Public methods
Method new()
Creates a new instance of this R6 class.
Usage
DataBackendMatrix$new(data, dense = NULL, primary_key = NULL)
Arguments
data
Matrix::Matrix()
The input Matrix::Matrix()
.
dense
data.frame()
.
Dense data, converted to data.table::data.table()
.
primary_key
(character(1)
| integer()
)
Name of the primary key column, or integer vector of row ids.
Method data()
Returns a slice of the data in the specified format.
Currently, the only supported formats are "data.table"
and "Matrix"
.
The rows must be addressed as vector of primary key values, columns must be referred to via column names.
Queries for rows with no matching row id and queries for columns with no matching column name are silently ignored.
Rows are guaranteed to be returned in the same order as rows
, columns may be returned in an arbitrary order.
Duplicated row ids result in duplicated rows, duplicated column names lead to an exception.
Usage
DataBackendMatrix$data(rows, cols, data_format = "data.table")
Arguments
rows
integer()
Row indices.
cols
character()
Column names.
data_format
(character(1)
)
Desired data format, e.g. "data.table"
or "Matrix"
.
Method head()
Retrieve the first n
rows.
Usage
DataBackendMatrix$head(n = 6L)
Arguments
n
(integer(1)
)
Number of rows.
Returns
data.table::data.table()
of the first n
rows.
Method distinct()
Returns a named list of vectors of distinct values for each column
specified. If na_rm
is TRUE
, missing values are removed from the
returned vectors of distinct values. Non-existing rows and columns are
silently ignored.
Usage
DataBackendMatrix$distinct(rows, cols, na_rm = TRUE)
Arguments
rows
integer()
Row indices.
cols
character()
Column names.
na_rm
logical(1)
Whether to remove NAs or not.
Returns
Named list()
of distinct values.
Method missings()
Returns the number of missing values per column in the specified slice
of data. Non-existing rows and columns are silently ignored.
Usage
DataBackendMatrix$missings(rows, cols)
Arguments
rows
integer()
Row indices.
cols
character()
Column names.
Returns
Total of missing values per column (named numeric()
).