Fokko commented on issue #8551:
URL: https://github.com/apache/iceberg/issues/8551#issuecomment-1715450270

   @grobgl That is correct. Currently, we stick to the order of fields of the 
table schema itself.
   
   ```
   Python 3.9.18 (main, Aug 24 2023, 21:19:58) 
   Type 'copyright', 'credits' or 'license' for more information
   IPython 8.14.0 -- An enhanced Interactive Python. Type '?' for help.
   
   In [1]: from pyiceberg.catalog import load_catalog
      ...: 
   
   In [2]: cat = load_catalog("local")
   
   In [3]: tbl = cat.load_table("nyc.taxis")
   
   In [4]: tbl.scan().to_pandas()
   Out[4]: 
             VendorID      tpep_pickup_datetime     tpep_dropoff_datetime  
passenger_count  ...  improvement_surcharge  total_amount congestion_surcharge  
airport_fee
   0                2 2003-01-05 23:37:05+00:00 2003-01-06 21:02:39+00:00       
       1.0  ...                    0.0          0.00                  0.0       
  0.00
   1                2 2009-01-01 00:35:26+00:00 2009-01-01 00:52:52+00:00       
       1.0  ...                    0.3         15.30                  2.5       
  0.00
   2                2 2009-01-01 00:34:48+00:00 2009-01-01 22:29:18+00:00       
       1.0  ...                    0.3         72.72                  0.0       
  1.25
   3                2 2009-01-01 00:04:40+00:00 2009-01-01 00:18:40+00:00       
       1.0  ...                    0.3         13.80                  2.5       
  0.00
   4                2 2009-01-01 00:08:33+00:00 2009-01-01 00:14:48+00:00       
       1.0  ...                    0.3         10.30                  2.5       
  0.00
   ...            ...                       ...                       ...       
       ...  ...                    ...           ...                  ...       
   ...
   15885528         2 2022-05-03 08:26:41+00:00 2022-05-03 08:35:54+00:00       
       1.0  ...                    0.3         15.36                  2.5       
  0.00
   15885529         2 2022-05-03 08:40:25+00:00 2022-05-03 08:50:11+00:00       
       1.0  ...                    0.3         13.80                  2.5       
  0.00
   15885530         2 2022-05-03 08:56:56+00:00 2022-05-03 09:11:19+00:00       
       1.0  ...                    0.3         15.80                  2.5       
  0.00
   15885531         2 2022-05-03 09:17:10+00:00 2022-05-03 09:33:03+00:00       
       1.0  ...                    0.3         15.30                  2.5       
  0.00
   15885532         2 2022-05-03 09:36:16+00:00 2022-05-03 09:44:01+00:00       
       1.0  ...                    0.3         11.54                  2.5       
  0.00
   
   [15885533 rows x 19 columns]
   
   In [5]: tbl.scan(selected_fields=('VendorID', 'tpep_dropoff_datetime', 
'tpep_pickup_datetime')).to_pandas()
   Out[5]: 
             VendorID      tpep_pickup_datetime     tpep_dropoff_datetime
   0                2 2003-01-05 23:37:05+00:00 2003-01-06 21:02:39+00:00
   1                2 2009-01-01 00:35:26+00:00 2009-01-01 00:52:52+00:00
   2                2 2009-01-01 00:34:48+00:00 2009-01-01 22:29:18+00:00
   3                2 2009-01-01 00:04:40+00:00 2009-01-01 00:18:40+00:00
   4                2 2009-01-01 00:08:33+00:00 2009-01-01 00:14:48+00:00
   ...            ...                       ...                       ...
   15885528         2 2022-05-03 08:26:41+00:00 2022-05-03 08:35:54+00:00
   15885529         2 2022-05-03 08:40:25+00:00 2022-05-03 08:50:11+00:00
   15885530         2 2022-05-03 08:56:56+00:00 2022-05-03 09:11:19+00:00
   15885531         2 2022-05-03 09:17:10+00:00 2022-05-03 09:33:03+00:00
   15885532         2 2022-05-03 09:36:16+00:00 2022-05-03 09:44:01+00:00
   
   [15885533 rows x 3 columns]
   ```
   
   I can see how this is counter intuitive. @rdblue WDYT?


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