Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/edat_lfs_9905.RData")$mtime)) %>%
print_table_conditional()| LAST_DOWNLOAD |
|---|
| 2024-10-08 |
Employees by educational attainment level, sex, age and occupation (%) - edat_lfs_9905
Data - Eurostat
Info
LAST_DOWNLOAD
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2024-11-22 |
Last
Code
edat_lfs_9905 %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2023 | 115038 |
unit
Code
edat_lfs_9905 %>%
left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| unit | Unit | Nobs |
|---|---|---|
| PC | Percentage | 1744366 |
isco08
Code
edat_lfs_9905 %>%
left_join(isco08, by = "isco08") %>%
group_by(isco08, Isco08) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| isco08 | Isco08 | Nobs |
|---|---|---|
| TOTAL | Total | 153744 |
| OC2 | Professionals | 153360 |
| OC3 | Technicians and associate professionals | 153360 |
| OC9 | Elementary occupations | 153360 |
| OC4 | Clerical support workers | 153356 |
| OC5 | Service and sales workers | 153356 |
| OC7 | Craft and related trades workers | 153166 |
| OC8 | Plant and machine operators and assemblers | 153026 |
| OC1 | Managers | 150518 |
| OC6 | Skilled agricultural, forestry and fishery workers | 149596 |
| OC0 | Armed forces occupations | 135460 |
| NRP | No response | 82064 |
sex
Code
edat_lfs_9905 %>%
left_join(sex, by = "sex") %>%
group_by(sex, Sex) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| sex | Sex | Nobs |
|---|---|---|
| T | Total | 586346 |
| M | Males | 585018 |
| F | Females | 573002 |
age
Code
edat_lfs_9905 %>%
left_join(age, by = "age") %>%
group_by(age, Age) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| age | Age | Nobs |
|---|---|---|
| Y25-34 | From 25 to 34 years | 122000 |
| Y15-24 | From 15 to 24 years | 119704 |
| Y18-24 | From 18 to 24 years | 119594 |
| Y20-24 | From 20 to 24 years | 119364 |
| Y15-74 | From 15 to 74 years | 105680 |
| Y15-64 | From 15 to 64 years | 105676 |
| Y15-69 | From 15 to 69 years | 105676 |
| Y18-74 | From 18 to 74 years | 105672 |
| Y18-64 | From 18 to 64 years | 105668 |
| Y18-69 | From 18 to 69 years | 105668 |
| Y25-74 | From 25 to 74 years | 105588 |
| Y25-64 | From 25 to 64 years | 105584 |
| Y25-69 | From 25 to 69 years | 105584 |
| Y25-54 | From 25 to 54 years | 105512 |
| Y30-54 | From 30 to 54 years | 105320 |
| Y55-74 | From 55 to 74 years | 102076 |
isced11
Code
load_data("eurostat/isced11_fr.RData")
edat_lfs_9905 %>%
left_join(isced11, by = "isced11") %>%
group_by(isced11, Isced11) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| isced11 | Isced11 | Nobs |
|---|---|---|
| ED0-2 | Inférieur à l'enseignement primaire, enseignement primaire et premier cycle de l'enseignement secondaire (niveaux 0-2) | 390131 |
| ED3-8 | Deuxième cycle de l'enseignement secondaire, enseignement post-secondaire non-supérieur et enseignement supérieur (niveaux 3-8) | 390131 |
| ED3_4 | Deuxième cycle de l'enseignement secondaire et enseignement post-secondaire non-supérieur (niveaux 3 et 4) | 390131 |
| ED5-8 | Enseignement supérieur (niveaux 5-8) | 390131 |
| ED3_4GEN | Deuxième cycle de l'enseignement secondaire et enseignement post-secondaire non-supérieur (niveaux 3 et 4) - général | 91921 |
| ED3_4VOC | Deuxième cycle de l'enseignement secondaire et enseignement post-secondaire non-supérieur (niveaux 3 et 4) - professionnel | 91921 |
geo
Code
edat_lfs_9905 %>%
left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}time
Code
edat_lfs_9905 %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2023 | 115038 |
| 2022 | 114846 |
| 2021 | 114876 |
| 2020 | 87828 |
| 2019 | 90556 |
| 2018 | 90642 |
| 2017 | 90386 |
| 2016 | 90360 |
| 2015 | 90330 |
| 2014 | 90344 |
| 2013 | 80756 |
| 2012 | 79004 |
| 2011 | 79080 |
| 2010 | 78868 |
| 2009 | 76672 |
| 2008 | 76356 |
| 2007 | 76712 |
| 2006 | 76944 |
| 2005 | 73072 |
| 2004 | 71696 |
France, EU, Italy, Germany, Spain, Netherlands
15-74, peu d’éducation
Code
edat_lfs_9905 %>%
filter(isced11 == "ED0-2",
age == "Y15-74",
geo %in% c("EA19", "DE", "ES", "FR", "IT"),
isco08 == "TOTAL",
sex == "T") %>%
select_if(~ n_distinct(.) > 1) %>%
year_to_date() %>%
filter(date >= as.Date("1995-01-01")) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(color = ifelse(geo == "EA19", color2, color)) %>%
mutate(color = ifelse(geo == "ES", color2, color)) %>%
mutate(values = values / 100) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("% Employés du 1er cycle de l'enseignement secondaire") +
scale_color_identity() + add_5flags +
scale_x_date(breaks = seq(1960, 2026, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
labels = percent_format(accuracy = 1))
Education moyenne
Code
edat_lfs_9905 %>%
filter(isced11 == "ED3_4",
age == "Y15-74",
isco08 == "TOTAL",
geo %in% c("EA19", "DE", "ES", "FR", "IT"),
sex == "T") %>%
year_to_date() %>%
filter(date >= as.Date("1995-01-01")) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(color = ifelse(geo == "EA19", color2, color)) %>%
mutate(color = ifelse(geo == "ES", color2, color)) %>%
mutate(values = values / 100) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("% Employés des niveaux 3 et 4") +
scale_color_identity() + add_5flags +
scale_x_date(breaks = seq(1960, 2026, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
labels = percent_format(accuracy = 1))
Enseignement supérieur
Code
edat_lfs_9905 %>%
filter(isced11 == "ED5-8",
age == "Y15-74",
geo %in% c("EA19", "DE", "ES", "FR", "IT"),
isco08 == "TOTAL",
sex == "T") %>%
year_to_date() %>%
filter(date >= as.Date("1995-01-01")) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(color = ifelse(geo == "EA19", color2, color)) %>%
mutate(color = ifelse(geo == "ES", color2, color)) %>%
mutate(values = values / 100) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("% Employés des niveaux 5 à 8") +
scale_color_identity() + add_5flags +
scale_x_date(breaks = seq(1960, 2026, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
labels = percent_format(accuracy = 1))