User Guide Foreword The need for causal inference Introduction to DoWhy Modeling Causal Relations Performing Causal Tasks Estimating Causal Effects Effect Estimation Using specific Effect Estimators (for ACE, mediation effect, …) Estimating Average Causal Effects using GCM Explaining Observed Effects and Root-Cause Analysis Outlier Attribution Attributing Distributional Changes Quantifying Intrinsic Causal Influence Unit Change Attribution Feature Attribution Asking and Answering What-If Questions Interventions Computing Counterfactuals Miscellaneous Topics Customizing Causal Mechanism Assignment Using ground truth models Estimating Confidence Intervals How to use it Computing confidence intervals for causal queries Conveniently bootstrapping graph training on random subsets of training data Runtime cost versus confidence Understanding the need for confidence intervals Generate samples from a GCM Citing this package