aggregate_map: Aggregates or disaggregates a data frame

In pik-piam/quitte: Bits and pieces of code to use with quitte-style data frames

Aggregates or disaggregates a data frame

Description

Aggregates or disaggregates the values of a data frame according to a mapping

Usage

aggregate_map(
  data,
  mapping,
  by,
  subset2agg = NULL,
  only.new = TRUE,
  na.rm = TRUE,
  weights = NULL,
  forceAggregation = FALSE,
  autodetect = "auto",
  scaleWeights = TRUE,
  variable = "variable",
  value = "value",
  unit = "unit",
  weight_val_col = "weight_val_col",
  weight_item_col = NULL,
  fun = sum
)

Arguments

data	a data frame.
mapping	a data frame connecting the resolution in "data" and the wished resolution
by	(named) vector giving the correspondence between the column name of "data" and of the "mapping"
subset2agg	subset of variables for which the (dis)aggregation is applied. If NULL (the default), the (dis)aggregation is applied to all variables.
only.new	If FALSE (the default), add the (dis)aggregated data frame to existing ones. If TRUE, return only the (dis)aggregated data frame.
na.rm	If TRUE (the default), remove items calculated as NA.
weights	a data frame, a variable name as a character vector, or NULL. See details.
forceAggregation	binary. If TRUE, (dis)aggregation will be applied even though the items contained contained in the data and in the data do not fully match. The data is reduced to the items covered both by the mapping and the data.
autodetect	this parameter takes the values 'auto', 'aggregate' or 'disaggregate'. If 'auto' (the default) the function tries to auto-detect whether this is an aggregation or a disaggregation. If 'aggregate', it will aggregate, if 'disaggregate', it will disaggregate.
scaleWeights	logical. If TRUE, weights are scaled so that the sum of the components equals the value of the larger category.
variable	Column name of variables. Defaults to "variable".
value	Column name of values. Defaults to "value".
unit	Column name of units. Defaults to "unit".
weight_val_col	name of the value column in the "weigths" data frame, if "weigths" is a data frame
weight_item_col	name of the item column in the "weigths" data frame, if "weigths" is a data frame. The item column is the column corresponding to the mapping
fun	aggregation function to use. Defaults to sum.

Details

By default "weights" is set to NULL. For aggregations, this means that values will be summed as they are. For disaggregations, each component of the larger category will take the same value as the larger category, or "scaleWeights" is TRUE, each component will be given an even weight. For aggregations, "weights" can also be the name of a variable contained in "data". "weights" may also be a data frame.

Value

A data frame.

Author(s)

Antoine Levesque

Examples

library(tidyr)
library(dplyr)
data <- inline.data.frame(c(
  "model;    scenario;   region;   variable;           unit;         period;   value",
  "REMIND;   Baseline;   USA;      GDP per Capita|MER; US$2005/yr;   2010;     40000",
  "REMIND;   Baseline;   USA;      GDP per Capita|MER; US$2005/yr;   2020;     50000",
  "REMIND;   Baseline;   USA;      Population;         million;      2010;     300",
  "REMIND;   Baseline;   USA;      Population;         million;      2020;     350",
  "REMIND;   Baseline;   CHN;      GDP per Capita|MER; US$2005/yr;   2010;     7000",
  "REMIND;   Baseline;   CHN;      GDP per Capita|MER; US$2005/yr;   2020;     8000",
  "REMIND;   Baseline;   CHN;      Population;         million;      2010;     1300",
  "REMIND;   Baseline;   CHN;      Population;         million;      2020;     1400"))

mapping = inline.data.frame(c(
  "region;      New_region",
  "USA;         GLO",
  "CHN;         GLO"
))

mapping2 = inline.data.frame(c(
  "Item      ;         Item_new",
  "Population;         Urban Population ",
  "Population;         Rural Population"
))

weights = inline.data.frame(c(
  "region; itemI           ;   weight",
  "USA   ; Urban Population;      0.5",
  "USA   ; Rural Population;      0.2",
  "CHN   ; Urban Population;      2",
  "CHN   ; Rural Population;      1"
))

#Regional Aggregation
aggregate_map(data,mapping, by = "region", subset2agg = c("Population"))

#Regional Weighted Aggregation
aggregate_map(data,mapping, by = "region", subset2agg = "GDP per Capita|MER",
              weights = "Population")

#Variable Weigthed Disaggregation
aggregate_map(data,mapping2, by = c("variable" = "Item"),
              subset2agg = c("Population"),weights = weights,
              weight_val_col = "weight", weight_item_col = "itemI")

pik-piam/quitte documentation built on April 26, 2024, 12:58 a.m.