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Performance regressions in GroupBy.fillna #38358

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TomAugspurger opened this issue Dec 8, 2020 · 5 comments
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Performance regressions in GroupBy.fillna #38358

TomAugspurger opened this issue Dec 8, 2020 · 5 comments
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Groupby Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Performance Memory or execution speed performance Regression Functionality that used to work in a prior pandas version

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@TomAugspurger
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https://pandas.pydata.org/speed/pandas/#groupby.FillNA.time_df_ffill?python=3.8&Cython=0.29.21&commits=03e58585

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cc @GYHHAHA
@TomAugspurger TomAugspurger added Groupby Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Performance Memory or execution speed performance Regression Functionality that used to work in a prior pandas version labels Dec 8, 2020
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GYHHAHA commented Dec 8, 2020

take

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GYHHAHA commented Dec 11, 2020

Is there a faster way to get the df with dropping the NaN group?
I try to use the indice operation to replace calling filter, but still slow.
Any suggestion? Thanks! @TomAugspurger

@TomAugspurger
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TomAugspurger commented Dec 11, 2020 via email

@mzeitlin11 mzeitlin11 mentioned this issue Sep 15, 2021
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@jreback
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jreback commented Sep 15, 2021

could be fixed by #43578

cc @mzeitlin11 @jbrockmendel

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closed by #43578

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Groupby Missing-data np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate Performance Memory or execution speed performance Regression Functionality that used to work in a prior pandas version
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