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    Class SimpleImputer (1.35.0) 

      SimpleImputer 
 ( 
 strategy 
 : 
 typing 
 . 
 Literal 
 [ 
 "mean" 
 , 
 "median" 
 , 
 "most_frequent" 
 ] 
 = 
 "mean" 
 )

    Univariate imputer for completing missing values with simple strategies.

    Replace missing values using a descriptive statistic (e.g. mean, median, or most frequent) along each column.

    Examples:

     >>> import bigframes.pandas as bpd
>>> from bigframes.ml.impute import SimpleImputer
>>> bpd.options.display.progress_bar = None
>>> X_train = bpd.DataFrame({"feat0": [7.0, 4.0, 10.0], "feat1": [2.0, None, 5.0], "feat2": [3.0, 6.0, 9.0]})
>>> imp_mean = SimpleImputer().fit(X_train)
>>> X_test = bpd.DataFrame({"feat0": [None, 4.0, 10.0], "feat1": [2.0, None, None], "feat2": [3.0, 6.0, 9.0]})
>>> imp_mean.transform(X_test)
   imputer_feat0  imputer_feat1  imputer_feat2
0            7.0            2.0            3.0
1            4.0            3.5            6.0
2           10.0            3.5            9.0
<BLANKLINE>
[3 rows x 3 columns]

    Parameter

    Name
    Description
    strategy
    {'mean', 'median', 'most_frequent'}, default='mean'

    The imputation strategy. 'mean': replace missing values using the mean along the axis. 'median':replace missing values using the median along the axis. 'most_frequent', replace missing using the most frequent value along the axis.

    Methods

    __repr__

      __repr__ 
 ()

    Print the estimator's constructor with all non-default parameter values.

    fit

      fit 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 , 
 pandas 
 . 
 core 
 . 
 frame 
 . 
 DataFrame 
 , 
 pandas 
 . 
 core 
 . 
 series 
 . 
 Series 
 , 
 ], 
 y 
 = 
 None 
 , 
 ) 
 - 
> bigframes 
 . 
 ml 
 . 
 impute 
 . 
 SimpleImputer

    Fit the imputer on X.

    Parameters
    Name
    Description
    X
    bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series

    The Dataframe or Series with training data.

    y
    default None

    Ignored.

    Returns
    Type
    Description
    SimpleImputer
    Fitted scaler.

    fit_transform

      fit_transform 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 , 
 pandas 
 . 
 core 
 . 
 frame 
 . 
 DataFrame 
 , 
 pandas 
 . 
 core 
 . 
 series 
 . 
 Series 
 , 
 ], 
 y 
 : 
 typing 
 . 
 Optional 
 [ 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 , 
 pandas 
 . 
 core 
 . 
 frame 
 . 
 DataFrame 
 , 
 pandas 
 . 
 core 
 . 
 series 
 . 
 Series 
 , 
 ] 
 ] 
 = 
 None 
 , 
 ) 
 - 
> bigframes 
 . 
 dataframe 
 . 
 DataFrame

    Fit to data, then transform it.

    Parameters
    Name
    Description
    X
    bigframes.dataframe.DataFrame or bigframes.series.Series

    Series or DataFrame of shape (n_samples, n_features). Input samples.

    y
    bigframes.dataframe.DataFrame or bigframes.series.Series

    Series or DataFrame of shape (n_samples,) or (n_samples, n_outputs). Default None. Target values (None for unsupervised transformations).

    Returns
    Type
    Description
    bigframes.dataframe.DataFrame
    DataFrame of shape (n_samples, n_features_new). Transformed DataFrame.

    get_params

      get_params 
 ( 
 deep 
 : 
 bool 
 = 
 True 
 ) 
 - 
> typing 
 . 
 Dict 
 [ 
 str 
 , 
 typing 
 . 
 Any 
 ]

    Get parameters for this estimator.

    Parameter
    Name
    Description
    deep
    bool, default True

    Default True . If True, will return the parameters for this estimator and contained subobjects that are estimators.

    Returns
    Type
    Description
    Dictionary
    A dictionary of parameter names mapped to their values.

    to_gbq

      to_gbq 
 ( 
 model_name 
 : 
 str 
 , 
 replace 
 : 
 bool 
 = 
 False 
 ) 
 - 
> bigframes 
 . 
 ml 
 . 
 base 
 . 
 _T

    Save the transformer as a BigQuery model.

    Parameters
    Name
    Description
    model_name
    str

    The name of the model.

    replace
    bool, default False

    Determine whether to replace if the model already exists. Default to False.

    transform

      transform 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 , 
 pandas 
 . 
 core 
 . 
 frame 
 . 
 DataFrame 
 , 
 pandas 
 . 
 core 
 . 
 series 
 . 
 Series 
 , 
 ], 
 ) 
 - 
> bigframes 
 . 
 dataframe 
 . 
 DataFrame

    Impute all missing values in X.

    Parameter
    Name
    Description
    X
    bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series

    The DataFrame or Series to be transformed.

    Returns
    Type
    Description
    bigframes.dataframe.DataFrame
    Transformed result.
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