%>%
icw_sr_03 left_join(quantile, by = "quantile") %>%
group_by(quantile, Quantile) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
quantile | Quantile | Nobs |
---|---|---|
QU1 | First quintile | 58 |
QU2 | Second quintile | 58 |
QU3 | Third quintile | 58 |
QU4 | Fourth quintile | 58 |
QU5 | Fifth quintile | 58 |
TOTAL | Total | 58 |
%>%
icw_sr_03 left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
unit | Unit | Nobs |
---|---|---|
PC_DI | Percentage of disposable income | 348 |
%>%
icw_sr_03 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="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
%>%
icw_sr_03 group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
time | Nobs |
---|---|
2015 | 186 |
2010 | 162 |
%>%
icw_sr_03 filter(time == "2010") %>%
select(quantile, geo, values) %>%
left_join(geo, by = "geo") %>%
spread(quantile, values) %>%
select(geo, Geo, TOTAL, everything()) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
arrange(-`TOTAL`) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
%>%
icw_sr_03 filter(time == "2015") %>%
select(quantile, geo, values) %>%
left_join(geo, by = "geo") %>%
spread(quantile, values) %>%
select(geo, Geo, TOTAL, everything()) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
arrange(-`TOTAL`) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
%>%
icw_sr_03 filter(time == "2015",
%in% c("SE", "FR", "DE")) %>%
geo mutate(quantile = substr(quantile, 3, 3) %>% as.numeric) %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
+ geom_line(aes(x = quantile, y = values/100, color = color)) +
ggplot scale_color_identity() + theme_minimal() +
geom_image(data = . %>%
filter(quantile == 3) %>%
mutate(image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Geo)), ".png")),
aes(x = quantile, y = values/100, image = image), asp = 1.5) +
xlab("Quintile") + ylab("Median saving rate by income quintile") +
scale_y_continuous(breaks = 0.01*seq(-30, 50, 5),
labels = percent_format(accuracy = 1)) +
scale_x_continuous(breaks = seq(0, 5, 1))
%>%
icw_sr_03 filter(time == "2015",
%in% c("UK", "ES", "PT")) %>%
geo mutate(quantile = substr(quantile, 3, 3) %>% as.numeric) %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
+ geom_line(aes(x = quantile, y = values/100, color = color)) +
ggplot scale_color_identity() + theme_minimal() +
geom_image(data = . %>%
filter(quantile == 5) %>%
mutate(image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Geo)), ".png")),
aes(x = quantile, y = values/100, image = image), asp = 1.5) +
xlab("Quintile") + ylab("Median saving rate by income quintile") +
scale_y_continuous(breaks = 0.01*seq(-30, 50, 5),
labels = percent_format(accuracy = 1)) +
scale_x_continuous(breaks = seq(0, 5, 1))