auto_prep package

Subpackages

• auto_prep.modeling package
  • Submodules
  • auto_prep.modeling.handler module
    • ModelHandler
      • ModelHandler.generate_shap()
      • ModelHandler.load_models()
      • ModelHandler.load_modules()
      • ModelHandler.load_pipelines()
      • ModelHandler.run()
      • ModelHandler.tune_model()
      • ModelHandler.write_to_raport()
    • custom_sort()
    • format_shape()
  • auto_prep.modeling.model_BayesianRidgeRegressor module
    • ModelBayesianRidgeRegressor
      • ModelBayesianRidgeRegressor.PARAM_GRID
      • ModelBayesianRidgeRegressor.to_tex()
      • ModelBayesianRidgeRegressor.PARAM_GRID
      • ModelBayesianRidgeRegressor.set_fit_request()
      • ModelBayesianRidgeRegressor.set_predict_request()
      • ModelBayesianRidgeRegressor.set_score_request()
      • ModelBayesianRidgeRegressor.to_tex()
  • auto_prep.modeling.model_DecisionTreeClassifier module
    • ModelDecisionTreeClassifier
      • ModelDecisionTreeClassifier.PARAM_GRID
      • ModelDecisionTreeClassifier.to_tex()
      • ModelDecisionTreeClassifier.PARAM_GRID
      • ModelDecisionTreeClassifier.set_fit_request()
      • ModelDecisionTreeClassifier.set_predict_proba_request()
      • ModelDecisionTreeClassifier.set_predict_request()
      • ModelDecisionTreeClassifier.set_score_request()
      • ModelDecisionTreeClassifier.to_tex()
  • auto_prep.modeling.model_GaussianNaiveClassifier module
    • ModelGaussianNaiveClassifier
      • ModelGaussianNaiveClassifier.__init__()
      • ModelGaussianNaiveClassifier.to_tex()
      • ModelGaussianNaiveClassifier.PARAM_GRID
      • ModelGaussianNaiveClassifier.set_fit_request()
      • ModelGaussianNaiveClassifier.set_partial_fit_request()
      • ModelGaussianNaiveClassifier.set_score_request()
      • ModelGaussianNaiveClassifier.to_tex()
  • auto_prep.modeling.model_GradientBoostingRegressor module
    • ModelGradientBoostingRegressor
      • ModelGradientBoostingRegressor.__init__()
      • ModelGradientBoostingRegressor.to_tex()
      • ModelGradientBoostingRegressor.PARAM_GRID
      • ModelGradientBoostingRegressor.set_fit_request()
      • ModelGradientBoostingRegressor.set_score_request()
      • ModelGradientBoostingRegressor.to_tex()
  • auto_prep.modeling.model_KNeighboursClassifier module
    • ModelKNeighboursClassifier
      • ModelKNeighboursClassifier.__init__()
      • ModelKNeighboursClassifier.to_tex()
      • ModelKNeighboursClassifier.PARAM_GRID
      • ModelKNeighboursClassifier.set_score_request()
      • ModelKNeighboursClassifier.to_tex()
  • auto_prep.modeling.model_KNeighboursRegressor module
    • ModelKNeighboursRegressor
      • ModelKNeighboursRegressor.__init__()
      • ModelKNeighboursRegressor.to_tex()
      • ModelKNeighboursRegressor.PARAM_GRID
      • ModelKNeighboursRegressor.set_score_request()
      • ModelKNeighboursRegressor.to_tex()
  • auto_prep.modeling.model_LinearRegression module
    • ModelLinearRegression
      • ModelLinearRegression.PARAM_GRID
      • ModelLinearRegression.set_fit_request()
      • ModelLinearRegression.set_score_request()
      • ModelLinearRegression.to_tex()
  • auto_prep.modeling.model_LinearSVR module
    • ModelLinearSVR
      • ModelLinearSVR.PARAM_GRID
      • ModelLinearSVR.set_fit_request()
      • ModelLinearSVR.set_score_request()
      • ModelLinearSVR.to_tex()
  • auto_prep.modeling.model_LogisticRegression module
    • ModelLogisticRegression
      • ModelLogisticRegression.PARAM_GRID
      • ModelLogisticRegression.set_fit_request()
      • ModelLogisticRegression.set_score_request()
      • ModelLogisticRegression.to_tex()
  • auto_prep.modeling.model_RandomForestRegressor module
    • ModelRandomForestRegressor
      • ModelRandomForestRegressor.__init__()
      • ModelRandomForestRegressor.to_tex()
      • ModelRandomForestRegressor.PARAM_GRID
      • ModelRandomForestRegressor.set_fit_request()
      • ModelRandomForestRegressor.set_score_request()
      • ModelRandomForestRegressor.to_tex()
  • auto_prep.modeling.model_SVC module
    • ModelSVC
      • ModelSVC.__init__()
      • ModelSVC.to_tex()
      • ModelSVC.PARAM_GRID
      • ModelSVC.set_fit_request()
      • ModelSVC.set_score_request()
      • ModelSVC.to_tex()
  • auto_prep.modeling.model_XGBoost module
  • Module contents
• auto_prep.preprocessing package
  • Submodules
  • auto_prep.preprocessing.abstract module
    • DimentionReducer
      • DimentionReducer.fit()
      • DimentionReducer.fit_transform()
      • DimentionReducer.to_tex()
      • DimentionReducer.transform()
    • FeatureImportanceSelector
      • FeatureImportanceSelector.k
      • FeatureImportanceSelector.selected_columns
      • FeatureImportanceSelector.fit()
      • FeatureImportanceSelector.fit_transform()
      • FeatureImportanceSelector.transform()
  • auto_prep.preprocessing.binning module
    • BinningTransformer
      • BinningTransformer.threshold
      • BinningTransformer.should_bin
      • BinningTransformer.bin_edges
      • BinningTransformer.PARAMS_GRID
      • BinningTransformer.fit()
      • BinningTransformer.fit_transform()
      • BinningTransformer.is_numeric()
      • BinningTransformer.to_tex()
      • BinningTransformer.transform()
  • auto_prep.preprocessing.correlation_filtering module
    • CorrelationFilter
      • CorrelationFilter.dropped_columns
      • CorrelationFilter.fit()
      • CorrelationFilter.fit_transform()
      • CorrelationFilter.to_tex()
      • CorrelationFilter.transform()
  • auto_prep.preprocessing.dimention_reducing module
    • PCADimentionReducer
      • PCADimentionReducer.fit()
      • PCADimentionReducer.fit_transform()
      • PCADimentionReducer.to_tex()
      • PCADimentionReducer.transform()
    • UMAPDimentionReducer
      • UMAPDimentionReducer.fit()
      • UMAPDimentionReducer.fit_transform()
      • UMAPDimentionReducer.to_tex()
      • UMAPDimentionReducer.transform()
    • VIFDimentionReducer
      • VIFDimentionReducer.fit()
      • VIFDimentionReducer.fit_transform()
      • VIFDimentionReducer.to_tex()
      • VIFDimentionReducer.transform()
  • auto_prep.preprocessing.encoding module
    • ColumnEncoder
      • ColumnEncoder.encoders
      • ColumnEncoder.columns
      • ColumnEncoder.fit()
      • ColumnEncoder.fit_transform()
      • ColumnEncoder.to_tex()
      • ColumnEncoder.transform()
  • auto_prep.preprocessing.feature_selecting module
    • CorrelationSelector
      • CorrelationSelector.selected_columns
      • CorrelationSelector.fit()
      • CorrelationSelector.fit_transform()
      • CorrelationSelector.is_numerical()
      • CorrelationSelector.to_tex()
      • CorrelationSelector.transform()
    • FeatureImportanceClassSelector
      • FeatureImportanceClassSelector.k
      • FeatureImportanceClassSelector.selected_columns
      • FeatureImportanceClassSelector.fit()
      • FeatureImportanceClassSelector.fit_transform()
      • FeatureImportanceClassSelector.to_tex()
      • FeatureImportanceClassSelector.transform()
    • FeatureImportanceRegressSelector
      • FeatureImportanceRegressSelector.k
      • FeatureImportanceRegressSelector.selected_columns
      • FeatureImportanceRegressSelector.fit()
      • FeatureImportanceRegressSelector.fit_transform()
      • FeatureImportanceRegressSelector.to_tex()
      • FeatureImportanceRegressSelector.transform()
  • auto_prep.preprocessing.handler module
    • PreprocessingHandler
      • PreprocessingHandler.run()
      • PreprocessingHandler.score_pipeline_with_model()
      • PreprocessingHandler.write_to_raport()
  • auto_prep.preprocessing.imputing module
    • NAImputer
      • NAImputer.numeric_features
      • NAImputer.categorical_features
      • NAImputer.fit()
      • NAImputer.fit_transform()
      • NAImputer.to_tex()
      • NAImputer.transform()
  • auto_prep.preprocessing.outlier_detecting module
    • OutlierDetector
      • OutlierDetector.fit()
      • OutlierDetector.fit_transform()
      • OutlierDetector.to_tex()
      • OutlierDetector.transform()
  • auto_prep.preprocessing.redundancy_filtering module
    • UniqueFilter
      • UniqueFilter.dropped_columns
      • UniqueFilter.fit()
      • UniqueFilter.fit_transform()
      • UniqueFilter.to_tex()
      • UniqueFilter.transform()
  • auto_prep.preprocessing.scaling module
    • ColumnScaler
      • ColumnScaler.scaler
      • ColumnScaler.PARAMS_GRID
      • ColumnScaler.fit()
      • ColumnScaler.fit_transform()
      • ColumnScaler.is_numerical()
      • ColumnScaler.to_tex()
      • ColumnScaler.transform()
  • auto_prep.preprocessing.utils module
    • TolerantLabelEncoder
      • TolerantLabelEncoder.inverse_transform()
      • TolerantLabelEncoder.set_transform_request()
      • TolerantLabelEncoder.transform()
  • auto_prep.preprocessing.variance_filtering module
    • VarianceFilter
      • VarianceFilter.dropped_columns
      • VarianceFilter.fit()
      • VarianceFilter.fit_transform()
      • VarianceFilter.to_tex()
      • VarianceFilter.transform()
  • Module contents
• auto_prep.raporting package
  • Submodules
  • auto_prep.raporting.eda module
    • EdaRaport
      • EdaRaport.run()
      • EdaRaport.visualizers
      • EdaRaport.write_to_raport()
  • auto_prep.raporting.overview module
    • OverviewRaport
      • OverviewRaport.run()
      • OverviewRaport.write_to_raport()
  • auto_prep.raporting.raport module
    • Raport
      • Raport.add_figure()
      • Raport.add_header()
      • Raport.add_list()
      • Raport.add_reference()
      • Raport.add_section()
      • Raport.add_subsection()
      • Raport.add_table()
      • Raport.add_text()
      • Raport.add_verbatim()
      • Raport.generate()
  • Module contents
• auto_prep.utils package
  • Submodules
  • auto_prep.utils.abstract module
    • Categorical
    • Classifier
    • ModulesHandler
      • ModulesHandler.construct_pipelines_steps()
      • ModulesHandler.construct_pipelines_steps_helper()
      • ModulesHandler.get_subpackage()
      • ModulesHandler.load_classes()
      • ModulesHandler.supported_combinations
      • ModulesHandler.supported_interfaces
    • NonRequiredStep
    • Numerical
    • NumericalCategorical
    • Regressor
    • RequiredStep
    • Step
      • Step.to_tex()
  • auto_prep.utils.config module
    • GlobalConfig
      • GlobalConfig.prepare_dir()
      • GlobalConfig.set()
      • GlobalConfig.update()
  • auto_prep.utils.logging_config module
    • ColoredFormatter
      • ColoredFormatter.format()
    • TimedLogger
      • TimedLogger.end_operation()
      • TimedLogger.start_operation()
    • setup_logger()
  • auto_prep.utils.other module
    • get_scoring()
    • save_chart()
    • save_json()
    • save_model()
  • auto_prep.utils.system module
    • get_system_info()
  • Module contents
• auto_prep.visualization package
  • Submodules
  • auto_prep.visualization.categorical module
    • CategoricalVisualizer
      • CategoricalVisualizer.categorical_distribution_chart()
      • CategoricalVisualizer.order
  • auto_prep.visualization.eda module
    • EdaVisualizer
      • EdaVisualizer.missing_values_chart()
      • EdaVisualizer.order
      • EdaVisualizer.target_distribution_chart()
  • auto_prep.visualization.numerical module
    • NumericalVisualizer
      • NumericalVisualizer.correlation_heatmap_chart()
      • NumericalVisualizer.numerical_distribution_chart()
      • NumericalVisualizer.numerical_features_boxplot_chart()
      • NumericalVisualizer.order
  • Module contents

Submodules

auto_prep.prep module

class auto_prep.prep.AutoPrep

Bases: object

Main pipeline orchestrating the entire preprocessing process.

This class handles the complete workflow from data preprocessing to report generation.

run(data: DataFrame, target_column: str)

Run the complete pipeline on the provided dataset.

Parameters:

• data (pd.DataFrame) – Input dataset to process.

• target_column (str) – Name of the target variable column.

auto_prep.prep.format_column_name(x)

Module contents