pyarrow.compute.partition_nth_indices

pyarrow.compute.partition_nth_indices(array, /, pivot, *, null_placement='at_end', options=None, memory_pool=None)

Return the indices that would partition an array around a pivot.

This functions computes an array of indices that define a non-stable partial sort of the input array.

The output is such that the N’th index points to the N’th element of the input in sorted order, and all indices before the N’th point to elements in the input less or equal to elements at or after the N’th.

By default, null values are considered greater than any other value and are therefore partitioned towards the end of the array. For floating-point types, NaNs are considered greater than any other non-null value, but smaller than null values.

The pivot index N must be given in PartitionNthOptions. The handling of nulls and NaNs can also be changed in PartitionNthOptions.

Parameters:

arrayArray-like

Argument to compute function.

pivotint

Index into the equivalent sorted array of the pivot element.

null_placementstr, default “at_end”

Where nulls in the input should be partitioned. Accepted values are “at_start”, “at_end”.

optionspyarrow.compute.PartitionNthOptions, optional

Alternative way of passing options.

memory_poolpyarrow.MemoryPool, optional

If not passed, will allocate memory from the default memory pool.

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