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.
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], y=None
) -> bigframes.ml.impute.SimpleImputer
Fit the imputer on X.
Parameters | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.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],
y: typing.Optional[
typing.Union[bigframes.dataframe.DataFrame, bigframes.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 |
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]
) -> bigframes.dataframe.DataFrame
Impute all missing values in X.
Parameter | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series
The DataFrame or Series to be transformed. |
Returns | |
---|---|
Type | Description |
bigframes.dataframe.DataFrame |
Transformed result. |