Code
lfst_r_lfe2emprt %>%
left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| unit | Unit | Nobs |
|---|---|---|
| PC | Percentage | 420480 |
Data - Eurostat
lfst_r_lfe2emprt %>%
left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| unit | Unit | Nobs |
|---|---|---|
| PC | Percentage | 420480 |
lfst_r_lfe2emprt %>%
left_join(sex, by = "sex") %>%
group_by(sex, Sex) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| sex | Sex | Nobs |
|---|---|---|
| F | Females | 140160 |
| M | Males | 140160 |
| T | Total | 140160 |
lfst_r_lfe2emprt %>%
left_join(age, by = "age") %>%
group_by(age, Age) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| age | Age | Nobs |
|---|---|---|
| Y15-24 | From 15 to 24 years | 35040 |
| Y15-64 | From 15 to 64 years | 35040 |
| Y15-74 | From 15 to 74 years | 35040 |
| Y20-64 | From 20 to 64 years | 35040 |
| Y25-34 | From 25 to 34 years | 35040 |
| Y25-64 | From 25 to 64 years | 35040 |
| Y35-44 | From 35 to 44 years | 35040 |
| Y45-54 | From 45 to 54 years | 35040 |
| Y55-64 | From 55 to 64 years | 35040 |
| Y_GE15 | 15 years or over | 35040 |
| Y_GE25 | 25 years or over | 35040 |
| Y_GE65 | 65 years or over | 35040 |
lfst_r_lfe2emprt %>%
left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}lfst_r_lfe2emprt %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}lfst_r_lfe2emprt %>%
filter(unit == "PC",
sex == "T",
age == "Y_GE15",
nchar(geo) == 4,
time == "2018") %>%
right_join(europe_NUTS2, by = "geo") %>%
filter(long >= -13.5, lat >= 33) %>%
ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(20, 100, 5),
values = c(0, 0.1, 0.3, 0.4, 0.5, 0.6, 1)) +
theme_void() + theme(legend.position = c(0.15, 0.85)) +
labs(fill = "Employment 15+ (%)")
lfst_r_lfe2emprt %>%
filter(unit == "PC",
sex == "T",
age == "Y_GE25",
nchar(geo) == 4,
time == "2018") %>%
right_join(europe_NUTS2, by = "geo") %>%
filter(long >= -13.5, lat >= 33) %>%
ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(20, 100, 5),
values = c(0, 0.1, 0.3, 0.4, 0.5, 0.6, 1)) +
theme_void() + theme(legend.position = c(0.15, 0.85)) +
labs(fill = "Employment 25+ (%)")
lfst_r_lfe2emprt %>%
filter(unit == "PC",
sex == "T",
age == "Y15-64",
nchar(geo) == 4,
time == "2018") %>%
right_join(europe_NUTS2, by = "geo") %>%
filter(long >= -13.5, lat >= 33) %>%
ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(20, 100, 10),
values = c(0, 0.1, 0.3, 0.4, 0.6, 0.8, 1)) +
theme_void() + theme(legend.position = c(0.15, 0.85)) +
labs(fill = "Employment 15-64 (%)")
lfst_r_lfe2emprt %>%
filter(unit == "PC",
sex == "T",
age == "Y25-64",
nchar(geo) == 4,
time == "2018") %>%
right_join(europe_NUTS2, by = "geo") %>%
filter(long >= -13.5, lat >= 33) %>%
ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
geom_polygon() + coord_map() +
scale_fill_viridis_c(na.value = "white",
labels = scales::percent_format(accuracy = 1),
breaks = 0.01*seq(20, 100, 10),
values = c(0, 0.1, 0.3, 0.4, 0.6, 0.8, 1)) +
theme_void() + theme(legend.position = c(0.15, 0.85)) +
labs(fill = "Employment 25-64 (%)")