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())

	2021	2022	2023	2024
Ilisimatuunngorniarneq
Angutit	30	27	26	23
Arnat	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
00-10	Katillugit	359	354
10-50	Katillugit	585	680
50-100	Katillugit	473	557
100-250	Katillugit	785	818
250-500	Katillugit	590	613
500-1000	Katillugit	407	372
1000-5000	Katillugit	517	477
5000-10000	Katillugit	88	81
10000-it sinnerlugit	Katillugit	110	111
atillugit	Katillugit	3.914	4.063

# 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")

	2021	2022	2023	2024	2025
Ukioq tamaat
Katillugit	5,11	5,88	6,50	5,52	NA
Aalisagaq, peqquk qaleruaqanngitsullu	4,78	5,64	5,86	4,95	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")

	2019	2020	2021	2022	2023	2024
Avammut Tunisat
Atortussiassat nerineqarsinnaanngitsut (ikummatissaq minillugu), katillugit	7,882	6,824	7,135	11,907	11,294	13,291
Ikummatissat punnerusaallu katillugit	0,004	0,079	0,002	0,004	0,017	0,141
Maskiinat assartuutillu, katillugit	315,276	326,187	232,384	179,201	556,847	516,213
Nioqqutissat aningaasanillu nuussinerit assigiinngitsut katillugit	108,924	91,546	74,050	9,617	19,494	4,548
Nioqqutissiat suliareriikkat allani ilaanngitsut katillugit	11,720	5,117	4,683	16,185	26,685	24,564
Nioqqutissiat suliareriikkat suliareqqitassallu	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