[GitHub] [superset] john-bodley commented on a diff in pull request #20760: fix(csv): Do not coerce persisted data integer columns to float

[GitBox <gi...@apache.org>]

john-bodley commented on code in PR #20760:
URL: https://github.com/apache/superset/pull/20760#discussion_r924024074


##########
superset/views/core.py:
##########
@@ -2502,8 +2502,7 @@ def csv(  # pylint: disable=no-self-use,too-many-locals
             obj = _deserialize_results_payload(
                 payload, query, cast(bool, results_backend_use_msgpack)
             )
-            columns = [c["name"] for c in obj["columns"]]
-            df = pd.DataFrame.from_records(obj["data"], columns=columns)
+            df = pd.DataFrame(data=obj["data"], dtype=object)

Review Comment:
   No need to specify column names as they're present in the data. Furthermore—per the Pandas documentation, 
   
   > Column labels to use for resulting frame when data does not have them, defaulting to RangeIndex(0, 1, 2, …, n). If data contains column labels, will perform column selection instead.
   
   the `columns` option doesn't rename existing columns if column labels are present, but performs column selection instead, i.e., 
   
   ```python
   >>> pd.DataFrame(data=[{"foo": 1}, {"foo": None}], dtype=object, columns=["foo"])
       foo
   0     1
   1  None
   
   >>> pd.DataFrame(data=[{"foo": 1}, {"foo": None}], dtype=object, columns=["bar"])
      bar
   0  NaN
   1  NaN
   ``` 



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