bigframes.ml.decomposition.PCA.components_#
- property PCA.components_: DataFrame#
Principal axes in feature space, representing the directions of maximum variance in the data.
- Returns:
- DataFrame of principal components, containing following columns:
principal_component_id: An integer that identifies the principal component.
feature: The column name that contains the feature.
numerical_value: If feature is numeric, the value of feature for the principal component that principal_component_id identifies. If feature isn’t numeric, the value is NULL.
- categorical_value: A list of mappings containing information about categorical features. Each mapping contains the following fields:
categorical_value.category: The name of each category.
categorical_value.value: The value of categorical_value.category for the centroid that centroid_id identifies.
The output contains one row per feature per component.
- Return type: