copying

cudf._lib.pylibcudf.copying.allocate_like(Column input_column, mask_allocation_policy policy, size=None) → Column

Allocate a column with the same type as input_column.

For details, see allocate_like().

Parameters:

input_columnColumn

The column to use as a template for the output.

policymask_allocation_policy

Controls whether the output column has a valid mask.

sizeint, optional

The number of elements to allocate in the output column. If not specified, the size of the input column is used.

Returns:

pylibcudf.Column

A column with the same type and size as input.

cudf._lib.pylibcudf.copying.boolean_mask_scalars_scatter(list input, Table target, Column boolean_mask) → Table

Scatter scalars from input into target according to boolean_mask.

For details on the implementation, see boolean_mask_scatter().

Parameters:

inputList[Scalar]

A list of scalars to scatter into target.

targetTable

The table object into which to scatter data.

boolean_maskColumn

A mapping from rows in input to rows in target.

Returns:

pylibcudf.Table

The result of the scatter

cudf._lib.pylibcudf.copying.boolean_mask_table_scatter(Table input, Table target, Column boolean_mask) → Table

Scatter rows from input into target according to boolean_mask.

For details on the implementation, see boolean_mask_scatter().

Parameters:

inputTable

The table object from which to pull data.

targetTable

The table object into which to scatter data.

boolean_maskColumn

A mapping from rows in input to rows in target.

Returns:

pylibcudf.Table

The result of the scatter

cudf._lib.pylibcudf.copying.column_slice(Column input_column, list indices) → list

Slice input_column according to indices.

For details on the implementation, see slice().

Parameters:

input_columnColumn

The column to slice.

indicesList[int]

The indices to select from input_column.

Returns:

List[pylibcudf.Column]

The result of slicing input_column.

cudf._lib.pylibcudf.copying.column_split(Column input_column, list splits) → list

Split input_column into multiple columns.

For details on the implementation, see split().

Parameters:

input_columnColumn

The column to split.

splitsList[int]

The indices at which to split the column.

Returns:

List[pylibcudf.Column]

The result of splitting input_column.

cudf._lib.pylibcudf.copying.copy_if_else(lhs, rhs, Column boolean_mask) → Column

Copy elements from lhs or rhs into a new column according to boolean_mask.

For details on the implementation, see copy_if_else().

Parameters:

lhsColumn or Scalar

The column or scalar to copy from if the corresponding element in boolean_mask is True.

rhsColumn or Scalar

The column or scalar to copy from if the corresponding element in boolean_mask is False.

boolean_maskColumn

The boolean mask to use to select elements from lhs and rhs.

Returns:

pylibcudf.Column

The result of copying elements from lhs and rhs according to boolean_mask.

cudf._lib.pylibcudf.copying.copy_range(Column input_column, Column target_column, size_type input_begin, size_type input_end, size_type target_begin) → Column

Copy a range of elements from input_column to target_column.

For details on the implementation, see copy_range().

Parameters:

input_columnColumn

The column from which to copy elements.

target_columnColumn

The column into which to copy elements.

input_beginint

The index of the first element in input_column to copy.

input_endint

The index of the last element in input_column to copy.

target_beginint

The index of the first element in target_column to overwrite.

Returns:

pylibcudf.Column

A copy of target_column with the specified range overwritten.

cudf._lib.pylibcudf.copying.copy_range_in_place(Column input_column, Column target_column, size_type input_begin, size_type input_end, size_type target_begin) → Column

Copy a range of elements from input_column to target_column.

The target_column is overwritten in place.

For details on the implementation, see copy_range_in_place().

Parameters:

input_columnColumn

The column from which to copy elements.

target_columnColumn

The column into which to copy elements.

input_beginint

The index of the first element in input_column to copy.

input_endint

The index of the last element in input_column to copy.

target_beginint

The index of the first element in target_column to overwrite.

cudf._lib.pylibcudf.copying.empty_column_like(Column input)

Create an empty column with the same type as input.

For details, see empty_like().

Parameters:

inputColumn

The column to use as a template for the output.

Returns:

pylibcudf.Column

An empty column with the same type as input.

cudf._lib.pylibcudf.copying.empty_table_like(Table input)

Create an empty table with the same type as input.

For details, see empty_like().

Parameters:

inputTable

The table to use as a template for the output.

Returns:

pylibcudf.Table

An empty table with the same type as input.

cudf._lib.pylibcudf.copying.gather(Table source_table, Column gather_map, out_of_bounds_policy bounds_policy) → Table

Select rows from source_table according to the provided gather_map.

For details, see gather().

Parameters:

source_tableTable

The table object from which to pull data.

gather_mapColumn

The list of row indices to pull out of the source table.

bounds_policyout_of_bounds_policy

Controls whether out of bounds indices are checked and nullified in the output or if indices are assumed to be in bounds.

Returns:

pylibcudf.Table

The result of the gather

cudf._lib.pylibcudf.copying.get_element(Column input_column, size_type index) → Scalar

Get the element at index from input_column.

For details on the implementation, see get_element().

Parameters:

input_columnColumn

The column from which to get the element.

indexint

The index of the element to get.

Returns:

pylibcudf.Scalar

The element at index from input_column.

cudf._lib.pylibcudf.copying.scatter_scalars(list source, Column scatter_map, Table target_table) → Table

Scatter scalars from source into target_table according to scatter_map.

For details, see scatter().

Parameters:

sourceList[Scalar]

A list of scalars to scatter into target_table.

scatter_mapColumn

A mapping from rows in source to rows in target_table.

target_tableTable

The table object into which to scatter data.

Returns:

pylibcudf.Table

The result of the scatter

cudf._lib.pylibcudf.copying.scatter_table(Table source, Column scatter_map, Table target_table) → Table

Scatter rows from source into target_table according to scatter_map.

For details, see scatter().

Parameters:

sourceTable

The table object from which to pull data.

scatter_mapColumn

A mapping from rows in source to rows in target_table.

target_tableTable

The table object into which to scatter data.

Returns:

pylibcudf.Table

The result of the scatter

cudf._lib.pylibcudf.copying.shift(Column input, size_type offset, Scalar fill_values) → Column

Shift the elements of input by offset.

For details on the implementation, see shift().

Parameters:

inputColumn

The column to shift.

offsetint

The number of elements to shift by.

fill_valuesScalar

The value to use for elements that are shifted in from outside the bounds of the input column.

Returns:

pylibcudf.Column

A copy of input shifted by offset.

cudf._lib.pylibcudf.copying.table_slice(Table input_table, list indices) → list

Slice input_table according to indices.

For details on the implementation, see slice().

Parameters:

input_tableTable

The table to slice.

indicesList[int]

The indices to select from input_table.

Returns:

List[pylibcudf.Table]

The result of slicing input_table.

cudf._lib.pylibcudf.copying.table_split(Table input_table, list splits) → list

Split input_table into multiple tables.

For details on the implementation, see split().

Parameters:

input_tableTable

The table to split.

splitsList[int]

The indices at which to split the table.

Returns:

List[pylibcudf.Table]

The result of splitting input_table.