soumya-ghosh commented on code in PR #1066:
URL: https://github.com/apache/iceberg-python/pull/1066#discussion_r1719782196


##########
pyiceberg/table/__init__.py:
##########
@@ -4393,12 +4397,12 @@ def _readable_metrics_struct(bound_type: PrimitiveType) 
-> pa.StructType:
                     "spec_id": data_file.spec_id,
                     "record_count": data_file.record_count,
                     "file_size_in_bytes": data_file.file_size_in_bytes,
-                    "column_sizes": dict(data_file.column_sizes),
-                    "value_counts": dict(data_file.value_counts),
-                    "null_value_counts": dict(data_file.null_value_counts),
-                    "nan_value_counts": dict(data_file.nan_value_counts),
-                    "lower_bounds": dict(data_file.lower_bounds),
-                    "upper_bounds": dict(data_file.upper_bounds),
+                    "column_sizes": dict(data_file.column_sizes) if 
data_file.column_sizes is not None else None,

Review Comment:
   Agreed.
   But these values are `null` when queried through Spark (Spark 3.5, Iceberg 
1.5.0), hence I am assigning them to `None` over here.
   <img width="1121" alt="Screenshot 2024-08-16 at 5 47 43 PM" 
src="https://github.com/user-attachments/assets/c5b63ad5-93a1-49b5-8072-ad385ddc609d";>
   



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