expand_to_tidy: Expand a 'matsindf' data frame

In matsindf: Matrices in Data Frames

Expand a matsindf data frame

Description

Any tidy data frame of matrices (in which each row represents one matrix observation) can also be represented as a tidy data frame with each non-zero matrix entry as an observation on its own row. This function (and collapse_to_matrices()) convert between the two representations.

Usage

expand_to_tidy(
  .DF,
  matnames = "matnames",
  matvals = "matvals",
  rownames = "rownames",
  colnames = "colnames",
  rowtypes = "rowtypes",
  coltypes = "coltypes",
  drop = NA
)

Arguments

.DF	The data frame containing matsindf-style matrices. (.DF may also be a named list of matrices, in which case names of the matrices are taken from the names of items in the list and list items are expected to be matrices.)
matnames	The name of the column in .DF containing matrix names (a string). Default is "matnames".
matvals	The name of the column in .DF containing IO-style matrices or constants (a string), This will also be the name of the column containing matrix entries in the output data frame. Default is "matvals".
rownames	The name for the output column of row names (a string). Default is "rownames".
colnames	The name for the output column of column names (a string). Default is "colnames".
rowtypes	An optional name for the output column of row types (a string). Default is "rowtypes".
coltypes	The optional name for the output column of column types (a string) Default is "coltypes".
drop	If specified, the value to be dropped from output, For example, drop = 0 will cause 0 entries in the matrices to be deleted from output. If NA, no values are dropped from output. Default is NA.

Details

Names for output columns are specified in the rownames, colnames, rowtypes, and coltypes, arguments. The entries of the matsindf-style matrices are stored in an output column named values.

Value

A tidy data frame containing expanded matsindf-style matrices

Examples

library(dplyr)
library(matsbyname)
ptype <- "Products"
itype <- "Industries"
tidy <- data.frame(Country  = c( "GH",  "GH",  "GH",  "GH",  "GH",  "GH",  "GH",
                                 "US",  "US",  "US",  "US", "GH", "US"),
                  Year      = c( 1971,  1971,  1971,  1971,  1971,  1971,  1971,
                                 1980,  1980,  1980,  1980, 1971, 1980),
                  matrix    = c(  "U",   "U",   "Y",   "Y",   "Y",   "V",   "V",
                                  "U",   "U",   "Y",   "Y", "eta", "eta"),
                  row       = c(  "c1",  "c2",  "c1",  "c2",  "c2",  "i1",  "i2",
                                  "c1",  "c1",  "c1",  "c2", NA, NA),
                  col       = c(  "i1",  "i2",  "i1",  "i2",  "i3",  "c1",  "c2",
                                  "i1",  "i2",  "i1",  "i2", NA, NA),
                  rowtypes  = c( ptype, ptype, ptype, ptype, ptype, itype, itype,
                                 ptype, ptype, ptype, ptype, NA, NA),
                  coltypes  = c(itype, itype, itype, itype, itype, ptype, ptype,
                                itype, itype, itype, itype, NA, NA),
                  vals      = c(11  ,  22,    11 ,   22 ,   23 ,   11 ,   22 ,
                                11 ,   12 ,   11 ,   22,   0.2, 0.3)) %>%
  group_by(Country, Year, matrix)
mats <- collapse_to_matrices(tidy, matnames = "matrix", rownames = "row", colnames = "col",
                             rowtypes = "rowtypes", coltypes = "coltypes",
                             matvals = "vals") %>%
  ungroup()
expand_to_tidy(mats, matnames = "matrix", matvals = "vals",
                     rownames = "rows", colnames = "cols",
                     rowtypes = "rt",   coltypes = "ct")
expand_to_tidy(mats, matnames = "matrix", matvals = "vals",
                     rownames = "rows", colnames = "cols",
                     rowtypes = "rt",   coltypes = "ct", drop = 0)

matsindf documentation built on July 4, 2024, 1:11 a.m.