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ColumnTransformer(
transformers: typing.Iterable[
typing.Tuple[
str,
typing.Union[
bigframes.ml.preprocessing.OneHotEncoder,
bigframes.ml.preprocessing.StandardScaler,
bigframes.ml.preprocessing.MaxAbsScaler,
bigframes.ml.preprocessing.MinMaxScaler,
bigframes.ml.preprocessing.KBinsDiscretizer,
bigframes.ml.preprocessing.LabelEncoder,
bigframes.ml.preprocessing.PolynomialFeatures,
bigframes.ml.impute.SimpleImputer,
bigframes.ml.compose.SQLScalarColumnTransformer,
],
typing.Union[str, typing.Iterable[str]],
]
]
)
Applies transformers to columns of BigQuery DataFrames.
This estimator allows different columns or column subsets of the input to be transformed separately, and the features generated by each transformer will be concatenated to form a single feature space. This is useful for heterogeneous or columnar data to combine several feature extraction mechanisms or transformations into a single transformer.
Properties
transformers_
The collection of transformers as tuples of (name, transformer, column).
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.compose.ColumnTransformer
Fit all transformers using X.
Parameter | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series
The Series or DataFrame of shape (n_samples, n_features). Training vector, where |
Returns | |
---|---|
Type | Description |
ColumnTransformer |
Fitted estimator. |
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
API documentation for fit_transform
method.
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 |
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
Transform X separately by each transformer, concatenate results.
Parameter | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series
The Series or DataFrame to be transformed by subset. |
Returns | |
---|---|
Type | Description |
bigframes.dataframe.DataFrame |
Transformed result. |