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	1554
C	Manufacturing	1218
C_HTC	High-technology manufacturing	1200
C_HTC_M	Medium high-technology manufacturing	1172
G-N	Services of the business economy	1150
C_LTC	Low-technology manufacturing	1106
C_LTC_M	Medium low-technology manufacturing	1054

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	4227
PC_TOT	Percentage of total	4227

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	460
2022	368
2021	520
2020	498
2019	574
2018	496
2017	574
2016	492
2015	538
2014	438
2013	514
2012	456
2011	524
2010	464
2009	496
2008	422
2007	282
2006	182
2005	156