ak.to_numpy — Awkward Array documentation

# ak.to_numpy

Defined in awkward.operations.convert on line 163.

ak.to_numpy(array, allow_missing=True)

Converts `array` (many types supported, including all Awkward Arrays and Records) into a NumPy array, if possible.

If the data are numerical and regular (nested lists have equal lengths in each dimension, as described by the #type), they can be losslessly converted to a NumPy array and this function returns without an error.

Otherwise, the function raises an error. It does not create a NumPy array with dtype `"O"` for `np.object_` (see the note on object_ type) since silent conversions to dtype `"O"` arrays would not only be a significant performance hit, but would also break functionality, since nested lists in a NumPy `"O"` array are severed from the array and cannot be sliced as dimensions.

If `array` is a scalar, it is converted into a NumPy scalar.

If `allow_missing` is True; NumPy masked arrays are a possible result; otherwise, missing values (None) cause this function to raise an error.

See also `ak.from_numpy` and `ak.to_cupy`.