Code
%>%
ei_bpm6iip_q left_join(bop_item, by = "bop_item") %>%
group_by(bop_item, Bop_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Data - Eurostat
%>%
ei_bpm6iip_q left_join(bop_item, by = "bop_item") %>%
group_by(bop_item, Bop_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
ei_bpm6iip_q left_join(partner, by = "partner") %>%
group_by(partner, Partner) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
partner | Partner | Nobs |
---|---|---|
WRL_REST | Rest of the world | 61206 |
EXT_EA20 | Extra-euro area - 20 countries (from 2023) | 914 |
EXT_EU27_2020 | Extra-EU27 (from 2020) | 584 |
%>%
ei_bpm6iip_q left_join(stk_flow, by = "stk_flow") %>%
group_by(stk_flow, Stk_flow) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
stk_flow | Stk_flow | Nobs |
---|---|---|
N_LE | Net positions at the end of period | 26317 |
A_LE | Assets - positions at the end of period | 17138 |
L_LE | Liabilities - positions at the end of period | 16626 |
NE_LE | Net liabilities (liabilities minus assets) | 2623 |
%>%
ei_bpm6iip_q left_join(sector10, by = "sector10") %>%
group_by(sector10, Sector10) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
sector10 | Sector10 | Nobs |
---|---|---|
S1 | Total economy | 62704 |
%>%
ei_bpm6iip_q left_join(sectpart, by = "sectpart") %>%
group_by(sectpart, Sectpart) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
sectpart | Sectpart | Nobs |
---|---|---|
S1 | Total economy | 62704 |
%>%
ei_bpm6iip_q left_join(sectpart, by = "sectpart") %>%
group_by(sectpart, Sectpart) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
sectpart | Sectpart | Nobs |
---|---|---|
S1 | Total economy | 62704 |
%>%
ei_bpm6iip_q left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {