fix: fix read_gbq_function issue in dataframe apply method #1174
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| @@ -3674,7 +3674,11 @@ def apply(self, func, *, axis=0, args: typing.Tuple = (), **kwargs): | |||
| return result_series | |||
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| # Per-column apply | |||
| results = {name: func(col, *args, **kwargs) for name, col in self.items()} | |||
| if hasattr(func, "bigframes_remote_function"): | |||
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@TrevorBergeron could you please review if this element-wise proxy for series-wise application doesn't have any blind sight?
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Isn't dataframe.apply for column or series-wise application? Why do we need to support applying as an element-wise operator? isn't this what dataframe.map is for?
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For scalar ops the end result is the same. I think we don't lose anything by being lax for user convenience. Note that this API has other non-pandas-like extended behavior
python-bigquery-dataframes/bigframes/dataframe.py
Line 3933 in e0a8288
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| func_ref = session.read_gbq_function("bqutil.fn.cw_lower_case_ascii_only") | ||
| bf_result = bdf.apply(func_ref).to_pandas() | ||
| # The str.lower() method has the same functionality as func_ref. |
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This is true for ASCII only, we should say that in the comment
See the description/example from b/379750234.
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Fixes #<issue_number_goes_here> 🦕