Unemployment distribution by duration (by sex and age) (%) - UNE_TUNE_SEX_AGE_DUR_DT_A

Data - ILO

Author

classif1

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  left_join(classif1, by = "classif1") %>%
  group_by(classif1, Classif1) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

classif1	Classif1	Nobs
AGE_YTHADULT_YGE15	Age (Youth, adults): 15+	61939
AGE_AGGREGATE_TOTAL	Age (Aggregate bands): Total	58988
AGE_YTHADULT_YGE25	Age (Youth, adults): 25+	57506
AGE_AGGREGATE_Y25-54	Age (Aggregate bands): 25-54	57285
AGE_AGGREGATE_Y15-24	Age (Aggregate bands): 15-24	54221
AGE_YTHADULT_Y15-24	Age (Youth, adults): 15-24	53422
AGE_10YRBANDS_TOTAL	Age (10-year bands): Total	51810
AGE_YTHADULT_Y15-64	Age (Youth, adults): 15-64	49083
AGE_10YRBANDS_Y15-24	Age (10-year bands): 15-24	47437
AGE_10YRBANDS_Y25-34	Age (10-year bands): 25-34	47286
AGE_10YRBANDS_Y35-44	Age (10-year bands): 35-44	44888
AGE_10YRBANDS_Y45-54	Age (10-year bands): 45-54	42083
AGE_AGGREGATE_Y55-64	Age (Aggregate bands): 55-64	41006
AGE_10YRBANDS_Y55-64	Age (10-year bands): 55-64	35372
AGE_10YRBANDS_YGE65	Age (10-year bands): 65+	14303
AGE_AGGREGATE_YGE65	Age (Aggregate bands): 65+	12387

classif2

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  left_join(classif2, by = "classif2") %>%
  group_by(classif2, Classif2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

classif2	Classif2	Nobs
DUR_AGGREGATE_TOTAL	Duration (Aggregate): Total	76940
DUR_AGGREGATE_MLT6	Duration (Aggregate): Less than 6 months	72181
DUR_DETAILS_TOTAL	Duration (Detailed): Total	69880
DUR_AGGREGATE_MGE12	Duration (Aggregate): 12 months or more	68192
DUR_AGGREGATE_MGE6LT12	Duration (Aggregate): 6 months to less than 12 months	64692
DUR_DETAILS_MGE3LT6	Duration (Detailed): 3 months to less than 6 months	59853
DUR_DETAILS_MGE1LT3	Duration (Detailed): 1 month to less than 3 months	59726
DUR_DETAILS_MGE6LT12	Duration (Detailed): 6 months to less than 12 months	58622
DUR_DETAILS_MGE12LT24	Duration (Detailed): 12 months to less than 24 months	57083
DUR_DETAILS_MLT1	Duration (Detailed): Less than 1 month	51420
DUR_DETAILS_MGE24	Duration (Detailed): 24 months or more	44697
DUR_AGGREGATE_X	Duration (Aggregate): Not elsewhere classified	23203
DUR_DETAILS_X	Duration (Detailed): Not elsewhere classified	21574
DUR_DETAILS_MLT3	Duration (Detailed): Less than 3 months	942
DUR_AGGREGATE_MLT12	Duration (Aggregate): Less than 12 months	11

source

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  left_join(source, by = "source") %>%
  group_by(source, Source) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

sex

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  left_join(sex, by = "sex") %>%
  group_by(sex, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

sex	Sex	Nobs
SEX_T	Sex: Total	256448
SEX_M	Sex: Male	241669
SEX_F	Sex: Female	230899

ref_area

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  left_join(ref_area, by = "ref_area") %>%
  group_by(ref_area, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Ref_area)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

AGE_YTHADULT_YGE15

Table

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  filter(classif1 == "AGE_YTHADULT_YGE15",
         sex == "SEX_T") %>%
  arrange(ref_area, time) %>%
  left_join(ref_area, by = "ref_area") %>%
  group_by(ref_area, Ref_area) %>%
  summarise(year1 = first(time),
            value1 = first(obs_value) %>% round() %>% paste0(" %"),
            year2 = last(time),
            value2 = last(obs_value) %>% round %>% paste0(" %")) %>%
  arrange(year1) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Ref_area)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

AGE_AGGREGATE_TOTAL

Table

Code

UNE_TUNE_SEX_AGE_DUR_DT_A %>%
  filter(classif1 == "AGE_AGGREGATE_TOTAL",
         sex == "SEX_T") %>%
  arrange(ref_area, time) %>%
  left_join(ref_area, by = "ref_area") %>%
  group_by(ref_area, Ref_area) %>%
  summarise(year1 = first(time),
            value1 = first(obs_value) %>% round() %>% paste0(" %"),
            year2 = last(time),
            value2 = last(obs_value) %>% round %>% paste0(" %")) %>%
  arrange(year1) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Ref_area)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}