PERF-#6696: Use cached dtypes in fillna when possible. #6697
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AndreyPavlenko
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devin-petersohn,
mvashishtha,
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anmyachev,
dchigarev and
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anmyachev
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Nov 6, 2023
dchigarev
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Nov 7, 2023
Signed-off-by: Andrey Pavlenko <[email protected]>
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dchigarev
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Nov 13, 2023
dchigarev
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Nov 13, 2023
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| dtype = pandas.Series(value).dtype | ||
| if all( | ||
| find_common_type([t, dtype]) == t for t in self._modin_frame.dtypes | ||
| ): | ||
| new_dtypes = self._modin_frame.dtypes |
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why can't we simply fill new dtypes with the find_common_type results?
Suggested change
| dtype = pandas.Series(value).dtype | |
| if all( | |
| find_common_type([t, dtype]) == t for t in self._modin_frame.dtypes | |
| ): | |
| new_dtypes = self._modin_frame.dtypes | |
| dtype = pandas.Series(value).dtype | |
| new_dtypes = pandas.Series({col: find_common_type([t, dtype]) for col, t in self._modin_frame.dtypes.items()}) |
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Because the new dtype depends on whether there are NAs in the frame or not. If there no NAs, the dtype is not changed, otherwise, it's changed to the common. We can't analyze the data here, but we can make the assumption, that the dtype will not changed if it's already the common one.
dchigarev
reviewed
Nov 13, 2023
| value_dtypes = pandas.DataFrame( | ||
| {k: [v] for (k, v) in value.items()} | ||
| ).dtypes | ||
| if all( |
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What do these changes do?
flake8 modin/ asv_bench/benchmarks scripts/doc_checker.pyblack --check modin/ asv_bench/benchmarks scripts/doc_checker.pygit commit -sdocs/development/architecture.rstis up-to-date