HICP - administered Prices (composition) - prc_hicp_apc

Data - Eurostat

Author

François Geerolf

statinfo

Code 
prc_hicp_apc %>%
  left_join(statinfo, by = "statinfo") %>%
  group_by(statinfo, Statinfo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
statinfo Statinfo Nobs
STA Status 407247
WT Weight 398142

coicop

Code 
prc_hicp_apc %>%
  left_join(coicop, by = "coicop") %>%
  group_by(coicop, Coicop) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

administr

Code 
prc_hicp_apc %>%
  left_join(administr, by = "administr") %>%
  group_by(administr, Administr) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
administr Administr Nobs
ADM Administered 268463
ADM_F Fully administered 268463
ADM_M Mainly administered 268463

geo

Code 
prc_hicp_apc %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Geo))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

time

Code 
prc_hicp_apc %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()
time Nobs
2025 57540
2024 57489
2023 57489
2022 57483
2021 57471
2020 59964
2019 60180
2018 60150
2017 60150
2016 18096
2015 18036
2014 17418
2013 17418
2012 17418
2011 17418
2010 17418
2009 17418
2008 17418
2007 17418
2006 17418
2005 17139
2004 16860
2003 16860
2002 16860
2001 16860

2022

France

Code 
prc_hicp_apc %>%
  filter(time == "2022",
         geo == "FR") %>%
  select_if(~n_distinct(.) > 1) %>%
  filter(values != 0) %>%
  left_join(coicop, by = "coicop") %>%
  left_join(administr, by = "administr") %>%
  spread(statinfo, values)
# # A tibble: 60 × 6
#    coicop  administr Coicop                 Administr             STA    WT
#    <chr>   <chr>     <chr>                  <chr>               <dbl> <dbl>
#  1 CP02201 ADM       Cigarettes             Administered            1 20.6 
#  2 CP02201 ADM_M     Cigarettes             Mainly administered     1 20.6 
#  3 CP02202 ADM       Cigars                 Administered            1  0.71
#  4 CP02202 ADM_M     Cigars                 Mainly administered     1  0.71
#  5 CP02203 ADM       Other tobacco products Administered            1  3.04
#  6 CP02203 ADM_M     Other tobacco products Mainly administered     1  3.04
#  7 CP0441  ADM       Water supply           Administered            1  4.45
#  8 CP0441  ADM_F     Water supply           Fully administered      1  4.45
#  9 CP0442  ADM       Refuse collection      Administered            1  4.25
# 10 CP0442  ADM_F     Refuse collection      Fully administered      1  4.25
# # ℹ 50 more rows

Germany

Code 
prc_hicp_apc %>%
  filter(time == "2022",
         geo == "DE") %>%
  select_if(~n_distinct(.) > 1) %>%
  filter(values != 0) %>%
  left_join(coicop, by = "coicop") %>%
  left_join(administr, by = "administr") %>%
  spread(statinfo, values)
# # A tibble: 60 × 6
#    coicop  administr Coicop                             Administr      STA    WT
#    <chr>   <chr>     <chr>                              <chr>        <dbl> <dbl>
#  1 CP0441  ADM       Water supply                       Administered     1  8.33
#  2 CP0441  ADM_F     Water supply                       Fully admin…     1  8.33
#  3 CP0442  ADM       Refuse collection                  Administered     1  6.95
#  4 CP0442  ADM_F     Refuse collection                  Fully admin…     1  6.95
#  5 CP0443  ADM       Sewerage collection                Administered     1  6.91
#  6 CP0443  ADM_F     Sewerage collection                Fully admin…     1  6.91
#  7 CP04449 ADM       Other services related to dwelling Administered     1  2.91
#  8 CP04449 ADM_F     Other services related to dwelling Fully admin…     1  2.91
#  9 CP0611  ADM       Pharmaceutical products            Administered     1 12.3 
# 10 CP0611  ADM_M     Pharmaceutical products            Mainly admi…     1 12.3 
# # ℹ 50 more rows