nonstat_alloc_plots_df: Create non-stationary allocation graphs in a data frame

In EnergyEconomyDecoupling/PFUDatabase: Functions and Workflows for Primary-Final-Useful Societal Exergy Analysis Within the PSUT Framework

Create non-stationary allocation graphs in a data frame

Description

This function adds a column of ggplot2 graphs to a completed allocation tables data frame. The graphs are stored in a list column named plots.

Usage

nonstat_alloc_plots_df(
  .df,
  countries,
  data_col = "Data",
  plots = "Plots",
  country = IEATools::iea_cols$country,
  ef_product = IEATools::template_cols$ef_product,
  destination = IEATools::template_cols$destination,
  quantity = IEATools::template_cols$quantity,
  c_source = IEATools::template_cols$c_source,
  year = IEATools::iea_cols$year,
  .values = IEATools::template_cols$.values,
  machine = IEATools::template_cols$machine,
  eu_product = IEATools::template_cols$eu_product
)

Arguments

.df	The completed allocation tables data frame. Default is drake::readd(completed_allocation_tables_target, path = cache_path, character_only = TRUE).
countries	The countries for which allocation plots are to be created.
data_col	The name of the output column containing nested data for allocation graphs. Default is "Data".
plots	The name of the output column containing allocation graphs. Default is "Plots".
country	See IEATools::iea_cols.
ef_product, destination, quantity, c_source	See IEATools::template_cols.
year	See IEATools::iea_cols. Passed to alloc_graph().
.values, machine, eu_product	See IEATools::template_cols. Passed to alloc_graph().

Details

The data frame is grouped by all variables needed to create the allocation graph, specifically country, ef_product, and destination and nested prior to making the graphs, namely machine, eu_product, quantity, year, .values, and c_source, meaning that one allocation graph is constructed for each combination of those variables.

Value

A data frame containing a list column of ggplot2 non-stationary allocation graphs.

Examples

# Make a simple data frame with the expected structure.
alloc_table <- tibble::tribble(~Country, ~Method, ~Energy.type, ~Year, ~Ef.product, ~Destination,
                               ~.values, ~Machine, ~Quantity, ~Eu.product, ~C.source,
                               "GHA", "PCM", "E", 1971, "Gasoline", "Transport",
                               0.5, "Cars", "C_1 [%]", "MD", "World",
                               "GHA", "PCM", "E", 1971, "Gasoline", "Transport",
                               0.5, "Trucks", "C_2 [%]", "MD", "World",
                               "GHA", "PCM", "E", 2020, "Gasoline", "Transport",
                               0.2, "Cars", "C_1 [%]", "MD", "World",
                               "GHA", "PCM", "E", 2020, "Gasoline", "Transport",
                               0.8, "Trucks", "C_2 [%]", "MD", "World",
                               "ZAF", "PCM", "E", 1971, "Gasoline", "Transport",
                               0.5, "Cars", "C_1 [%]", "MD", "World",
                               "ZAF", "PCM", "E", 1971, "Gasoline", "Transport",
                               0.5, "Trucks", "C_2 [%]", "MD", "World",
                               "ZAF", "PCM", "E", 2020, "Gasoline", "Transport",
                               0.3, "Cars", "C_1 [%]", "MD", "World",
                               "ZAF", "PCM", "E", 2020, "Gasoline", "Transport",
                               0.7, "Trucks", "C_2 [%]", "MD", "World")
alloc_plots_df(alloc_table, c("GHA", "ZAF"))

EnergyEconomyDecoupling/PFUDatabase documentation built on Feb. 8, 2024, 8:45 a.m.