TSCColumnTransformer

class datafold.dynfold.TSCColumnTransformer(transformers, *, remainder='drop', n_jobs=None, transformer_weights=None, verbose=False, verbose_feature_names_out=True)

Bases: ColumnTransformer, TSCTransformerMixin

A column transformer for time series data.

This class is a wrapper class of scikit-learn’s ColumnTransformer and adopted for TSCDataFrame in the pipeline.

For the undocumented attributes please go to the base class documentation ColumnTransformer.

Note

The parameter sparse_threshold of the super class is not supported.

Parameters:

transformers (list[tuple]) – All transformers included in the list must be able to process TSCDataFrame. See base class for the detailed specification of the tuple.

Attributes Summary

n_features_out_

Methods Summary

fit(X[, y])	Fit all transformers using X.
partial_fit(X[, y])

Attributes Documentation

n_features_out_

Methods Documentation

fit(X, y=None, **fit_params)

Fit all transformers using X.

Parameters:

• X ({array-like, dataframe} of shape (n_samples, n_features)) – Input data, of which specified subsets are used to fit the transformers.

• y (array-like of shape (n_samples,...), default=None) – Targets for supervised learning.

Returns:

self – This estimator.

Return type:

ColumnTransformer

partial_fit(X, y=None, **fit_params)