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Commit fe5245b

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tswastgemini-code-assist[bot]
tswast
and
gemini-code-assist[bot]
authored
fix: avoid copy argument warning in to_pandas (#16917)
Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly: - [ ] Make sure to open an issue as a [bug/issue](https://github.com/googleapis/google-cloud-python/issues) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [ ] Ensure the tests and linter pass - [ ] Code coverage does not decrease (if any source code was changed) - [ ] Appropriate docs were updated (if necessary) Fixes internal issue b/508671576 🦕 --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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2 files changed

+5-3Lines changed: 5 additions & 3 deletions

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‎packages/bigframes/bigframes/core/blocks.py‎

Copy file name to clipboardExpand all lines: packages/bigframes/bigframes/core/blocks.py
+1-1Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -848,7 +848,7 @@ def _materialize_local(
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else:
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raw_df = result_batches.to_pandas()
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df = self._copy_index_to_pandas(raw_df)
851-
df.set_axis(self.column_labels, axis=1, copy=False)
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df.columns = self.column_labels
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return df, execute_result.query_job
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854854
def split(
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‎packages/bigframes/bigframes/dataframe.py‎

Copy file name to clipboardExpand all lines: packages/bigframes/bigframes/dataframe.py
+4-2Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1743,7 +1743,8 @@ def to_pandas(
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)
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if query_job:
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self._set_internal_query_job(query_job)
1746-
return df.set_axis(self._block.column_labels, axis=1, copy=False)
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df.columns = self._block.column_labels
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return df
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17481749
def to_pandas_batches(
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self,
@@ -1869,7 +1870,8 @@ def peek(
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raise ValueError(
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"Cannot peek efficiently when data has aggregates, joins or window functions applied. Use force=True to fully compute dataframe."
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)
1872-
return maybe_result.set_axis(self._block.column_labels, axis=1, copy=False)
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maybe_result.columns = self._block.column_labels
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return maybe_result
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18741876
def nlargest(
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self,

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