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
Ilisimatuunngorniarneq
Angutit	27	30	27	26
Arnat	27	32	35	38

Inuussutissarsiutit aaqqissuussaanerat

---

GS Akissarsialiornerit annertussusaat malillugit suliffeqarfiit amerlassusaat

# Import
ESD6A_raw <-
  statgl_url("ESX6A", lang = language) %>%
  statgl_fetch(
    unit                                        = "N",
    time                                        = px_all(),
    "interval of aggregate salaries and shares" = c(LETTERS[1:8], "K"),
    .col_code                                   = TRUE
  ) %>% 
    as_tibble()

# transform
ESD6A <- 
  ESD6A_raw %>%
  mutate(
    `interval of aggregate salaries and shares` = `interval of aggregate salaries and shares` %>% str_remove_all("[A-K]|\\.") %>% trimws() %>% fct_inorder() %>% fct_rev(),
    time = time %>% make_date()
  )


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

# Plot
ESD6A %>% 
  ggplot(aes(
    x    = time,
    y    = value,
    fill = `interval of aggregate salaries and shares`
  )) +
  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(
    `interval of aggregate salaries and shares` = `interval of aggregate salaries and shares` %>% 
      str_remove_all("[A-K]|\\.") %>% 
      trimws() %>% 
      fct_inorder() %>% 
      fct_rev(),
    ) %>% 
  filter(time >= Sys.time() %>% year() - 5) %>% 
  mutate(time = time %>% fct_inorder() %>% fct_rev()) %>% 
  spread(time, value) %>% 
  arrange(desc(`interval of aggregate salaries and shares`)) %>% 
  rename(col_lab)

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

Akissarsialiussaqassuseq	2021	2020
00-10	708	620
10-50	1.360	1.020
50-100	1.114	922
100-250	1.636	1.502
250-500	1.226	1.282
500-1000	744	736
1000-5000	954	958
5000-10000	162	168
10000-it sinnerlugit	222	200
* Suliffeqarfiit amerlassusaat

# Import
ESX5A_raw <-
  statgl_url("ESX5A", lang = language) %>%
  statgl_fetch(
    municipality                                = 1:5,
    "interval of aggregate salaries and shares" = c(LETTERS[1:8], "K"),
    unit                                        = "N",
    time                                        = px_all(),
    .col_code                                   = TRUE
    ) %>% 
  as_tibble()

ESX5A <- 
  ESX5A_raw %>% 
  rename(lonsum = `interval of aggregate salaries and shares`) %>% 
  mutate(
    time   = time %>% make_date(),
    lonsum = lonsum %>% str_remove_all("[A-K]|\\.") %>% trimws() %>% fct_inorder() %>% fct_rev()
  )


# Plot
ESX5A %>% 
  ggplot(aes(
    x    = time,
    y    = value,
    fill = lonsum
  )) +
  geom_area() +
  facet_wrap(~ municipality, 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 = `interval of aggregate salaries and shares`) %>% 
  filter(time >= Sys.time() %>% year() - 5) %>% 
  mutate(
    time         = time %>% fct_inorder() %>% fct_rev(),
    municipality = municipality %>% fct_inorder(),
    lonsum       = lonsum %>% str_remove_all("[A-K]|\\.") %>% trimws() %>% fct_inorder() %>% fct_rev()
    ) %>% 
  spread(time, value) %>% 
  arrange(municipality, desc(lonsum))

ESX5A %>% 
  select(-c(municipality, unit)) %>% 
  rename(col_lab) %>% 
  statgl_table() %>% 
  pack_rows(index = ESX5A[["municipality"]] %>% table()) %>% 
  add_footnote(ESX5A[["unit"]][1], notation = "symbol")

Akissarsialiussaqassuseq	2021	2020
Kommune Kujalleq
00-10	37	36
10-50	70	45
50-100	58	48
100-250	62	71
250-500	45	33
500-1000	26	25
1000-5000	35	35
5000-10000	7	5
10000-it sinnerlugit	4	5
Kommuneqarfik Sermersooq
00-10	84	94
10-50	173	134
50-100	145	116
100-250	213	189
250-500	174	165
500-1000	150	141
1000-5000	243	247
5000-10000	42	45
10000-it sinnerlugit	78	69
Qeqqata Kommunia
00-10	67	51
10-50	105	66
50-100	86	66
100-250	97	98
250-500	64	70
500-1000	39	43
1000-5000	76	71
5000-10000	16	17
10000-it sinnerlugit	9	9
Kommune Qeqertalik
00-10	76	43
10-50	93	95
50-100	60	55
100-250	86	84
250-500	50	44
500-1000	17	20
1000-5000	22	23
5000-10000	5	5
10000-it sinnerlugit	3	2
Avannaata Kommunia
00-10	70	65
10-50	178	152
50-100	176	169
100-250	312	288
250-500	251	309
500-1000	120	122
1000-5000	72	75
5000-10000	7	7
10000-it sinnerlugit	11	10
* Suliffeqarfiit amerlassusaat

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