Collapse a "tidy" data frame to matrices in a data frame matsindf)
Source: R/collapse.R
collapse_to_matrices.RdA "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,
matrix.class = lifecycle::deprecated(),
matrix_class = c("matrix", "Matrix")
)Arguments
- .DF
the "tidy" data frame
- matnames
A string identifying the column in
.DFcontaining matrix names for matrices to be created. Default is "matnames".- matvals
A string identifying the column in
.DFcontaining 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 thematvalscolumn. Default is "matvals".- rownames
A string identifying the column in
.DFcontaining row names for matrices to be created. Default is "rownames".- colnames
A string identifying the column in
.DFcontaining column names for matrices to be created. Default is "colnames".- rowtypes
An optional string identifying the column in
.DFcontaining the type of values in rows of the matrices to be created. Default isif ("rowtypes" %in% names(.DF)) "rowtypes" else NULL, so that failure to set the rowtypes argument will giveNULL, as appropriate.- coltypes
An optional string identifying the column in
.DFcontaining the type of values in columns of the matrices to be created Default isif ("coltypes" %in% names(.DF)) "rowtypes" else NULL, so that failure to set the coltypes argument will giveNULL, as appropriate.- matrix.class
![[Deprecated]](figures/lifecycle-deprecated.svg)
Use matrix_classinstead.- matrix_class
One of "matrix" or "Matrix". "matrix" creates a
base::matrixobject with thematrix()function. "Matrix" creates aMatrix::Matrixobject using thematsbyname::Matrix()function. This could be a sparse matrix. Default is "matrix".
Details
Groups are not preserved on output.
Note that two types of matrices can be created, a matrix or a Matrix.
Matrix has the advantage of representing sparse matrices with less memory
(and disk space).
Matrix objects are created by matsbyname::Matrix().
Examples
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
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)
#> # A tibble: 2 × 6
#> Country Year E U V eta
#> <chr> <dbl> <list> <list> <list> <list>
#> 1 GH 1971 <dbl [2 × 3]> <dbl [2 × 2]> <dbl [2 × 2]> <dbl [1]>
#> 2 US 1980 <dbl [2 × 2]> <dbl [1 × 2]> <NULL> <dbl [1]>