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 5048
D2 Second decile 5048
D3 Third decile 5048
D4 Fourth decile 5048
D5 Fifth decile 5048
D6 Sixth decile 5048
D7 Seventh decile 5048
D8 Eighth decile 5048
D9 Ninth decile 5048
Q1 First quartile 5048
Q2 Second quartile 5048
Q3 Third quartile 5048
QU1 First quintile 5048
QU2 Second quintile 5048
QU3 Third quintile 5048
QU4 Fourth quintile 5048
P1 First percentile 4452
P5 Fifth percentile 4452
P95 Ninety-fifth percentile 4452
P96 Ninety-sixth percentile 4452
P97 Ninety-seventh percentile 4452
P98 Ninety-eighth percentile 4452
P99 Ninety-ninth percentile 4452
P3 Third percentile 4446
P4 Fourth percentile 4446
P2 Second percentile 4434
D10 Tenth decile 2524
Q4 Fourth quartile 2524
QU5 Fifth quintile 2524
P100 Hundredth percentile 2226

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 72427
TC Top cut-off point 62629

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))