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Merge pull request #139 from scikit-learn-contrib/dev
doc examples patched
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examples/tutorials/plot_tuto_categorical.py

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# ---------------------------------------------------------------
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# We get the data and focus on the explanatory variables
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df = data.get_data("Titanic")
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df = df.drop(columns=["survived"])
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df = df.drop(columns=["Survived"])
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# %%
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# 2. Mixed type imputation methods

qolmat/utils/data.py

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@@ -324,7 +324,7 @@ def add_holes(df: pd.DataFrame, ratio_masked: float, mean_size: int) -> pd.DataF
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pd.DataFrame
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dataframe with missing values
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"""
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groups = df.index.names.difference(["datetime", "date", "index"])
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groups = df.index.names.difference(["datetime", "date", "index", None])
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if groups != []:
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generator = missing_patterns.GeometricHoleGenerator(
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1, ratio_masked=ratio_masked, subset=df.columns, groups=groups

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