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 4752
D2 Second decile 4752
D3 Third decile 4752
D4 Fourth decile 4752
D5 Fifth decile 4752
D6 Sixth decile 4752
D7 Seventh decile 4752
D8 Eighth decile 4752
D9 Ninth decile 4752
Q1 First quartile 4752
Q2 Second quartile 4752
Q3 Third quartile 4752
QU1 First quintile 4752
QU2 Second quintile 4752
QU3 Third quintile 4752
QU4 Fourth quintile 4752
P1 First percentile 4156
P4 Fourth percentile 4156
P5 Fifth percentile 4156
P95 Ninety-fifth percentile 4156
P96 Ninety-sixth percentile 4156
P97 Ninety-seventh percentile 4156
P98 Ninety-eighth percentile 4156
P99 Ninety-ninth percentile 4156
P3 Third percentile 4150
P2 Second percentile 4138
D10 Tenth decile 2376
Q4 Fourth quartile 2376
QU5 Fifth quintile 2376
P100 Hundredth percentile 2078

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 67990
TC Top cut-off point 58784

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))