Business enterprise R&D expenditure in high-tech sectors - NACE Rev. 2 - htec_sti_exp2

Data - Eurostat

Author

nace_r2

Code

htec_sti_exp2 %>%
  left_join(nace_r2, by = "nace_r2") %>%
  group_by(nace_r2, Nace_r2) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

nace_r2	Nace_r2	Nobs
TOTAL	Total - all NACE activities	1552
G-N	Services of the business economy	1090
C	Manufacturing	1002
C_HTC	High-technology manufacturing	992
C_HTC_M	Medium high-technology manufacturing	972
C_LTC	Low-technology manufacturing	928
C_LTC_M	Medium low-technology manufacturing	872

unit

Code

htec_sti_exp2 %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

unit	Unit	Nobs
MIO_EUR	Million euro	3704
PC_TOT	Percentage of total	3704

geo

Code

htec_sti_exp2 %>%
  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 .}

time

Code

htec_sti_exp2 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()

time	Nobs
2023	122
2022	328
2021	438
2020	490
2019	534
2018	466
2017	524
2016	452
2015	516
2014	410
2013	468
2012	428
2011	446
2010	426
2009	436
2008	362
2007	244
2006	172
2005	146