Mean and median economic resources of households by income, consumption and wealth quantiles - experimental statistics - icw_res_02

Data - Eurostat

Info

LAST_DOWNLOAD

Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/icw_res_02.RData")$mtime)) %>%
  print_table_conditional()
LAST_DOWNLOAD
2024-11-21

LAST_COMPILE

LAST_COMPILE
2024-11-22

Last

Code
icw_res_02 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2020 111940

quant_inc

Code
icw_res_02 %>%
  left_join(quant_inc, by = "quant_inc") %>%
  group_by(quant_inc, Quant_inc) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
quant_inc Quant_inc Nobs
D1 First decile 34688
D10 Tenth decile 34326
QU1 First quintile 34914
QU2 Second quintile 34920
QU3 Third quintile 34896
QU4 Fourth quintile 34856
QU5 Fifth quintile 34752
TOTAL Total 34944

quant_expn

Code
icw_res_02 %>%
  left_join(quant_expn, by = "quant_expn") %>%
  group_by(quant_expn, Quant_expn) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
quant_expn Quant_expn Nobs
D1 First decile 34046
D10 Tenth decile 34736
QU1 First quintile 34842
QU2 Second quintile 34938
QU3 Third quintile 34944
QU4 Fourth quintile 34932
QU5 Fifth quintile 34914
TOTAL Total 34944

quant_wlth

Code
icw_res_02 %>%
  left_join(quant_wlth, by = "quant_wlth") %>%
  group_by(quant_wlth, Quant_wlth) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
quant_wlth Quant_wlth Nobs
D1 First decile 33414
D10 Tenth decile 33588
QU1 First quintile 33564
QU2 Second quintile 33678
QU3 Third quintile 33678
QU4 Fourth quintile 33684
QU5 Fifth quintile 33702
TOTAL Total 42988

statinfo

Code
icw_res_02 %>%
  left_join(statinfo, by = "statinfo") %>%
  group_by(statinfo, Statinfo) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
statinfo Statinfo Nobs
AVG Average 139148
MED Median 139148

indic_il

Code
icw_res_02 %>%
  left_join(indic_il, by = "indic_il") %>%
  group_by(indic_il, Indic_il) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}
indic_il Indic_il Nobs
EXPN_CONS Consumption expenditure 94302
INC_DISP Disposable income 94302
WLTH_NET Net wealth 89692

geo

Code
icw_res_02 %>%
  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
icw_res_02 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
time Nobs
2015 120388
2020 111940
2010 45968

Example

France

Code
icw_res_02 %>%
  filter(geo == "FR",
         quant_inc %in% c("QU1", "QU2", "QU3", "QU4", "QU5"),
         quant_expn == "TOTAL",
         quant_wlth == "TOTAL") %>%
  select_if(~ n_distinct(.) > 1) %>%
  spread(indic_il, values) %>%
  {if (is_html_output()) print_table(.) else .}
quant_inc statinfo unit time EXPN_CONS INC_DISP WLTH_NET
QU1 AVG EUR 2010 16349.0 15709.2 104542.9
QU1 AVG EUR 2015 17261.8 18570.2 103501.5
QU1 AVG EUR 2020 17155.5 16227.7 125314.4
QU1 AVG PPS 2015 16495.1 17745.4 98904.4
QU1 AVG PPS 2020 15191.1 14369.5 110965.4
QU1 MED EUR 2010 13278.0 13508.2 12659.0
QU1 MED EUR 2015 14608.3 16095.3 16930.7
QU1 MED EUR 2020 13831.4 14095.3 16976.7
QU1 MED PPS 2015 13959.4 15380.4 16178.7
QU1 MED PPS 2020 12247.6 12481.3 15032.8
QU2 AVG EUR 2010 21273.2 24177.4 139605.7
QU2 AVG EUR 2015 20914.6 26617.5 150478.1
QU2 AVG EUR 2020 21248.0 25658.4 157700.6
QU2 AVG PPS 2015 19985.6 25435.3 143794.5
QU2 AVG PPS 2020 18815.0 22720.4 139643.3
QU2 MED EUR 2010 18332.4 22918.6 59098.4
QU2 MED EUR 2015 17874.3 24983.8 60167.5
QU2 MED EUR 2020 18174.4 23452.8 57230.4
QU2 MED PPS 2015 17080.4 23874.1 57495.1
QU2 MED PPS 2020 16093.3 20767.4 50677.3
QU3 AVG EUR 2010 24856.3 31505.8 170487.6
QU3 AVG EUR 2015 24546.4 33734.1 188473.3
QU3 AVG EUR 2020 25140.7 33103.6 210922.8
QU3 AVG PPS 2015 23456.2 32235.8 180102.2
QU3 AVG PPS 2020 22262.0 29313.1 186771.4
QU3 MED EUR 2010 21965.0 30146.9 119093.0
QU3 MED EUR 2015 21362.7 32584.7 123315.3
QU3 MED EUR 2020 21708.1 32107.5 126255.0
QU3 MED PPS 2015 20413.8 31137.4 117838.2
QU3 MED PPS 2020 19222.4 28431.0 111798.4
QU4 AVG EUR 2010 28530.1 40250.8 254204.9
QU4 AVG EUR 2015 29863.0 44273.2 273659.4
QU4 AVG EUR 2020 30621.6 43707.1 290210.8
QU4 AVG PPS 2015 28536.6 42306.8 261504.6
QU4 AVG PPS 2020 27115.3 38702.5 256980.6
QU4 MED EUR 2010 25459.6 38805.2 192423.6
QU4 MED EUR 2015 26107.8 42374.1 182012.2
QU4 MED EUR 2020 26598.4 41844.8 205632.3
QU4 MED PPS 2015 24948.2 40492.0 173928.0
QU4 MED PPS 2020 23552.8 37053.4 182086.7
QU5 AVG EUR 2010 39029.7 73896.1 733967.1
QU5 AVG EUR 2015 39371.2 75513.0 1093215.2
QU5 AVG EUR 2020 41776.0 77831.9 789451.1
QU5 AVG PPS 2015 37622.5 72159.1 1044659.4
QU5 AVG PPS 2020 36992.5 68919.9 699056.2
QU5 MED EUR 2010 33504.5 61535.0 383827.7
QU5 MED EUR 2015 33283.6 64269.3 375558.3
QU5 MED EUR 2020 35724.8 66854.6 428635.6
QU5 MED PPS 2015 31805.3 61414.7 358877.7
QU5 MED PPS 2020 31634.2 59199.5 379555.3

Italy

Code
icw_res_02 %>%
  filter(geo == "DE",
         quant_inc %in% c("QU1", "QU2", "QU3", "QU4", "QU5"),
         quant_expn == "TOTAL",
         quant_wlth == "TOTAL") %>%
  select_if(~ n_distinct(.) > 1) %>%
  spread(indic_il, values) %>%
  {if (is_html_output()) print_table(.) else .}
quant_inc statinfo unit time EXPN_CONS INC_DISP WLTH_NET
QU1 AVG EUR 2010 12862.9 10542.7 111939.0
QU1 AVG EUR 2015 13591.0 9865.1 96540.6
QU1 AVG EUR 2020 15383.4 12472.2 113415.7
QU1 AVG PPS 2015 13549.0 9834.6 96242.3
QU1 AVG PPS 2020 14390.7 11667.4 106097.1
QU1 MED EUR 2010 11223.8 9631.6 11941.3
QU1 MED EUR 2015 11580.7 9655.9 11203.0
QU1 MED EUR 2020 13039.9 11543.4 9317.0
QU1 MED PPS 2015 11544.9 9626.1 11168.4
QU1 MED PPS 2020 12198.5 10798.5 8715.8
QU2 AVG EUR 2010 19480.0 20538.7 123877.9
QU2 AVG EUR 2015 20291.1 20860.5 123712.3
QU2 AVG EUR 2020 23108.2 25250.4 193097.3
QU2 AVG PPS 2015 20228.4 20796.1 123330.0
QU2 AVG PPS 2020 21617.0 23621.1 180636.9
QU2 MED EUR 2010 17435.7 19229.1 32461.3
QU2 MED EUR 2015 17986.6 19644.2 30412.0
QU2 MED EUR 2020 20577.0 23964.2 30584.3
QU2 MED PPS 2015 17931.0 19583.5 30318.0
QU2 MED PPS 2020 19249.2 22417.9 28610.8
QU3 AVG EUR 2010 24625.8 28201.8 175814.8
QU3 AVG EUR 2015 25268.5 29150.6 162172.4
QU3 AVG EUR 2020 28776.1 34287.9 307055.7
QU3 AVG PPS 2015 25190.5 29060.5 161671.2
QU3 AVG PPS 2020 26919.2 32075.4 287241.8
QU3 MED EUR 2010 22233.6 26867.1 73760.4
QU3 MED EUR 2015 22924.5 27980.8 63126.5
QU3 MED EUR 2020 25615.6 32754.5 97499.7
QU3 MED PPS 2015 22853.6 27894.3 62931.4
QU3 MED PPS 2020 23962.7 30640.9 91208.1
QU4 AVG EUR 2010 29524.1 36117.3 249440.4
QU4 AVG EUR 2015 30262.0 38534.7 249610.6
QU4 AVG EUR 2020 34378.0 44182.9 401171.5
QU4 AVG PPS 2015 30168.5 38415.6 248839.2
QU4 AVG PPS 2020 32159.6 41331.8 375284.4
QU4 MED EUR 2010 26356.2 34771.4 109685.0
QU4 MED EUR 2015 27368.0 37252.7 112553.3
QU4 MED EUR 2020 30429.0 42617.4 224852.7
QU4 MED PPS 2015 27283.4 37137.6 112205.5
QU4 MED PPS 2020 28465.5 39867.3 210343.2
QU5 AVG EUR 2010 41594.2 59153.8 499576.0
QU5 AVG EUR 2015 41385.0 64391.2 489193.8
QU5 AVG EUR 2020 46315.4 72677.9 716382.1
QU5 AVG PPS 2015 41257.1 64192.2 487681.9
QU5 AVG PPS 2020 43326.7 67988.1 670154.8
QU5 MED EUR 2010 36450.5 52325.3 225191.3
QU5 MED EUR 2015 36046.2 55952.9 231288.3
QU5 MED EUR 2020 39937.7 64328.7 371617.3
QU5 MED PPS 2015 35934.8 55779.9 230573.6
QU5 MED PPS 2020 37360.6 60177.6 347637.3