Compute DID estimate and pretrend flag

You are given three equal-length arrays describing observations from a panel-like dataset: - `period[i]` ∈ {0,1}: 0 = pre period, 1 = post period - `treat[i]` ∈ {0,1}: 1 = treated group, 0 = control group - `y[i]` (float): outcome Tasks: A) Compute the **difference-in-differences (DID)** estimate of the treatment effect: \[ \text{DID} = (\bar y_{post,treated} - \bar y_{pre,treated}) - (\bar y_{post,control} - \bar y_{pre,control}) \] B) Compute a simple **pretrend flag**: - Let \(d_{pre} = \bar y_{pre,treated} - \bar y_{pre,control}\). - Given a scalar `threshold` ≥ 0, return `pretrend=True` if \(|d_{pre}| > threshold\), else `False`. Assumptions/requirements: - Use simple means over the subsets implied by (`period`, `treat`). - Describe how you would handle missing cells (e.g., no treated observations in pre period).