Calculates total aggregate primary energy from a data frame of IEA data.
This function is named with "_IEA", because it is meant to operate on
tidy, IEA-style data frames.
The function primary_aggregates
does the same thing,
but it is meant to operate on tidy SUT-style data frames.
primary_aggregates_IEA( .ieadata, flow = "Flow", flow_aggregation_point = "Flow.aggregation.point", energy = "E.dot", p_industries = c("Production", "Coal mines", "Oil and gas extraction", "Imports", "Exports", "International aviation bunkers", "International marine bunkers", "Stock changes"), eiou = "Energy industry own use", aggregate_primary = Recca::aggregate_cols$aggregate_primary_iea )
.ieadata | the data frame containing an IEA table |
---|---|
flow | the name of the column that contains flow information. Default is " |
flow_aggregation_point | the name of the column that identifies flow aggregation points.
Default is " |
energy | the name of the column that contains energy information. Default is " |
p_industries | a vector of names of primary industries. Default is
" |
eiou | the string that identifies energy industry own use in the |
aggregate_primary | the name of the aggregate primary energy
column to be created in the output data frame.
Default is " |
a data frame containing the grouping columns of .ieadata
as well as a column named with the value of aggregate_primary
.
This function works similar to summarise
:
it distills .ieadata
to many fewer rows
according to the grouping variables.
Thus, .ieadata
should be grouped prior to sending into this function.
Grouping columns are preserved on output.
library(dplyr) library(tidyr) r_ind <- resource_industries(UKEnergy2000mats %>% spread(key = matrix.name, value = matrix))[["r_industries"]][[1]] UKEnergy2000tidy %>% group_by(Country, Year, Energy.type, Last.stage) %>% primary_aggregates_IEA(p_industries = r_ind)#> # A tibble: 4 x 5 #> # Groups: Country, Year, Energy.type [2] #> Country Year Energy.type Last.stage EX_p_IEA.ktoe #> <chr> <dbl> <chr> <chr> <dbl> #> 1 GBR 2000 E Final 93000 #> 2 GBR 2000 E Services 93000 #> 3 GBR 2000 E Useful 93000 #> 4 GBR 2000 X Services 98220