as_data_backend function

Create a Data Backend

Wraps a DataBackend around data. list("mlr3") ships with methods for data.frame (converted to a DataBackendDataTable

and Matrix from package list("Matrix") (converted to a DataBackendMatrix ).

Additional methods are implemented in the package list("mlr3db"), e.g. to connect to real DBMS like PostgreSQL (via list("dbplyr")) or DuckDB (via list("DBI")/list("duckdb")).

## S3 method for class 'Matrix'
as_data_backend(data, primary_key = NULL, dense = NULL, ...)

as_data_backend(data, primary_key = NULL, ...)

## S3 method for class 'data.frame'
as_data_backend(data, primary_key = NULL, keep_rownames = FALSE, ...)

Arguments

• data: (data.frame())

  The input data.frame(). Automatically converted to a data.table::data.table().

• primary_key: (character(1) | integer())

  Name of the primary key column, or integer vector of row ids.

• dense: (data.frame()). Dense data.

• ...: (any)

  Additional arguments passed to the respective DataBackend method.

• keep_rownames: (logical(1) | character(1))

  If TRUE or a single string, keeps the row names of data as a new column. The column is named like the provided string, defaulting to "..rownames" for keep_rownames == TRUE. Note that the created column will be used as a regular feature by the task unless you manually change the column role. Also see data.table::as.data.table().

Returns

DataBackend .

Examples

# create a new backend using the penguins data:
as_data_backend(palmerpenguins::penguins)

See Also

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter10/advanced_technical_aspects_of_mlr3.html#sec-backends
• Package list("mlr3db") to interface out-of-memory data, e.g. SQL servers or list("duckdb").

Other DataBackend: DataBackend, DataBackendDataTable, DataBackendMatrix