Re: [I] [Python] Unable to import arrow table to pandas if it has categorical columns with index types of unsigned ints [arrow]

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

Danferno commented on issue #47022:
URL: https://github.com/apache/arrow/issues/47022#issuecomment-3637584537

   The only solution I've found for this so far is catching any pa.lib.ArrowTypeError and then using this manual parquet -> pyarrow -> pandas code that recasts the field type. It might break upon negative values in the indices?
   
   
   ```
   def readParquetFileWithUnsignedDictionaryKeys(path, fs=None):
       import pyarrow as pa
       table = pa.parquet.read_table(path, filesystem=fs)
       for field, column in zip(table.schema, table.columns):      # fiter = iter(zip(table.schema, table.columns)); field, column = next(fiter)
           if pa.types.is_dictionary(field.type):
               # Convert unsigned types to their signed variant
               index_type = field.type.index_type
               if pa.types.is_uint8(index_type):
                   new_index_type = pa.int8()
               elif pa.types.is_uint16(index_type):
                   new_index_type = pa.int16()
               elif pa.types.is_uint32(index_type):
                   new_index_type = pa.int32()
               elif pa.types.is_uint64(index_type):
                   new_index_type = pa.int64()
               else:
                   new_index_type = index_type
               new_type = pa.dictionary(new_index_type, field.type.value_type)
               table = table.set_column(table.schema.get_field_index(field.name), field.name, column.cast(new_type))
       return table.to_pandas()
   ```


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