 74)],
         time >= year(Sys.time()) -7,
         value != "NA") %>% 
  #arrange(desc(time)) %>% 
  mutate(
    value      = round(value / 10^6, 3),
    processing = processing %>% str_remove_all("[:digit:]|\\-") %>% trimws(),
    time       = time %>% factor(levels = unique(time))
    ) %>% 
  spread(3,4)

# Table
IEXSITC %>% 
  select(-2) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = IEXSITC[[2]] %>% str_to_title() %>% table()) %>% 
  add_footnote(sdg9$figs$fig5$foot[language], notation = "symbol")

	2018	2019	2020	2021	2022	2023	2024
Avammut Tunisat
Atortussiassat nerineqarsinnaanngitsut (ikummatissaq minillugu), katillugit	4,605	7,882	6,824	7,135	11,907	11,294	13,291
Ikummatissat punnerusaallu katillugit	0,002	0,004	0,079	0,002	0,004	0,017	0,141
Maskiinat assartuutillu, katillugit	530,455	315,276	326,187	182,999	179,201	260,847	76,197
Nioqqutissat aningaasanillu nuussinerit assigiinngitsut katillugit	124,994	108,924	91,546	74,050	9,617	19,494	4,548
Nioqqutissiat suliareriikkat allani ilaanngitsut katillugit	11,818	11,720	5,117	4,683	16,185	26,685	24,564
Nioqqutissiat suliareriikkat suliareqqitassallu	13,285	5,699	13,193	8,149	16,420	20,536	11,039
* Koruunit millioninngorlugit

Suliffissuaqarnermi naleqarnerulersitsineq

---

FN 9.2.1 Suliffissuaqarnermi naleqarnerulersitsineq

# Import
BVT <-
  statgl_url("NRX0418", lang = language) %>% 
  statgl_fetch(units    = "L",
               industry = px_all(),
               time     = px_all(),
               .col_code  = TRUE
               ) %>% 
    as_tibble() %>% 
  mutate(value = value/1000)


BVT <- BVT %>%  filter(industry %in% unique(BVT %>% pull(2))[9])


BNP <-
  statgl_url("NRX10", lang = language) %>% 
  statgl_fetch(
    units   = "L",
    account = "02",
    time    = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
industry <- 
  BVT %>% 
  rename("BVT" = 4) %>% 
  left_join(BNP %>% rename("BNP" = 4)) %>% 
  mutate(value = BVT / BNP,
         time = time %>% as.numeric())

# Plot
industry %>% 
  ggplot(aes(
    x     = time,
    y     = value,
    color = units
  )) +
  geom_line(size = 2) +
  scale_y_continuous(labels = scales:: percent) +
  theme_statgl() + 
  scale_color_statgl() +
  theme(legend.position = "none") +
  labs(
    title    = sdg9$figs$fig6$title[language],
    subtitle = industry[[1]][1],
    x        = " ",
    y        = sdg9$figs$fig6$y_lab[language],
    caption  = sdg9$figs$fig6$cap[language]
  )

Kisitsisaataasivik, naleqarnerulersitsineq

Kisitsisaataasivik, BNP innuttaasunut agguarlugu

Tabel nuisiguk

tab <- 
  industry %>% 
  select(industry, time, value) %>% 
  mutate(
    industry = industry %>% str_remove_all("C "),
    value    = value * 100
    ) %>% 
  #arrange(desc(time)) %>% 
  filter(time >= max(time) - 5) %>% 
  mutate(time = time %>% as.character() %>%  fct_inorder()) %>% 
  mutate(value = value %>% round(2)) %>% 
  mutate(value = paste0(value, "%")) %>% 
  spread(time, value)

tab %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(sdg9$figs$fig6$foot[language], notation = "symbol")

	2018	2019	2020	2021	2022	2023
Tunisassiorneq	0.29%	0.19%	0.16%	0.11%	0.23%	0.15%
* BNP-p innuttaasumut ataatsimut annertussusaa procentinngorlugu.

Suliffissuaqarnermi sulifillit

---

FN 9.2.2 Suliffissuaqarnermi sulifillit

# Import
NRX0518_raw <-
  statgl_url("NRX0518", lang = language) %>% 
  statgl_fetch(
    units    = "BES",
    industry = c("C", "TOT"),
    time     = px_all(),
    .col_code  = TRUE
    ) %>% 
    as_tibble()


NRX0518 <- 
  NRX0518_raw %>% 
  spread(industry, value) %>% 
  rename("indu" = 3, "total" = 4) %>% 
  mutate(
    value = indu / total,
    time = time %>% as.numeric()
    )



NRX0518 %>% 
  ggplot(aes(
    x = time,
    y = value,
    color = units
  )) +
  geom_line(size = 2) +
  expand_limits(y = 0) +
  scale_y_continuous(labels  = scales::percent_format(scale = 100, accuracy = 1, big.mark = ".",
  decimal.mark = ",")) +
  theme_statgl() + 
  scale_color_statgl() +
  theme(legend.position = "none") +
  labs(
    title = sdg9$figs$fig7$title[language],
    x = " ",
    y = sdg9$figs$fig7$y_lab[language],
    caption = sdg9$figs$fig7$cap[language]
  )

Kisitsisaataasivik

Tabel nuisiguk

NRX0518 %>% 
  select(time, value) %>% 
  #arrange(desc(time)) %>% 
  filter(time >= max(time) - 5) %>% 
  mutate(time = time %>% as.character() %>%  fct_inorder()) %>% 
  mutate(
    value = value * 100,
    value = value %>% round(1)
    ) %>% 
  spread(time, value) %>% 
  statgl_table() %>% 
  add_footnote(sdg9$figs$fig7$foot[language], notation = "symbol")

2018	2019	2020	2021	2022	2023
5,8	5,4	5,6	5,4	5,4	5,4
* Sulisut tamakkerlutik annertussusaat procentinngorlugu