[GitHub] [arrow] spenczar commented on issue #35622: [Python] Fixed size lists of numeric types without nulls could be converted to numpy with zero-copy

["spenczar (via GitHub)" <gi...@apache.org>]

spenczar commented on issue #35622:
URL: https://github.com/apache/arrow/issues/35622#issuecomment-1561313124

   > The problem is that to_numpy() for a fixed size list array doesn't give you this flat (or nd) array of the values, but an object dtype array of sub-arrays.
   
   True, but is this desirable? I can't think of a scenario where that is a useful return shape. In practice, my group currently always reshapes that into a 2D array.
   
   FixedShapeTensorArray has a `to_numpy_ndarrray` method which addresses this usage issue: https://github.com/apache/arrow/blob/f45a9e57dfcabe73b341f0e0504f7e8210988dad/python/pyarrow/array.pxi#L3149-L3161
   
   Maybe a solution is for FixedSizeListArray to have a to_numpy_ndarray method? It'd be a somewhat crummy API, since you'd almost never want to use `to_numpy`, but it'd preserve the current behavior.
   
   > Sidenote, there is actually another API to directly get this numpy array, without having to go through the buffers manually:
   
   Very useful to know, thanks! I'll add an issue that those should be documented for the ListArray, LargeListArray, and FixedSizeListArray types (see https://arrow.apache.org/docs/python/generated/pyarrow.FixedSizeListArray.html#pyarrow.FixedSizeListArray.values).


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