class_docstr: Manager for generating causal analyses from a dataset.
class_docstr_tok: ["Manager","for","generating","causal","analyses","from","a","dataset","."]
docstr: Construct a CausalManager for generating causal analyses
      from a dataset.
  :param train: Dataset on which to compute global causal effects
      (#samples x #features).
  :type train: pandas.DataFrame
  :param test: Dataset on which to compute local causal effects
      (#samples x #features).
  :type test: pandas.DataFrame
  :param target_column: The name of the label column.
  :type target_column: str
  :param task_type: Task type is either 'classification/regression'
  :type task_type: str
  :param categorical_features: All categorical feature names.
  :type categorical_features: list
  :param feature_metadata: Feature metadata for the train/test
                           dataset to identify different kinds
                           of features in the dataset.
  :type feature_metadata: FeatureMetadata
docstr_tok: ["Construct","a","CausalManager","for","generating","causal","analyses","from","a","dataset",".",":","param","train",":","Dataset","on","which","to","compute","global","causal","effects","(","#","samples","x","#","features",")",".",":","type","train",":","pandas.DataFrame",":","param","test",":","Dataset","on","which","to","compute","local","causal","effects","(","#","samples","x","#","features",")",".",":","type","test",":","pandas.DataFrame",":","param","target_column",":","The","name","of","the","label","column",".",":","type","target_column",":","str",":","param","task_type",":","Task","type","is","either","'classification\/regression'",":","type","task_type",":","str",":","param","categorical_features",":","All","categorical","feature","names",".",":","type","categorical_features",":","list",":","param","feature_metadata",":","Feature","metadata","for","the","train\/test","dataset","to","identify","different","kinds","of","features","in","the","dataset",".",":","type","feature_metadata",":","FeatureMetadata"]
code: def __init__(
      self,
      train: pd.DataFrame,
      test: pd.DataFrame,
      target_column: str,
      task_type: str,
      categorical_features: Optional[List[str]],
      feature_metadata: Optional[FeatureMetadata] = None,
  ):
      """Construct a CausalManager for generating causal analyses
          from a dataset.
      :param train: Dataset on which to compute global causal effects
          (#samples x #features).
      :type train: pandas.DataFrame
      :param test: Dataset on which to compute local causal effects
          (#samples x #features).
      :type test: pandas.DataFrame
      :param target_column: The name of the label column.
      :type target_column: str
      :param task_type: Task type is either 'classification/regression'
      :type task_type: str
      :param categorical_features: All categorical feature names.
      :type categorical_features: list
      :param feature_metadata: Feature metadata for the train/test
                               dataset to identify different kinds
                               of features in the dataset.
      :type feature_metadata: FeatureMetadata
      """
      self._train = train
      self._test = test
      self._target_column = target_column
      self._task_type = task_type
  
      self._categorical_features = categorical_features
      if categorical_features is None:
          self._categorical_features = []
      self._feature_metadata = feature_metadata
  
      self._results = []
  
imports: from pathlib import Path
  from typing import Any, List, Optional, Union
  import numpy
  import pandas
  from econml.solutions.causal_analysis import CausalAnalysis
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask
  from responsibleai._data_validations import validate_train_test_categories
  from responsibleai._internal.constants import CausalManagerKeys, ListProperties, ManagerNames
  from responsibleai._tools.causal.causal_config import CausalConfig
  from responsibleai._tools.causal.causal_constants import DefaultParams, ModelTypes
  from responsibleai._tools.causal.causal_result import CausalResult
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.feature_metadata import FeatureMetadata
  from responsibleai.managers.base_manager import BaseManager
  from responsibleai.utils import _find_features_having_missing_values, _measure_time
label_desc: Use image node_id 1 to create a new CausalManager object from inherited base classes: BaseManager with example: obj = CausalManager(train, test, target_column, task_type, categorical_features, feature_metadata)