TSColumnTransformer¶
-
class
hcrystalball.compose.
TSColumnTransformer
(**kwargs)[source]¶ Bases:
sklearn.compose._column_transformer.ColumnTransformer
Time Series compatible ColumnTransformer.
Allow usage of hcrystalball wrappers and index based transformers. See also:
sklearn.compose.ColumnTransformer
- Returns
Data transformed on given column
- Return type
- Raises
ValueError – If
remainder=='passthrough'
is set. Usepassthrough
as an identity estimator If sparse output is requested, but not all columns are numeric
Attributes Summary
Access the fitted transformer by name.
Access to original remainder
Methods Summary
fit
(X[, y])Fit all transformers using X.
fit_transform
(X[, y])Run index aware fit_transform
Get feature names from all transformers.
get_params
([deep])Get parameters for this estimator.
set_params
(**kwargs)Set the parameters of this estimator.
transform
(X)Run index aware transform
Attributes Documentation
-
named_transformers_
¶ Access the fitted transformer by name.
Read-only attribute to access any transformer by given name. Keys are transformer names and values are the fitted transformer objects.
-
remainder
¶ Access to original remainder
Methods Documentation
-
fit
(X, y=None)¶ 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
-
fit_transform
(X, y=None)[source]¶ Run index aware fit_transform
- Parameters
X (pandas.DataFrame) – Input features.
y (pandas.Series or numpy.array) – Target values
- Returns
Transformed data by given transformer on given column
- Return type
-
get_feature_names
()[source]¶ Get feature names from all transformers.
- Returns
feature_names – Names of the features produced by transform.
- Return type
list of strings
-
get_params
(deep=True)¶ Get parameters for this estimator.
-
set_params
(**kwargs)¶ Set the parameters of this estimator.
Valid parameter keys can be listed with
get_params()
.- Returns
- Return type
self
-
transform
(X)[source]¶ Run index aware transform
- Parameters
X (pandas.DataFrame) – Input features.
- Returns
Transformed data by given transformer on given column
- Return type