iaml.actionables.features_precleaning.act_normalize_column_names¶
[STEP] Normalize column names
Classes¶
[STEP] Normalize column names |
Module Contents¶
- class iaml.actionables.features_precleaning.act_normalize_column_names.ActNormalizeColumnNames¶
Bases:
iaml.actionable.Actionable[STEP] Normalize column names
- name: str = 'Normalize column names'¶
Step’s name.
- refs = []¶
List of references for this step.
- configuration¶
Configuration of this step (equivalent to hyperparameters for models).
- columns: list = None¶
- normalized_columns: list[str] = None¶
- fit(dataset: iaml.dataset.Dataset) iaml.actionable.Actionable¶
Fits the step on the given dataset.
- Parameters:
dataset (Dataset) – Features and labels.
- Returns:
Fitted step.
- transform(X: pandas.DataFrame) pandas.DataFrame¶
Normalize column names.
- Parameters:
X (pd.DataFrame) – DataFrame to transform.
- Returns:
Transformed dataset.
- suitable(dataset: iaml.dataset.Dataset) bool¶
Evaluates whether the step is suitable to run with the given dataset.
- Parameters:
dataset (Dataset) – Dataset to evaluate on.
- Returns:
Whether the step is suitable to run.
- priorize(candidate: iaml.candidate.Candidate = None) float¶
Evaluates the priority of the step within a pipeline. 0 means the execution of the step should not be prioritized, and 1 means it should be executed early in the pipeline.
- Parameters:
candidate (Candidate, optional) – Candidate on which the priority should be evaluated.
- Returns:
Value between 0 and 1.