Compute Functions¶

Arrow supports logical compute operations over inputs of possibly varying types. Many compute functions support both array (chunked or not) and scalar inputs, but some will mandate either. For example, sort_indices requires its first and only input to be an array.

Below are a few simple examples:

>>> import pyarrow as pa
>>> import pyarrow.compute as pc
>>> a = pa.array([1, 1, 2, 3])
>>> pc.sum(a)
<pyarrow.Int64Scalar: 7>
>>> b = pa.array([4, 1, 2, 8])
>>> pc.equal(a, b)
<pyarrow.lib.BooleanArray object at 0x7f686e4eef30>
[
  false,
  true,
  true,
  false
]
>>> x, y = pa.scalar(7.8), pa.scalar(9.3)
>>> pc.multiply(x, y)
<pyarrow.DoubleScalar: 72.54>

These functions can do more than just element-by-element operations. Here is an example of sorting a table:

>>> import pyarrow as pa
>>> import pyarrow.compute as pc
>>> t = pa.table({'x':[1,2,3],'y':[3,2,1]})
>>> i = pc.sort_indices(t, sort_keys=[('y', 'ascending')])
>>> i
<pyarrow.lib.UInt64Array object at 0x7fcee5df75e8>
[
  2,
  1,
  0
]