Distribution of income by quantiles - EU-SILC and ECHP surveys - ilc_di01

Data - Eurostat

Author

François Geerolf

quantile

Code 
ilc_di01 %>%
  left_join(quantile, by = "quantile") %>%
  group_by(quantile, Quantile) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
quantile Quantile Nobs
D1 First decile 5120
D2 Second decile 5120
D3 Third decile 5120
D4 Fourth decile 5120
D5 Fifth decile 5120
D6 Sixth decile 5120
D7 Seventh decile 5120
D8 Eighth decile 5120
D9 Ninth decile 5120
Q1 First quartile 5120
Q2 Second quartile 5120
Q3 Third quartile 5120
QU1 First quintile 5120
QU2 Second quintile 5120
QU3 Third quintile 5120
QU4 Fourth quintile 5120
P1 First percentile 4524
P5 Fifth percentile 4524
P95 Ninety-fifth percentile 4524
P96 Ninety-sixth percentile 4524
P97 Ninety-seventh percentile 4524
P98 Ninety-eighth percentile 4524
P99 Ninety-ninth percentile 4524
P3 Third percentile 4518
P4 Fourth percentile 4518
P2 Second percentile 4506
D10 Tenth decile 2560
Q4 Fourth quartile 2560
QU5 Fifth quintile 2560
P100 Hundredth percentile 2262

indic_il

Code 
ilc_di01 %>%
  left_join(indic_il, by = "indic_il") %>%
  group_by(indic_il, Indic_il) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
indic_il Indic_il Nobs
SHARE Share of national equivalised income 73507
TC Top cut-off point 63565

geo

Code 
ilc_di01 %>%
  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 .}

D10 / D1

Code 
ilc_di01 %>%
  filter(quantile %in% c("D1", "D10"),
         geo %in% c("FR", "DE"),
         currency == "EUR",
         indic_il == "SHARE") %>%
  time_to_date %>%
  left_join(geo, by = "geo") %>%
  arrange(date, quantile, geo, values) %>%
  spread(quantile, values) %>%
  mutate(values = D10/D1) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_2flags + theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
               labels = date_format("%y")) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(0, 20, 1))

D9 / D1

Code 
ilc_di01 %>%
  filter(quantile %in% c("D1", "D9"),
         geo %in% c("FR", "DE"),
         currency == "EUR",
         indic_il == "SHARE") %>%
  time_to_date %>%
  left_join(geo, by = "geo") %>%
  arrange(date, quantile, geo, values) %>%
  spread(quantile, values) %>%
  mutate(values = D9/D1) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_2flags + theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
               labels = date_format("%y")) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(0, 20, 1))