sdg2020

Meeqqat atualinnginnermi ulluunerani neqeroorutiniittut, 3-niik 5-inut ukiullit

FN 4.2.2 Meeqqat atualinnginnermi ulluunerani neqeroorutiniittut (3-5-inik ukiullit)

# Import
OFXUKN1_raw <-
  statgl_url("OFXUKN1", lang = language) %>% 
  statgl_fetch(
    born_var   = 3:5,
    inst_type2 = 1:5,
    .col_code  = TRUE
    ) %>% 
  as_tibble()

# Transform
OFXUKN1 <-
  OFXUKN1_raw %>% 
  mutate(across(where(is.integer), ~ if_else(is.na(.x), 0, .x))) |> 
  summarise(value = sum(value), .by = c(inst_type2, aar)) |> 
  mutate(
    aar = aar %>% make_date(),
    inst_type2 = inst_type2 %>% fct_inorder(),
    alder = "Børn 3-5 år"
    )

# Plot
OFXUKN1 %>% 
  ggplot(aes(
    x    = aar,
    y    = value,
    fill = inst_type2
  )) +
  geom_col() +
  scale_y_continuous(labels = scales::unit_format(
    suffix       = " ",
    big.mark     = ".",
    decimal.mark = ","
  )) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = FALSE, nrow = 2)) +
  labs(
    title    = sdg4$figs$fig1$title[language],
    subtitle = OFXUKN1[[4]][1],
    x        = " ",
    y        = sdg4$figs$fig1$y_lab[language],
    fill     = " ",
    caption  = sdg4$figs$fig1$cap[language]
  )

Kisitsisaataasivik

# Transform
OFXUKN1 <-
  OFXUKN1_raw %>% 
  #arrange(desc(time)) %>% 
  filter(aar >= year(Sys.time()) - 5) %>% 
  mutate(across(where(is.integer), ~ if_else(is.na(.x), 0, .x))) |> 
  summarise(value = sum(value), .by = c(inst_type2, aar)) |> 
  mutate(
    aar = aar %>% factor(levels = unique(aar)),
    inst_type2 = inst_type2 %>% fct_inorder(),
    alder = "Børn 3-5 år"
    ) %>% 
  spread(aar, value)

# Table
OFXUKN1 %>% 
  select(-2) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  pack_rows(index = table(OFXUKN1[[2]])) %>% 
  add_footnote(
    sdg4$figs$fig1$foot[language], 
    notation = "symbol"
    )

	2020	2021	2022	2023	2024
Børn 3-5 år
Meeraaqqeriviit	52	102	149	189	151
Meeqqeriviit	1.917	1.943	1.876	1.869	1.895
Meeqqeriviit meeraaqqeriviillu akuleriit	19	21	27	10	4
Angerlarsimafimmi paarsisartut	104	120	114	115	130
Pisortat neqeroorutaat allat	6	9	5	18	3
^* Meeqqat amerlassusaat, 3-5-inik ukiullit.

# Import
OFXUKN1_raw <-
  statgl_url("OFXUKN1", lang = language) %>% 
  statgl_fetch(
    born_var   = 3:5,
    inst_type2 = 1:5,
    bosted     = 1:2,
    .col_code  = TRUE
    ) %>% 
  as_tibble()

# Transform
OFXUKN1 <-
  OFXUKN1_raw %>% 
  mutate(
    inst_type2 = inst_type2 %>% fct_inorder(),
    bosted  = bosted %>% fct_inorder(),
    aar = aar %>% make_date(),
    born_var = "Børn 3-5 år",
    across(where(is.integer), ~ if_else(is.na(.x), 0, .x))
    ) |> 
  summarise(value = sum(value), .by = c(inst_type2, born_var, bosted, aar))

# Plot
OFXUKN1 %>% 
  ggplot(aes(
    x    = aar,
    y    = value,
    fill = inst_type2
    )) +
  geom_col() +
  facet_wrap(~ bosted, scales = "free_y") +
  theme_statgl() +
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = FALSE, nrow = 2)) +
  labs(
    title    = sdg4$figs$fig2$title[language],
    subtitle = OFXUKN1[[2]][1],
    x        = " ",
    y        = sdg4$figs$fig2$y_lab[language],
    fill     = NULL,
    caption  = sdg4$figs$fig2$cap[language]
  )

Kisitsisaataasivik

# Transform
OFXUKN1 <- 
  OFXUKN1_raw %>% 
  mutate(born_var = "Børn 3-5 år",
    across(where(is.integer), ~ if_else(is.na(.x), 0, .x))) |> 
  #arrange(desc(time)) %>%
  summarise(value = sum(value), .by = c(inst_type2, born_var, bosted, aar)) |> 
  filter(aar >= year(Sys.time()) - 5) %>% 
  mutate(aar = aar %>% factor(levels = unique(aar))) %>% 
  spread(aar, value) |> 
  arrange(bosted)

# Table
OFXUKN1 %>% 
  select(-c(2, 3)) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  pack_rows(index = table(OFXUKN1[[2]])) %>% 
  pack_rows(index = table(OFXUKN1[[3]])) %>% 
  add_footnote(
    sdg4$figs$fig2$foot[language], 
    notation = "symbol"
    )

	2020	2021	2022	2023	2024
Børn 3-5 år
Illoqarfiit
Angerlarsimafimmi paarsisartut	10	11	17	9	7
Meeqqeriviit	1.856	1.885	1.815	1.790	1.833
Meeqqeriviit meeraaqqeriviillu akuleriit	0	0	0	0	0
Meeraaqqeriviit	47	94	133	178	140
Pisortat neqeroorutaat allat	6	9	5	18	3
Nunaqarfiit
Angerlarsimafimmi paarsisartut	94	109	97	106	123
Meeqqeriviit	61	58	61	79	62
Meeqqeriviit meeraaqqeriviillu akuleriit	19	21	27	10	4
Meeraaqqeriviit	5	8	16	11	11
Pisortat neqeroorutaat allat	0	0	0	0	0
^* Meeqqat amerlassusaat, 3-5-inik ukiullit.

Meeqqat atuarfianni alloriarfinni misilitsinnernit angusat

FN 4.1.1 Meeqqat atuarfianni 3.klassini aamma 7.klassini alloriarfinni misilitsinnerni inerniliillaqqissuseq

# Import
UDXTKB_raw <-
  statgl_url("UDXTKB", lang = language) %>%
  statgl_fetch(
    subject   = px_all(),
    grade     = c(3, 7),
    unit      = "B",
    .col_code = TRUE) %>% 
  as_tibble()

# Transform
UDXTKB <-
  UDXTKB_raw %>% 
  mutate(
    time     = time %>% make_date(),
     subject =  subject %>% fct_inorder()
    )

# Plot
UDXTKB %>% 
  ggplot(aes(
    x     = time,
    y     = value,
    color = subject
    )) +
  geom_line(size = 2) +
  facet_wrap(~ grade) +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 1, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl() + 
  scale_color_statgl() +
  labs(
    title    = sdg4$figs$fig3$title[language],
    subtitle = UDXTKB[[3]][1],
    x        = " ",
    y        = " ",
    color    = sdg4$figs$fig3$color[language],
    caption  = sdg4$figs$fig3$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXTKB <- 
  UDXTKB_raw %>% 
  arrange(desc(time)) %>% 
  filter(time >= year(Sys.time()) - 5) %>% 
  mutate(time = time %>% factor(levels = unique(time))) %>% 
  arrange(grade, desc(subject)) %>% 
  unite(combi, 1, 2, sep = ",") %>% 
  mutate(combi = combi %>% factor(levels = unique(combi))) %>% 
  spread(1, ncol(.))

vec      <- UDXTKB %>% select(-(1:2)) %>% colnames() %>% str_split(",") %>% unlist()
head_vec <- table(vec[c(F, T)])
col_vec  <- vec[c(T, F)]

# Table
UDXTKB %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(col.names = c(" ", col_vec)) %>% 
  add_header_above(c(" ", head_vec)) %>% 
  pack_rows(index = table(UDXTKB[[1]]))

	klassi				klassi
	Tuluttut,3. klassi	Qallunaatut,3. klassi	Matematikki,3. klassi	Kalaallisut,3. klassi	Tuluttut,7. klassi	Qallunaatut,7. klassi	Matematikki,7. klassi	Kalaallisut,7. klassi
Inerniliillaqqissuseq (eqqortut pct.-inngorlugit)
2024	NA	41	49	45	84	42	40	56
2023	NA	48	52	48	86	45	41	59
2022	NA	41	48	41	82	51	41	62
2021	NA	47	51	48	73	50	40	61
2020	NA	50	51	41	73	57	41	61

# Import
UDXTKB_raw <-
  statgl_url("UDXTKB", lang = language) %>%
  statgl_fetch(
    subject              = px_all(),
    grade                = c(3, 7),
    unit                 = "B",
    "place of residence" = 1:2,
    .col_code            = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXTKB <-
  UDXTKB_raw %>% 
  mutate(
    time = time %>% make_date(),
    `place of residence` = `place of residence` %>% fct_inorder(),
    subject = subject %>% fct_inorder()
    )

# Plot
UDXTKB %>% 
  ggplot(aes(
    x     = time,
    y     = value,
    color = subject
  )) +
  geom_line(size = 2) +
  facet_grid(grade ~ `place of residence`) +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 1, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl() + 
  scale_color_statgl() +
  labs(
    title    = sdg4$figs$figX$title_fig4,
    subtitle = UDXTKB[[4]][1],
    x        = " ",
    y        = " ",
    color    = sdg4$figs$fig4$color[language],
    caption  = sdg4$figs$fig4$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXTKB <- 
  UDXTKB_raw %>% 
  arrange(desc(time)) %>% 
  filter(time >= year(Sys.time()) - 5) %>% 
  mutate(time = time %>% fct_inorder()) %>% 
  arrange(grade, subject) %>% 
  unite(combi, 1, 2, 3, sep = ",") %>% 
  mutate(combi = combi %>% factor(levels = unique(combi))) %>% 
  spread(1, 4) 

vec       <- UDXTKB[-(1:2)] %>% colnames() %>% str_split(",") %>% unlist()
head_vec1 <- rep(vec[c(F, T, F)][1:8] %>% table(), 2)
head_vec2 <- vec[c(F, F, T)] %>% table()
col_vec   <- vec[c(T, F, F)]

UDXTKB %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(col.names = c(" ", col_vec)) %>% 
  add_header_above(c(" ", head_vec1)) %>% 
  add_header_above(c(" ", head_vec2)) %>% 
  pack_rows(index = table(UDXTKB[[1]]))

	klassi								klassi
	Kalaallisut		Matematikki		Qallunaatut		Tuluttut		Kalaallisut		Matematikki		Qallunaatut		Tuluttut
	Illoqarfiit,Kalaallisut,3. klassi	Nunaqarfiit,Kalaallisut,3. klassi	Illoqarfiit,Matematikki,3. klassi	Nunaqarfiit,Matematikki,3. klassi	Illoqarfiit,Qallunaatut,3. klassi	Nunaqarfiit,Qallunaatut,3. klassi	Illoqarfiit,Tuluttut,3. klassi	Nunaqarfiit,Tuluttut,3. klassi	Illoqarfiit,Kalaallisut,7. klassi	Nunaqarfiit,Kalaallisut,7. klassi	Illoqarfiit,Matematikki,7. klassi	Nunaqarfiit,Matematikki,7. klassi	Illoqarfiit,Qallunaatut,7. klassi	Nunaqarfiit,Qallunaatut,7. klassi	Illoqarfiit,Tuluttut,7. klassi	Nunaqarfiit,Tuluttut,7. klassi
Inerniliillaqqissuseq (eqqortut pct.-inngorlugit)
2024	43	48	48	56	42	38	NA	NA	55	57	39	40	45	34	86	55
2023	48	49	53	45	50	36	NA	NA	57	66	43	40	47	40	88	73
2022	41	52	47	52	41	43	NA	NA	62	61	41	39	54	40	86	53
2021	48	47	52	50	48	39	NA	NA	59	62	40	41	52	45	76	54
2020	41	57	50	51	50	52	NA	NA	61	62	42	37	59	43	78	41

Meeqqat atuarfianni soraarummeernerit

GS Meeqqat atuarfianni inaarutaasumik misilitsinnernit karakteerit

# Import
UDXFKK_raw <-
  statgl_url("UDXFKK", lang = language) %>% 
  statgl_fetch(
    unit             = "andel",
    grade            = "FO",
    subject          = c("01", "02", "03", "04"),
    "type of grades" = 56:58,
    .col_code        = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXFKK <-
  UDXFKK_raw %>% 
  mutate(
    `type of grades` = `type of grades` %>% str_remove_all("Prøvekarakter -") %>% trimws() %>% str_to_title(),
    subject          = subject %>% fct_inorder(),
    time             = time %>% make_date()
    )

# Plot
UDXFKK %>% 
  ggplot(aes(
    x     = time,
    y     = value,
    color = `type of grades`
    )) +
  geom_line(size = 2) +
  facet_wrap( ~ subject, ncol = 2) +
  theme_statgl() + 
  scale_color_statgl(guide = guide_legend(nrow = 3)) +
  labs(
    title   = sdg4$figs$fig5$title[language],
    color   = sdg4$figs$fig5$color[language],
    x       = " ",
    y       = sdg4$figs$fig5$y_lab[language],
    caption = sdg4$figs$fig5$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXFKK <-
  UDXFKK_raw %>% 
  mutate(
    `type of grades` = `type of grades` %>% 
      str_remove_all("Prøvekarakter -") %>%
      trimws() %>%
      str_to_title()
    ) %>% 
  #arrange(desc(time)) %>% 
  filter(
    value != "NA",
    time >= year(Sys.time()) - 5
    ) %>% 
  mutate(
    subject = subject %>% fct_inorder(),
    time = time %>% factor(levels = unique(time)),
    ) %>% 
  spread(5, 6) %>% 
  arrange(subject)

# Table
UDXFKK %>% 
  select(-(1:3)) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = table(UDXFKK[[1]] %>% str_to_title())) %>% 
  pack_rows(index = table(UDXFKK[[3]])) %>% 
  add_footnote(UDXFKK[[2]][1], notation = "symbol")

	2021	2022	2023	2024
Agguaqatigiissillugu Karakteeri
Kalaallisut
Inaarutaasumik Misilitsinnermi Karakteeri - Allattariarsorneq	5,35	5,48	4,75	5,30
Inaarutaasumik Misilitsinnermi Karakteeri - Oqaluttariarsorneq	5,96	6,81	6,54	6,80
Inaarutaasumik Misilitsinnermi Karakteeri - Piginnaasat	3,56	3,72	3,99	4,86
Qallunaatut
Inaarutaasumik Misilitsinnermi Karakteeri - Allattariarsorneq	3,36	3,58	3,82	3,18
Inaarutaasumik Misilitsinnermi Karakteeri - Oqaluttariarsorneq	5,36	4,85	6,15	4,63
Inaarutaasumik Misilitsinnermi Karakteeri - Piginnaasat	4,47	4,14	4,05	3,70
Matematikki
Inaarutaasumik Misilitsinnermi Karakteeri - Allattariarsorneq	2,17	2,52	2,98	2,48
Inaarutaasumik Misilitsinnermi Karakteeri - Oqaluttariarsorneq	4,88	5,24	5,58	5,60
Inaarutaasumik Misilitsinnermi Karakteeri - Piginnaasat	4,94	4,89	4,82	4,81
Tuluttut
Inaarutaasumik Misilitsinnermi Karakteeri - Allattariarsorneq	4,11	4,51	4,56	5,34
Inaarutaasumik Misilitsinnermi Karakteeri - Oqaluttariarsorneq	6,49	6,52	6,99	7,55
Inaarutaasumik Misilitsinnermi Karakteeri - Piginnaasat	4,90	5,20	5,56	5,63
^* Meeqqat atuarfianni naggataarlutik atuartut

Covid-19 peqqutaalluni 2020-mi naggataarutaasumik soraarummeertoqanngilaq.

Meeqqat atuarfianniit ilinniakkanut ingerlaqqinneq

GS Meeqqat atuarfianniit inuusuttut ilinniarfiinut ingerlaqqinnerit

# Import
UDXTRFA1_raw <-
  statgl_url("UDXTRFA1", lang = language) %>% 
  statgl_fetch(
    aar       = 2,
    status    = px_all(),
    dim_aar   = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXTRFA1 <-
  UDXTRFA1_raw %>%
  filter(dim_aar <= year(Sys.time()) - 3) %>% 
  mutate(dim_aar = dim_aar %>% make_date())

  


# Plot
UDXTRFA1 %>% 
  ggplot(aes(
    x    = dim_aar,
    y    = value,
    fill = status
  )) +
  geom_col(position = "fill") +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 100, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  scale_fill_statgl(reverse = TRUE) +
  theme_statgl() +
  labs(
    title    = sdg4$figs$fig6$title[language],
    subtitle = sdg4$figs$fig6$sub[language],
    x        = sdg4$figs$fig6$x_lab[language],
    y        = " ",
    fill     = sdg4$figs$fig6$fill[language],
    caption  = sdg4$figs$fig6$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXTRFA1 <- 
  UDXTRFA1_raw %>% 
  filter(dim_aar <= year(Sys.time()) - 3) %>% 
  #arrange(desc(`graduation year`)) %>% 
  filter(dim_aar >= year(Sys.time()) - 8) %>% 
  mutate(dim_aar = dim_aar %>% factor(levels = unique(dim_aar))) %>% 
  spread(3, 4)

# Table
UDXTRFA1 %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  add_footnote(
    sdg4$figs$fig6$foot[language],
    notation = "symbol"
  )

	2017	2018	2019	2020	2021	2022
Naammassisimasut	4	7	5	7	3	6
Suli ingerlatsisut	264	243	250	269	252	226
Unitsitsisut	117	108	82	96	97	116
Aallartitsisimanngitsut	301	340	311	312	357	330
^* Meeqqat atuarfianniit inuusuttut ilinniarfiinut ingerlaqqinnerit (meeqqat atuarfianni soraarummeereernermi ukiut marluk qaangiunnerini), ilinniartut amerlassusaat.

# Import
UDXTRFA1_raw <-
  statgl_url("UDXTRFA1", lang = language) %>% 
  statgl_fetch(
    aar       = 2,
    status    = px_all(),
    dim_aar   = px_all(),
    sex       = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXTRFA1 <-
  UDXTRFA1_raw %>% 
  filter(dim_aar <= year(Sys.time()) - 3) %>% 
  mutate(dim_aar = dim_aar %>% make_date())

# Plot
UDXTRFA1 %>% 
  ggplot(aes(
    x    = dim_aar,
    y    = value,
    fill = status
  )) +
  geom_col(position = "fill") +
  facet_wrap(~ sex) +
  scale_y_continuous(labels  = scales::percent_format()) +
  scale_fill_statgl(reverse = TRUE) +
  theme_statgl() +
  labs(
    title    = sdg4$figs$fig7$title[language],
    subtitle = sdg4$figs$fig7$sub[language],
    x        = sdg4$figs$fig7$x_lab[language],
    y        = " ",
    fill     = sdg4$figs$fig7$fill[language],
    caption  = sdg4$figs$fig7$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXTRFA1 <- 
  UDXTRFA1_raw %>% 
  filter(dim_aar <= year(Sys.time()) - 3) %>% 
  #arrange(desc(`graduation year`)) %>% 
  filter(dim_aar >= year(Sys.time()) - 8) %>% 
  mutate(dim_aar = dim_aar %>% factor(levels = unique(dim_aar))) %>% 
  spread(4, 5) %>% 
  arrange(status)
  
# Table
UDXTRFA1 %>% 
  select(-1, -3) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  pack_rows(index = table(UDXTRFA1[[3]])) %>% 
  add_footnote(
    sdg4$figs$fig7$foot[language],
    notation = "symbol"
  )

	2017	2018	2019	2020	2021	2022
Naammassisimasut
Angutit	153	171	174	170	181	169
Arnat	148	169	137	142	176	161
Suli ingerlatsisut
Angutit	3	7	3	7	2	6
Arnat	1	0	2	0	1	0
Unitsitsisut
Angutit	111	101	102	119	111	94
Arnat	153	142	148	150	141	132
Aallartitsisimanngitsut
Angutit	53	45	45	45	44	45
Arnat	64	63	37	51	53	71
^* Karaktergennemsnit, Folkeskolens Afgangselever

Ilinniarnertuunngorniarnermiit ingerlariaqqiffiusumik ilinniarnermut ingerlaqqinneq

GS Ilinniarnertuunngorniarnermiit ingerlariaqqiffiusumik ilinniarnermut ingerlaqqinnerit

# Import
UDXTRGU2_raw <-
  statgl_url("UDXTRGU2", lang = language) %>% 
  statgl_fetch(
    aar     = 2,
    status  = px_all(),
    dim_aar = px_all(),
    .col_code = TRUE) %>% 
  as_tibble()

# Transform
UDXTRGU2 <-
  UDXTRGU2_raw %>% 
  filter(dim_aar <= year(Sys.time()) - 2) |> 
  mutate(dim_aar = dim_aar %>% make_date())

# Plot
UDXTRGU2 %>% 
  ggplot(aes(
    x    = dim_aar,
    y    = value,
    fill = status
    )) +
  geom_col(position = "fill") +
  scale_y_continuous(labels  = scales::percent_format(
    scale = 100, 
    accuracy = 1, 
    big.mark = ".",
    decimal.mark = ","
    )) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE) +
  labs(
    title    = sdg4$figs$fig8$title[language],
    subtitle = sdg4$figs$fig8$sub[language],
    x        = sdg4$figs$fig8$x_lab[language],
    y        = " ",
    fill     = sdg4$figs$fig8$fill[language],
    caption  = sdg4$figs$fig8$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXTRGU2 <-
  UDXTRGU2_raw %>% 
  filter(dim_aar >= year(Sys.time()) - 9 & dim_aar < year(Sys.time()) - 3) %>% 
  mutate(dim_aar = dim_aar %>% factor(levels = unique(dim_aar))) %>% 
  spread(3, 4)

# Table
UDXTRGU2 %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  add_footnote(
    sdg4$figs$fig8$foot[language],
    notation = "symbol"
    )

	2016	2017	2018	2019	2020	2021
Naammassisimasut	28	29	32	35	36	26
Suli ingerlatsisut	157	134	137	131	112	124
Unitsitsisut	69	61	46	50	54	67
Aallartitsisimanngitsut	91	104	89	87	93	95
^* Ilinniarnertuunngorniarnermiik ingerlariaqqiffiusumik ilinniarnermut ingerlaqqinneq (ilinniarnertuunngoreernermik ukiut marluk qaangiunnerini), ilinniartut amerlassusaat.

# Import
UDXTRGU2_raw <-
  statgl_url("UDXTRGU2", lang = language) %>% 
  statgl_fetch(
    aar       = 2,
    status    = px_all(),
    dim_aar   = px_all(),
    sex       = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXTRGU2 <- 
  UDXTRGU2_raw %>% 
  filter(dim_aar <= year(Sys.time()) - 3) |> 
  mutate(dim_aar = dim_aar %>% make_date())

# Plot
UDXTRGU2 %>% 
  ggplot(aes(
    x    = dim_aar,
    y    = value,
    fill = status
  )) +
  geom_col(position = "fill") +
  facet_wrap( ~ sex) +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 100, 
    accuracy     = 1,
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE) +
  labs(
    title    = sdg4$figs$fig9$title[language],
    subtitle = sdg4$figs$fig9$sub[language],
    x        = sdg4$figs$fig9$x_lab[language],
    y        = " ",
    fill     = sdg4$figs$fig9$fill[language],
    caption  = sdg4$figs$fig9$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXTRGU2 <-
  UDXTRGU2_raw %>% 
  #arrange(desc(`graduation year`)) %>% 
  filter(dim_aar >= year(Sys.time()) - 8 & dim_aar < year(Sys.time()) - 3) %>% 
  mutate(dim_aar = dim_aar %>% factor(levels = unique(dim_aar))) %>% 
  spread(4, 5) %>% 
  arrange(status)

# Table
UDXTRGU2 %>% 
  select(-c(1, 3)) %>% 
  rename("  " = 1) %>% 
  statgl_table(replace_0s = TRUE) %>% 
  pack_rows(index = UDXTRGU2[[3]] %>% table()) %>% 
  add_footnote(
    sdg4$figs$fig9$foot[language],
    notation = "symbol"
  )

	2017	2018	2019	2020	2021
Naammassisimasut
Angutit	51	38	49	44	37
Arnat	53	51	38	49	58
Suli ingerlatsisut
Angutit	10	13	9	12	12
Arnat	19	19	26	24	14
Unitsitsisut
Angutit	61	52	49	32	33
Arnat	73	85	82	80	91
Aallartitsisimanngitsut
Angutit	22	13	16	23	21
Arnat	39	33	34	31	46
^* Ilinniarnertuunngorniarnermiik ingerlariaqqiffiusumik ilinniarnermut ingerlaqqinneq (ilinniarnertuunngoreernermik ukiut marluk qaangiunnerini), ilinniartut amerlassusaat.

Ilinniakkamik ingerlatsitsut

GS Ilinniakkamik ingerlatsisut amerlassusaat ilinniakkap qaffasissusaa aamma nuna malillugit

# Import
UDXISC11B_raw <-
  statgl_url("UDXISC11B", lang = language) %>% 
  statgl_fetch(
    isced = px_all(),
    .col_code            = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXISC11B <-
  UDXISC11B_raw %>% 
  mutate(taar = taar %>% make_date(),
        isced = isced %>%  fct_inorder() %>% fct_rev(),
        value = value * 10^-3)

# Plot
UDXISC11B %>% 
  ggplot(aes(
    x    = taar,
    y    = value,
    fill = isced
  )) +
  geom_col() +
   guides(fill = guide_legend(nrow = 4, byrow = TRUE)) +
  theme_statgl() +
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = FALSE)) +
  labs(
    title   = sdg4$figs$fig10$title[language],
    x       = " ",
    y       = sdg4$figs$fig10$y_lab[language],
    fill    = NULL,
    caption = sdg4$figs$fig10$cap[language]
  )

Kisitsisaataasivik

# Transform
UDXISC11B <-
  UDXISC11B_raw %>% 
  #arrange(desc(time)) %>% 
  filter(taar >= year(Sys.time()) - 6) %>% 
  mutate(
         isced = isced %>% factor(levels = unique(isced)),
         taar  = taar %>% factor(levels = unique(taar)),
         ) %>% 
  spread(2, 3)

# Table
UDXISC11B %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(
    sdg4$figs$fig10$foot[language],
    notation = "symbol"
    )

	2019	2020	2021	2022	2023	2024
Ilinniarnertuunngorniarneq	1.120	1.170	1.161	1.129	1.064	1.071
Inuussutissarsiornermik ilinniarneq	1.087	1.136	1.025	1.001	921	876
Angusanik qaffassaanerit	29	29	14	19	22	26
Ingerlariaqqiffiusumik ilinniarneq naatsoq	186	167	155	162	155	162
Bachelorinngorniarneq	323	373	359	346	333	353
Professionsbachelorinngorniarneq	561	550	527	528	511	528
Kandidatinngorniarneq	182	170	165	155	154	150
^* Ilinniakkamik ingerlatsisut amerlassusaat.

# Import
UDXISC11B_raw <-
  statgl_url("UDXISC11B", lang = language) %>% 
  statgl_fetch(
    skoleomr   = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Translate
UDXISC11B <-
  UDXISC11B_raw %>% 
  mutate(
    taar     = taar %>% make_date(),
    skoleomr = skoleomr %>% fct_reorder(value),
    value    = value * 10^-3
    )

# Plot
UDXISC11B %>% 
  ggplot(aes(
    x    = taar,
    y    = value,
    fill = skoleomr
  )) +
  geom_col() +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = TRUE)) +
  labs(
    title   = sdg4$figs$fig11$title[language],
    x       = " ",
    y       = sdg4$figs$fig11$y_lab[language],
    fill    = " ",
    caption = sdg4$figs$fig11$cap[language] 
  )

Kisitsisaataasivik

# Transform
UDXISC11B <-
  UDXISC11B_raw %>% 
  #arrange(desc(time)) %>% 
  filter(taar >= year(Sys.time()) - 6) %>% 
  mutate(
    taar    = taar %>% fct_inorder(),
    skoleomr = skoleomr %>% fct_inorder
    ) %>% 
  spread(2, 3)

# Table
UDXISC11B %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(
    sdg4$figs$fig11$foot[language],
    notation = "symbol"
    )

	2019	2020	2021	2022	2023	2024
Kalaallit Nunaanni Atuarfiit	2.945	3.061	2.922	2.806	2.638	2.580
Danmarkimi atuarfiit	518	510	464	512	506	569
Nunani allani atuarfiit	25	24	20	22	16	17
^* Ilinniakkamik ingerlatsisut amerlassussaat.

FN 4.3.1 Ilinniakkamik ingerlatsisut amerlassusaat suiaassuseq malillugu

# Import
UDXISC11B_raw <-
  statgl_url("UDXISC11B", lang = language) %>% 
  statgl_fetch(
    sex       = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXISC11B <-
  UDXISC11B_raw %>% 
  mutate(
    taar  = taar %>% make_date(),
    sex   = sex %>% reorder(value),
    value = value * 10^-3
    )

# Plot
UDXISC11B %>% 
  ggplot(aes(
    x    = taar,
    y    = value,
    fill = sex
  )) +
  geom_col() +
  theme_statgl() + 
  scale_fill_statgl() +
  labs(
    title   = sdg4$figs$fig12$title[language],
    x       = " ",
    y       = sdg4$figs$fig12$y_lab[language],
    fill    = " ",
    caption = sdg4$figs$fig12$cap[language]
  )

Kisitsisaataasivik

# Transform
UDXISC11B <-
  UDXISC11B_raw %>% 
  #arrange(desc(time)) %>% 
  filter(taar >= year(Sys.time()) - 6) %>% 
  mutate(taar = taar %>% fct_inorder()) %>% 
  spread(2, 3)

# Table
UDXISC11B %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(
    sdg4$figs$fig12$foot[language],
    notation = "symbol"
    )

	2019	2020	2021	2022	2023	2024
Angutit	1.370	1.363	1.289	1.231	1.150	1.160
Arnat	2.118	2.232	2.117	2.109	2.010	2.006
^* Ilinniakkamik ingerlatsisut amerlassusaat.

Ilinniarnerit naammassineqarsimasut

GS Ilinniarnerit naammassineqarsimasut amerlassusaat

# Import
UDXISC11D_raw <-
  statgl_url("UDXISC11D", lang = language) %>% 
  statgl_fetch(
    Isced     = px_all(),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXISC11D <-
  UDXISC11D_raw %>%
  mutate(
    slutaar              = slutaar %>% make_date(),
    id                   = row_number(),
    Isced = Isced %>% str_remove("uddannelse"),
    Isced = Isced %>% fct_reorder(id, .fun = min, na.rm = TRUE) %>% fct_rev()
  )

# Plot
UDXISC11D %>% 
  ggplot(aes(
    x    = slutaar,
    y    = value,
    fill = Isced
    )) +
  geom_col() +
  scale_y_continuous(labels = scales::number_format(
    accuracy     = 1,
    big.mark     = ".",
    decimal.mark = ",")) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = TRUE, nrow = 4)) +
  labs(
    title    = sdg4$figs$fig13$title[language],
    subtitle = sdg4$figs$fig13$sub[language],
    x        = " ",
    y        = sdg4$figs$fig13$y_lab[language],
    fill     = sdg4$figs$fig13$fill[language],
    caption  = sdg4$figs$fig13$cap[language] 
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXISC11D <- 
  UDXISC11D_raw %>% 
  #arrange(desc(time)) %>% 
  filter(slutaar >= year(Sys.time()) - 6) %>% 
  mutate(
    Isced    = Isced %>% fct_inorder(),
    slutaar  = slutaar %>% fct_inorder()
    ) %>% 
  spread(2, 3)

# Table
UDXISC11D %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(
    sdg4$figs$fig13$foot[language],
    notation = "symbol"
    )

	2019	2020	2021	2022	2023	2024
Ilinniarnertuunngorniarneq	314	310	318	282	333	293
Inuussutissarsiornermik ilinniarneq	399	411	448	376	403	362
Angusanik qaffassaanerit	111	125	141	119	99	89
Ingerlariaqqiffiusumik ilinniarneq naatsoq	55	68	66	62	62	62
Bachelorinngorniarneq	53	47	54	55	56	53
Professionsbachelorinngorniarneq	129	107	119	103	88	95
Kandidatinngorniarneq	35	40	35	32	35	28
^* Qaffasinnerpaatut ilinniakat naammassineqarsimasut, naammassinnissimasut amerlassusaat.

# Import
UDXISC11D_raw <-
  statgl_url("UDXISC11D", lang = language) %>% 
  statgl_fetch(
    Isced     = px_all(),
    sex       = px_all(),
    skoleomr  = c("A_SG", "B_SD"),
    .col_code = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXISC11D <- 
  UDXISC11D_raw %>% 
  mutate(
    Isced    = Isced %>% str_remove("uddannelse") %>% trimws(),
    Isced    = Isced %>% fct_inorder() %>% fct_rev(),
    sex      = sex  %>% fct_inorder(),
    skoleomr = skoleomr %>% fct_inorder,
    slutaar  = slutaar    %>% make_date()
  )

# Plot
UDXISC11D %>% 
  ggplot(aes(
    x = slutaar,
    y = value, 
    fill = Isced
  )) +
  geom_col() +
  facet_grid(skoleomr ~ sex, 
             scales = "free_y") +
  scale_y_continuous(labels = scales::number_format(
    accuracy = 1, 
    big.mark = ".",
    decimal.mark = ","
    )) +
  theme_statgl() +
  scale_fill_statgl(reverse = TRUE, 
                    guide = guide_legend(reverse = TRUE, nrow = 4)) +
  labs(
    title    = sdg4$figs$fig14$title[language],
    subtitle = sdg4$figs$fig14$sub[language],
    x        = " ",
    y        = sdg4$figs$fig14$y_lab[language],
    fill     = sdg4$figs$fig14$fill[language],
    caption  = sdg4$figs$fig14$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXISC11D <- 
  UDXISC11D_raw %>% 
  #arrange(desc(time)) %>% 
  filter(slutaar >= year(Sys.time()) - 4) %>% 
  mutate(
    slutaar  = slutaar %>% fct_inorder(),
    Isced    = Isced %>% fct_inorder(),
    skoleomr = skoleomr %>% fct_inorder()
    ) %>% 
  unite(combi, 2, 4, sep = ",") %>%  
  mutate(combi = combi %>% fct_inorder()) %>% 
  spread(2, 4)

vec      <- UDXISC11D[-(1:2)] %>% colnames() %>% str_split(",") %>% unlist()
head_vec <- table(vec[c(F, T)]) %>% rev()
col_vec  <- vec[c(T, F)]

# Table
UDXISC11D %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(col.names = c(" ", col_vec)) %>% 
  pack_rows(index = table(UDXISC11D[[1]])) %>% 
  add_header_above(c(" ", head_vec))

	2024		2023		2022		2021
	Angutit,2021	Angutit,2022	Angutit,2023	Angutit,2024	Arnat,2021	Arnat,2022	Arnat,2023	Arnat,2024
Ilinniarnertuunngorniarneq
Kalaallit Nunaanni Atuarfiit	96	86	84	107	198	163	214	166
Danmarkimi atuarfiit	7	17	6	7	14	13	26	11
Inuussutissarsiornermik ilinniarneq
Kalaallit Nunaanni Atuarfiit	180	164	166	147	249	198	222	197
Danmarkimi atuarfiit	11	8	6	7	8	5	8	10
Angusanik qaffassaanerit
Kalaallit Nunaanni Atuarfiit	37	41	27	30	95	75	67	59
Danmarkimi atuarfiit	2	1	2	0	7	2	3	0
Ingerlariaqqiffiusumik ilinniarneq naatsoq
Kalaallit Nunaanni Atuarfiit	14	17	11	18	34	27	35	29
Danmarkimi atuarfiit	5	8	5	7	13	10	10	7
Bachelorinngorniarneq
Kalaallit Nunaanni Atuarfiit	10	8	15	16	22	24	29	22
Danmarkimi atuarfiit	5	7	6	3	14	14	5	11
Professionsbachelorinngorniarneq
Kalaallit Nunaanni Atuarfiit	12	17	15	10	86	75	52	65
Danmarkimi atuarfiit	6	4	9	6	13	7	12	14
Kandidatinngorniarneq
Kalaallit Nunaanni Atuarfiit	3	2	2	2	10	10	10	9
Danmarkimi atuarfiit	10	6	8	7	11	13	15	8

35-t 39-llu akornanni ukiullit ilinniarsimassusaat

GS 35-t 39-llu akornanni ukiullit ilinniagaasa qaffasissusaat

# Import
UDXISCPROF_raw <-
  statgl_url("UDXISCPROF", lang = language) %>% 
  statgl_fetch(
    alder_grp     = "35-39",
    ISCED11_level = c(20, 34, 35, 40, 50, 64, 65, 70, 80),
    .col_code     = TRUE
    ) %>% 
  as_tibble()
  
# Transform
UDXISCPROF <-
  UDXISCPROF_raw %>% 
  mutate(
    id = row_number(),
    ISCED11_level = ISCED11_level %>% str_remove("uddannelse") %>% 
    fct_reorder(id, .fun = min, na.rm = T) %>% fct_rev()
    )

# Plot
UDXISCPROF %>% 
  mutate(Aar = Aar %>% make_date()) %>% 
  ggplot(aes(
    x    = Aar, 
    y    = value,
    fill = ISCED11_level
    )) +
  geom_area(position = "fill") +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 100, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl(base_size = 11) +
  guides(fill = guide_legend(nrow = 3, byrow = TRUE)) +
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = TRUE)) +
  labs(
    title    = sdg4$figs$fig15$title[language],
    subtitle = UDXISCPROF[[2]][1],
    x        = " ",
    y        = " ",
    fill     = NULL,
    caption  = sdg4$figs$fig15$cap[language]
  )

Kisitsisaataasivik

Periaaseq

# Transform
UDXISCPROF <- 
  UDXISCPROF_raw %>% 
  #arrange(desc(time)) %>% 
  filter(Aar >= year(Sys.time()) - 5) %>% 
  mutate(
    Aar           = Aar %>% fct_inorder(),
    ISCED11_level = ISCED11_level %>% fct_inorder()
    ) %>% 
  spread(3, 4)

# Table
UDXISCPROF %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = table(UDXISCPROF[[1]])) %>% 
  add_footnote(
    sdg4$figs$fig15$foot[language], 
    notation = "symbol"
    )

	2020	2021	2022	2023
Ukiut 35-39
Atuarfik tunngaviliivik, 10.klasse tikillugu	1.669	1.696	1.781	1.901
Ilinniarnertuunngorniarneq	154	175	183	197
Inuussutissarsiornermik ilinniarneq	1.223	1.247	1.229	1.292
Angusanik qaffassaaneq	118	91	80	80
Ingerlariaqqiffiusumik ilinniarneq naatsoq	163	158	159	176
Bachelorinngorniarneq	48	48	58	56
Professionsbachelorinngorniarneq	394	417	433	442
Kandidatinngorniarneq	156	173	179	180
Ilisimatuunngorniarneq	7	9	9	11
^* Qaffasinnerpaatut ilinniagaq naammassisimasaq, naammassinnissimasut amerlassusaat.

# Import
UDXISCPROD_raw <-
  statgl_url("UDXISCPROD", lang = language) %>% 
  statgl_fetch(
    alder_grp     = "35-39",
    ISCED11_level = c(20, 34, 35, 40, 50, 64, 65, 70, 80),
    Bsted         = px_all(),
    .col_code     = TRUE
    ) %>% 
  as_tibble()
  
# Transform
UDXISCPROD <-
  UDXISCPROD_raw %>% 
  mutate(
    id                   = row_number(),
    ISCED11_level = ISCED11_level %>% str_remove("uddannelse") %>% 
           fct_reorder(id, .fun = min, na.rm = TRUE) %>% fct_rev(),
    Aar                 = Aar %>% make_date()
    )

# Plot
UDXISCPROD %>% 
  ggplot(aes(
    x    = Aar,
    y    = value,
    fill = ISCED11_level
    )) +
  geom_area(position = "fill") +
  facet_wrap(~ Bsted) +
  scale_y_continuous(labels  = scales::percent_format(
    scale        = 100, 
    accuracy     = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl(base_size = 11) +
  guides(fill = guide_legend(nrow = 3, byrow = TRUE)) +
  scale_fill_statgl(reverse = TRUE, guide = guide_legend(reverse = TRUE)) +
  labs(
    title    = sdg4$figs$fig16$title[language],
    subtitle = UDXISCPROD[[3]][1],
    x        = " ",
    y        = " ",
    fill     = NULL,
    caption  = sdg4$figs$fig16$cap[language]
  )

Kisitsisaataasivik

Periaaseq

UDXISCPROD <-
  UDXISCPROD_raw %>% 
  #arrange(desc(time)) %>% 
  filter(Aar >= year(Sys.time()) - 5) %>% 
  mutate(
    Aar = Aar %>% fct_inorder(),
    ISCED11_level = ISCED11_level %>% fct_inorder()
  ) %>% 
  arrange(ISCED11_level) %>% 
  unite(combi, 2, 4, sep = ",") %>% 
  mutate(combi = combi %>% fct_inorder()) %>% 
  spread(2, ncol(.))

vec      <- colnames(UDXISCPROD[-(1:2)]) %>% str_split(",") %>% unlist()
head_vec <- table(vec[c(F, T)]) %>% rev()
col_vec  <- vec[c(T, F)]

UDXISCPROD %>% 
  select(-1) %>% 
  rename(" " = 1) %>% 
  statgl_table(col.names = c(" ", col_vec), replace_0s = TRUE) %>% 
  add_header_above(c(" ", head_vec)) %>% 
  add_footnote(
    sdg4$figs$fig16$foot[language], 
    notation = "symbol"
    )

	2023		2022		2021		2020
	Illoqarfik,2020	Illoqarfik,2021	Illoqarfik,2022	Illoqarfik,2023	Nunaqarfik,2020	Nunaqarfik,2021	Nunaqarfik,2022	Nunaqarfik,2023
Atuarfik tunngaviliivik, 10.klasse tikillugu	1.360	1.389	1.506	1.618	309	307	275	283
Ilinniarnertuunngorniarneq	148	162	171	183	6	13	12	14
Inuussutissarsiornermik ilinniarneq	1.120	1.140	1.125	1.180	103	107	104	112
Angusanik qaffassaaneq	112	86	76	77	6	5	4	3
Ingerlariaqqiffiusumik ilinniarneq naatsoq	161	157	155	171	2	1	4	5
Bachelorinngorniarneq	48	48	58	55	0	0	0	1
Professionsbachelorinngorniarneq	383	403	411	427	11	14	22	15
Kandidatinngorniarneq	155	173	179	180	1	0	0	0
Ilisimatuunngorniarneq	7	9	9	11	0	0	0	0
^* Qaffasinnerpaatut ilinniagaq naammassisimaseq, naammassinnissimasut amerlassusaat.

Paasissutissalerinermi attaveqatigiinnermilu ingerlaatsit

FN 4.4.1 16-iniit 74-inut ukiullit akornanni paasissutissalerinermi attaveqatigiinnermilu ingerlaatsinik ilinniarsimasut annertussusaat

# Import
UDXISCPROE_raw1 <-
  statgl_url("UDXISCPROE", lang = language) %>% 
  statgl_fetch(
    ISCED11_level  = c(35, 50, 64, 65, 70),
    ISCED11_sektor = c("06"),
    .col_code      = TRUE
    ) %>% 
  as_tibble()

UDXISCPROE_raw2 <-
  statgl_url("UDXISCPROE", lang = language) %>% 
  statgl_fetch(
    ISCED11_level = "00",
    .col_code     = TRUE
    ) %>% 
  as_tibble()

# Transform
UDXISCPROE <-
  UDXISCPROE_raw1 %>% 
  rename(tæller = value) %>% 
  left_join(UDXISCPROE_raw2 %>% rename(nævner = value) %>% select(-1)) %>% 
  mutate(
    procent       = tæller / nævner * 100,
    ISCED11_level = ISCED11_level %>% str_remove("uddannelse"),
    Aar           = Aar %>% make_date()
    )

# Plot
UDXISCPROE %>% 
  ggplot(aes(
    x    = Aar,
    y    = procent,
    fill = ISCED11_level
  )) +
  geom_col() +
  scale_y_continuous(labels = scales::percent_format(
    scale        = 1, 
    big.mark     = ".",
    decimal.mark = ","
    )) +
  theme_statgl() + 
  scale_fill_statgl(reverse = TRUE, palette  = "spring") +
  guides(fill = guide_legend(nrow = 2, byrow = TRUE)) +
  labs(
    title    = sdg4$figs$fig17$title[language],
    subtitle = sdg4$figs$fig17$sub[language],
    x        = " ",
    y        = " ",
    fill     = NULL,
    caption  = sdg4$figs$fig17$cap[language]
  )

Kisitsisaataasivik

# Transform
UDXISCPROE <-
  UDXISCPROE_raw1 %>% 
  rename(tæller = value) %>% 
  left_join(UDXISCPROE_raw2 %>% rename(nævner = value) %>% select(-1)) %>% 
  mutate(
    procent              = tæller / nævner * 100,
    procent              = procent %>% round(1),
    ISCED11_level = ISCED11_level %>% str_remove("uddannelse")
    ) %>% 
  #arrange(desc(time)) %>% 
  filter(Aar >= year(Sys.time()) - 5) %>% 
  mutate(
    ISCED11_level = ISCED11_level %>% fct_inorder(),
    Aar           = Aar %>% fct_inorder()
  ) %>% 
  select(-c(2, 4:5)) %>% 
  spread(2, 3)
  
# Table
UDXISCPROE %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  add_footnote(
    sdg4$figs$fig17$foot[language],
    notation = "symbol")

	2020	2021	2022	2023
Inuussutissarsiornermik ilinniarneq	0,2	0,2	0,2	0,2
Ingerlariaqqiffiusumik ilinniarneq naatsoq	0,2	0,2	0,2	0,2
Bachelorinngorniarneq	0,0	0,0	0,0	0,0
Professionsbachelorinngorniarneq	0,0	0,0	0,0	0,0
Kandidatinngorniarneq	0,0	0,0	0,0	0,0
^* Inuusuttut inersimasullu 16-it 74-illu akornanni ukiullit paasissutissalerinermi attaveqatigiinnermilu ingerlaatsinik suliaqarnermi piginnaasallit annertussusaat procentinngorlugu.

Anguniagaq 4: Ilinniartitaaneq pitsaassusilik

Meeqqat atualinnginnermi ulluunerani neqeroorutiniittut, 3-niik 5-inut ukiullit

FN 4.2.2 Meeqqat atualinnginnermi ulluunerani neqeroorutiniittut (3-5-inik ukiullit)

Meeqqat atuarfianni alloriarfinni misilitsinnernit angusat

FN 4.1.1 Meeqqat atuarfianni 3.klassini aamma 7.klassini alloriarfinni misilitsinnerni inerniliillaqqissuseq

Meeqqat atuarfianni soraarummeernerit

GS Meeqqat atuarfianni inaarutaasumik misilitsinnernit karakteerit

Meeqqat atuarfianniit ilinniakkanut ingerlaqqinneq

GS Meeqqat atuarfianniit inuusuttut ilinniarfiinut ingerlaqqinnerit

Ilinniarnertuunngorniarnermiit ingerlariaqqiffiusumik ilinniarnermut ingerlaqqinneq

GS Ilinniarnertuunngorniarnermiit ingerlariaqqiffiusumik ilinniarnermut ingerlaqqinnerit

Ilinniakkamik ingerlatsitsut

GS Ilinniakkamik ingerlatsisut amerlassusaat ilinniakkap qaffasissusaa aamma nuna malillugit

FN 4.3.1 Ilinniakkamik ingerlatsisut amerlassusaat suiaassuseq malillugu

Ilinniarnerit naammassineqarsimasut

GS Ilinniarnerit naammassineqarsimasut amerlassusaat

35-t 39-llu akornanni ukiullit ilinniarsimassusaat

GS 35-t 39-llu akornanni ukiullit ilinniagaasa qaffasissusaat

Paasissutissalerinermi attaveqatigiinnermilu ingerlaatsit

FN 4.4.1 16-iniit 74-inut ukiullit akornanni paasissutissalerinermi attaveqatigiinnermilu ingerlaatsinik ilinniarsimasut annertussusaat