HICP - administered Prices (composition) - prc_hicp_apc

Data - Eurostat

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 361962
WT Weight 355467

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 239143
ADM_F Fully administered 239143
ADM_M Mainly administered 239143

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
2024 53949
2023 53949
2022 53943
2021 53931
2020 56424
2019 56640
2018 56610
2017 56610
2016 17856
2015 17856
2014 17298
2013 17298
2012 17298
2011 17298
2010 17298
2009 17298
2008 17298
2007 17298
2006 17298
2005 17019
2004 16740
2003 16740
2002 16740
2001 16740

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