collapse_to_matrices: Collapse a "tidy" data frame to matrices in a data frame...

View source: R/collapse.R

collapse_to_matricesR Documentation

Collapse a "tidy" data frame to matrices in a data frame matsindf)

Description

A "tidy" data frame contains information that can be collapsed into matrices, including columns for matrix names, row names, column names, row types, column types, and values (entries in matrices). These column names are specified as strings by the matnames, rownames, colnames, rowtypes, coltypes, and values arguments to collapse_to_matrices(), respectively. A matsindf-style matrix has named rows and columns. In addition, matsindf-style matrices have "types" for row and column information, such as "Commodities", "Industries", "Products", or "Machines". The row and column types for the matsindf-style matrices are stored as attributes on the matrix (rowtype and coltype), which can be accessed with the functions matsbyname::rowtype() and matsbyname::coltype(). Row and column types are both respected and propagated by the various *_byname functions of the matsbyname package. Use the *_byname functions when you do operations on the matsindf-style matrices. The matsindf-style matrices will be stored in a column with same name as the incoming values column. This function is similar to tidyr::nest(), which stores data frames into a cell of a data frame. With collapse_to_matrices, matrices are created. This function respects groups, like dplyr::summarise(). (In fact, calls to this function may not work properly unless grouping is provided. Errors of the form "Error: Duplicate identifiers for rows ..." are usually fixed by grouping .DF prior to calling this function.) The usual approach is to dplyr::group_by() the matnames column and any other columns to be preserved in the output. Note that execution is halted if any of rownames, colnames, rowtypes, coltypes, or values is a grouping variable in .DF. rowtypes and coltypes should be the same for all rows of the same matrix in .DF; execution is halted if that is not the case. tidyr::pivot_wider()ing the output by matnames may be necessary before calculations are done on the collapsed matrices. See the example.

Usage

collapse_to_matrices(
  .DF,
  matnames = "matnames",
  matvals = "matvals",
  rownames = "rownames",
  colnames = "colnames",
  rowtypes = if ("rowtypes" %in% names(.DF)) "rowtypes" else NULL,
  coltypes = if ("coltypes" %in% names(.DF)) "coltypes" else NULL
)

Arguments

.DF

the "tidy" data frame

matnames

A string identifying the column in .DF containing matrix names for matrices to be created. Default is "matnames".

matvals

A string identifying the column in .DF containing values to be inserted into the matrices to be created. This will also be the name of the column in the output containing matrices formed from the data in the matvals column. Default is "matvals".

rownames

A string identifying the column in .DF containing row names for matrices to be created. Default is "rownames".

colnames

A string identifying the column in .DF containing column names for matrices to be created. Default is "colnames".

rowtypes

An optional string identifying the column in .DF containing the type of values in rows of the matrices to be created. Default is if ("rowtypes" %in% names(.DF)) "rowtypes" else NULL, so that failure to set the rowtypes argument will give NULL, as appropriate.

coltypes

An optional string identifying the column in .DF containing the type of values in columns of the matrices to be created Default is if ("coltypes" %in% names(.DF)) "rowtypes" else NULL, so that failure to set the coltypes argument will give NULL, as appropriate.

Details

Groups are not preserved on output.

Value

A data frame with matrices in the matvals column.

See Also

tidyr::nest() and dplyr::summarise().

Examples

library(dplyr)
library(tidyr)
library(tibble)
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",   "E",   "E",   "E",   "V",   "V",
                                 "U",   "U",   "E",   "E", "eta", "eta"),
                  row     = c( "c 1", "c 2", "c 1", "c 2", "c 2", "i 1", "i 2",
                               "c 1", "c 1", "c 1", "c 2", NA, NA),
                  col     = c( "i 1", "i 2", "i 1", "i 2", "i 3", "c 1", "c 2",
                               "i 1", "i 2", "i 1", "i 2", 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", matvals = "vals",
                             rownames = "row", colnames = "col",
                             rowtypes = "rowtypes", coltypes = "coltypes")
mats %>% pivot_wider(names_from = matrix, values_from = vals)

matsindf documentation built on May 20, 2022, 1:06 a.m.