~/data/eurostat/

Info

LAST_DOWNLOAD

tibble(dataset = c("ext_st_ea19sitc", "ext_st_eu27_2020sitc", "namq_10_a10")) %>%
  mutate(LAST_DOWNLOAD = as.Date(file.info(paste0("~/Dropbox/website/data/eurostat/", dataset, ".RData"))$mtime)) %>%
  mutate(html = paste0("[html](https://fgeerolf.com/data/eurostat/", dataset, '.html)')) %>%
  print_table_conditional()
dataset LAST_DOWNLOAD html
ext_st_ea19sitc 2023-02-14 html
ext_st_eu27_2020sitc 2023-04-16 html
namq_10_a10 2023-04-16 html

LAST_COMPILE

LAST_COMPILE
2023-04-16

Last

ext_st_ea19sitc %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2022M11 9747

stk_flow

ext_st_ea19sitc %>%
  left_join(stk_flow, by = "stk_flow") %>%
  group_by(stk_flow, Stk_flow) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
stk_flow Stk_flow Nobs
EXP Exports 2957259
IMP Imports 2925662
BAL_RT Balance for values / Ratio for indices 1389764

indic_et

ext_st_ea19sitc %>%
  left_join(indic_et, by = "indic_et") %>%
  group_by(indic_et, Indic_et) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
indic_et Indic_et Nobs
TRD_VAL Trade value in million ECU/EURO 894999
TRD_VAL_SCA Seasonally and calendar adjusted trade value in million ECU/EURO 894999
IVU Unit value index (2015=100) 797307
IVOL_NSA Volume indices - unadjusted data (2015=100) 796282
IVOL_SCA Seasonally and calendar adjusted volume indices (2015=100) 796238
TRD_VAL_SCA_RT1 Growth rate M/M-1 of the seasonally and calendar adjusted trade value 592016
TRD_VAL_RT12 Growth rate M/M-12 of the trade value 569410
IVU_RT1 Growth rate M/M-1 of the unit-value indices 493482
IVOL_SCA_RT1 Growth rate M/M-1 of the seasonally and calendar adjusted volume Indices 492169
IVU_RT12 Growth rate M/M-12 of the unit-value indices 473490
IVOL_NSA_RT12 Growth rate M/M-12 of the volume Indices - unadjusted data 472293

sitc06

ext_st_ea19sitc %>%
  left_join(sitc06, by = "sitc06") %>%
  group_by(sitc06, Sitc06) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
sitc06 Sitc06 Nobs
TOTAL Total - all products 484982
SITC5-8 Manufactured goods 484132
SITC6_8 Other manufactured goods 484074
SITC6 Manufactured goods classified chiefly by material 484012
SITC2_4 Raw materials 483955
SITC7 Machinery and transport equipment 483938
SITC2 Crude materials, inedible, except fuels 483934
SITC8 Miscellaneous manufactured articles 483141
SITC5 Chemicals and related products, n.e.s. 483083
SITC0_1 Food, drinks and tobacco 482609
SITC0 Food and live animals 482418
SITC1 Beverages and tobacco 480222
SITC3 Mineral fuels, lubricants and related materials 474155
SITC4 Animal and vegetable oils, fats and waxes 466278
SITC33 Petroleum, petroleum products and related materials 346983
SITC9 Commodities and transactions not classified elsewhere in the SITC 184769

stk_flow

ext_st_ea19sitc %>%
  left_join(stk_flow, by = "stk_flow") %>%
  group_by(stk_flow, Stk_flow) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
stk_flow Stk_flow Nobs
EXP Exports 2957259
IMP Imports 2925662
BAL_RT Balance for values / Ratio for indices 1389764

geo

ext_st_ea19sitc %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  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 .}

partner

ext_st_ea19sitc %>%
  left_join(partner, by = "partner") %>%
  group_by(partner, Partner) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

time

ext_st_ea19sitc %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()