performing-causal-analysis

# Performing Causal Analysis Executes causal analysis using CausalPy experiment classes. ## Workflow 1. **Load Data**: Ensure data is in a Pandas DataFrame. 2. **Initialize Experiment**: Use the appropriate class (see References). 3. **Fit & Model**: Models are fitted automatically upon initialization if arguments are provided. 4. **Analyze Results**: Use `summary()`, `print_coefficients()`, and `plot()`. ## Core Methods * `experiment.summary()`: Prints model summary and main results. * `experiment.plot()`: Visualizes observed vs. counterfactual. * `experiment.print_coefficients()`: Shows model coefficients. ## References Detailed usage for specific methods: * [Difference-in-Differences](reference/diff_in_diff.md) * [Interrupted Time Series](reference/interrupted_time_series.md) * [Synthetic Control](reference/synthetic_control.md)