Simplify a data frame by collapsing specified variables, according to the location of total codes, into a single vector or by consolidating groups of variables into new columns.
Arguments
- data
A data frame containing the variables to be collapsed.
- variables
A vector of variable names or a named list of variable names.
If
variablesis a vector, the specified variables indataare collapsed into a single character vector.If
variablesis a named list, each element in the list defines a group of variables to consolidate into a new column. Each list name will be used as the new column name in the resulting data frame.
- total
A total code or vector of total codes to use in the result.
If
variablesis a vector,totalspecifies the code to represent collapsed values.If
variablesis a named list,totalmay contain one code per group.
- include_names
A character string or
NULL(default).If
variablesis a vector, whether the resulting output vector is named depends on whetherinclude_namesisNULLor not. The actual value ofinclude_namesis ignored in this case.If
variablesis a named list,include_namesspecifies a suffix to append to each group name, creating one additional column per group. IfNULL, no additional columns with variable names are included in the result.
Value
A character vector (if variables is a vector) or a modified data frame (if variables is a named list).
Examples
# Creates data that can act as input
magnitude1 <- SSBtoolsData("magnitude1")
a <- model_aggregate(magnitude1,
formula = ~geo + eu + sector2 + sector4,
sum_vars = "value",
avoid_hierarchical = TRUE)
#> [pre_aggregate 20*6->10*5] [ModelMatrix] [crossprod] [cbind]
a
#> geo eu sector2 sector4 value
#> 1 Total Total Total Total 462.3
#> 2 Iceland Total Total Total 37.1
#> 3 Portugal Total Total Total 162.5
#> 4 Spain Total Total Total 262.7
#> 5 Total EU Total Total 425.2
#> 6 Total nonEU Total Total 37.1
#> 7 Total Total private Total 429.5
#> 8 Total Total public Total 32.8
#> 9 Total Total Total Agriculture 240.2
#> 10 Total Total Total Entertainment 131.5
#> 11 Total Total Total Governmental 32.8
#> 12 Total Total Total Industry 57.8
b <- total_collapse(a, list(GEO = c("geo", "eu"), SECTOR = c("sector2", "sector4")))
b
#> GEO SECTOR value
#> 1 Total Total 462.3
#> 2 Iceland Total 37.1
#> 3 Portugal Total 162.5
#> 4 Spain Total 262.7
#> 5 EU Total 425.2
#> 6 nonEU Total 37.1
#> 7 Total private 429.5
#> 8 Total public 32.8
#> 9 Total Agriculture 240.2
#> 10 Total Entertainment 131.5
#> 11 Total Governmental 32.8
#> 12 Total Industry 57.8
total_collapse(a, c("geo", "eu"))
#> [1] "Total" "Iceland" "Portugal" "Spain" "EU" "nonEU"
#> [7] "Total" "Total" "Total" "Total" "Total" "Total"
total_collapse(a, c("sector2", "sector4"))
#> [1] "Total" "Total" "Total" "Total"
#> [5] "Total" "Total" "private" "public"
#> [9] "Agriculture" "Entertainment" "Governmental" "Industry"
# Similar examples with both `total` and `include_names` parameters
aa <- a
aa[1:2][aa[1:2] == "Total"] <- "Europe"
aa[3:4][aa[3:4] == "Total"] <- ""
aa
#> geo eu sector2 sector4 value
#> 1 Europe Europe 462.3
#> 2 Iceland Europe 37.1
#> 3 Portugal Europe 162.5
#> 4 Spain Europe 262.7
#> 5 Europe EU 425.2
#> 6 Europe nonEU 37.1
#> 7 Europe Europe private 429.5
#> 8 Europe Europe public 32.8
#> 9 Europe Europe Agriculture 240.2
#> 10 Europe Europe Entertainment 131.5
#> 11 Europe Europe Governmental 32.8
#> 12 Europe Europe Industry 57.8
bb <- total_collapse(data = aa,
variables = list(GEO = c("geo", "eu"),
SECTOR = c("sector2", "sector4")),
total = c("Europe", ""),
include_names = "_Vars")
bb
#> GEO GEO_Vars SECTOR SECTOR_Vars value
#> 1 Europe geo sector2 462.3
#> 2 Iceland geo sector2 37.1
#> 3 Portugal geo sector2 162.5
#> 4 Spain geo sector2 262.7
#> 5 EU eu sector2 425.2
#> 6 nonEU eu sector2 37.1
#> 7 Europe geo private sector2 429.5
#> 8 Europe geo public sector2 32.8
#> 9 Europe geo Agriculture sector4 240.2
#> 10 Europe geo Entertainment sector4 131.5
#> 11 Europe geo Governmental sector4 32.8
#> 12 Europe geo Industry sector4 57.8
total_collapse(aa, c("geo", "eu"), total = "Europe", include_names = "_Vars")
#> geo geo geo geo eu eu geo
#> "Europe" "Iceland" "Portugal" "Spain" "EU" "nonEU" "Europe"
#> geo geo geo geo geo
#> "Europe" "Europe" "Europe" "Europe" "Europe"
total_collapse(aa, c("sector2", "sector4"), total = "", include_names = "_Vars")
#> sector2 sector2 sector2 sector2 sector2
#> "" "" "" "" ""
#> sector2 sector2 sector2 sector4 sector4
#> "" "private" "public" "Agriculture" "Entertainment"
#> sector4 sector4
#> "Governmental" "Industry"
# All four variables can be collapsed
total_collapse(a,
list(ALL = c("geo", "eu", "sector2", "sector4")),
include_names = "_Vars")
#> ALL ALL_Vars value
#> 1 Total geo 462.3
#> 2 Iceland geo 37.1
#> 3 Portugal geo 162.5
#> 4 Spain geo 262.7
#> 5 EU eu 425.2
#> 6 nonEU eu 37.1
#> 7 private sector2 429.5
#> 8 public sector2 32.8
#> 9 Agriculture sector4 240.2
#> 10 Entertainment sector4 131.5
#> 11 Governmental sector4 32.8
#> 12 Industry sector4 57.8