id | description |
---|---|
LOCATION | Country |
TRANSACT | Transaction |
SECTOR | Sector |
MEASURE | Measure |
TIME | Year |
OBS_VALUE | Observation Value |
TIME_FORMAT | Time Format |
OBS_STATUS | Observation Status |
UNIT | Unit |
POWERCODE | Unit multiplier |
REFERENCEPERIOD | Reference period |
id | label |
---|---|
SS1 | Total economy |
SS11_S12 | Corporations |
SS13 | General government |
SS14_S15 | Households and non-profit institutions serving households |
id | label |
---|---|
C | Current prices |
id | label |
---|---|
P1Y | Annual |
P1M | Monthly |
P3M | Quarterly |
P6M | Half-yearly |
P1D | Daily |
SNA_TABLE13_SNA93 %>%
# NFK1R: Consumption of fixed capital
filter(TRANSACT %in% c("SP5P", "B1_GE"), #
# SS1: Total economy
SECTOR == "SS1") %>%
left_join(SNA_TABLE13_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
select(Country = label, TRANSACT, obsTime, obsValue) %>%
spread(TRANSACT, obsValue) %>%
na.omit %>%
mutate(SP5P_B1_GE = (100*SP5P / B1_GE) %>% round(1) %>% paste("%")) %>%
select(Country, obsTime, SP5P_B1_GE) %>%
group_by(Country) %>%
summarise(year_first = first(obsTime),
value_first = first(SP5P_B1_GE),
year_last = last(obsTime),
value_last = last(SP5P_B1_GE)) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}
SNA_TABLE13_SNA93 %>%
# NFK1R: Consumption of fixed capital
filter(TRANSACT %in% c("SK1R", "B1_GE"),
SECTOR == "SS1") %>%
left_join(SNA_TABLE13_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
select(Country = label, TRANSACT, obsTime, obsValue) %>%
spread(TRANSACT, obsValue) %>%
na.omit %>%
mutate(SK1R_B1_GE = (100*SK1R / B1_GE) %>% round(1) %>% paste("%")) %>%
select(Country, obsTime, SK1R_B1_GE) %>%
group_by(Country) %>%
summarise(year_first = first(obsTime),
value_first = first(SK1R_B1_GE),
year_last = last(obsTime),
value_last = last(SK1R_B1_GE)) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}
SNA_TABLE13_SNA93 %>%
# NFK1R: Consumption of fixed capital
filter(TRANSACT %in% c("SP5P", "B1_GE", "SK1R"),
SECTOR == "SS1") %>%
left_join(SNA_TABLE13_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
select(Country = label, TRANSACT, obsTime, obsValue) %>%
spread(TRANSACT, obsValue) %>%
na.omit %>%
mutate(net_inv_B1_GE = (100*(SP5P-SK1R) / B1_GE) %>% round(1) %>% paste("%")) %>%
select(Country, obsTime, net_inv_B1_GE) %>%
group_by(Country) %>%
summarise(year_first = first(obsTime),
value_first = first(net_inv_B1_GE),
year_last = last(obsTime),
value_last = last(net_inv_B1_GE)) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}