Update app.py

app.py

@@ -37,7 +37,21 @@ def _airline_passengers() -> pd.DataFrame:
         import statsmodels.api as sm
         data = sm.datasets.get_rdataset("AirPassengers", "datasets").data
         dates = pd.date_range(start="1949-01-01", periods=len(data), freq="MS")
-        return pd.DataFrame({"ds": dates, "y": data.iloc[:, 0].values})
+        # Prefer common value column names from Rdatasets
+        candidate_cols = [c for c in ["value", "passengers", "x"] if c in data.columns]
+        
+        if candidate_cols:
+            y = pd.to_numeric(data[candidate_cols[0]], errors="coerce").to_numpy()
+        else:
+            # Fallback: take the last numeric column (and avoid obvious time columns)
+            numeric_cols = data.select_dtypes(include=["number"]).columns.tolist()
+            drop_cols = [c for c in ["time", "date", "year", "month"] if c in numeric_cols]
+            numeric_cols = [c for c in numeric_cols if c not in drop_cols]
+            if not numeric_cols:
+                raise ValueError(f"Could not identify value column in AirPassengers data: {list(data.columns)}")
+            y = pd.to_numeric(data[numeric_cols[-1]], errors="coerce").to_numpy()
+        
+        return pd.DataFrame({"ds": dates, "y": y})
     except Exception:
         # Fallback: generate the well-known series manually
         np.random.seed(0)