jorisvandenbossche opened a new pull request, #36242:
URL: https://github.com/apache/arrow/pull/36242

   ### Rationale for this change
   
   Currently, calling `np.asarray(table)` gives the wrong result (transpose of 
the expected result), because we don't implement an explicit `__array__` to 
numpy conversion, and then numpy falls back to iterate the object (but this 
iterates the columns, giving a transposed result).
   
   To fix this unexpected result, I added an actual `__array__` (currently with 
a naive implementation in python, potentially this could be optimized in our 
C++ conversion layer)
   
   ### Are there any user-facing changes?
   
   This changes the behaviour of `np.asarray(table/record_batch)`


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