Share of housing costs in disposable household income, by type of household and income group - EU-SILC survey - ilc_mded01

Data - Eurostat

Author

hhtyp

Code

ilc_mded01 %>%
  left_join(hhtyp, by = "hhtyp") %>%
  group_by(hhtyp, Hhtyp) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

incgrp

Code

ilc_mded01 %>%
  left_join(incgrp, by = "incgrp") %>%
  group_by(incgrp, Incgrp) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

incgrp	Incgrp	Nobs
A_MD60	Above 60% of median equivalised income	12563
B_MD60	Below 60% of median equivalised income	12563
TOTAL	Total	12563

unit

Code

ilc_mded01 %>%
  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	37689

geo

Code

ilc_mded01 %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

time

Code

ilc_mded01 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Table

Javascript

Code

ilc_mded01 %>%
  filter(hhtyp == "TOTAL",
         time %in% c("2018")) %>%
  left_join(geo, by = "geo") %>%
  select(geo, Geo, incgrp, values) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  spread(incgrp, values) %>%
  arrange(-TOTAL) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}