Finished the data deseasonalization code.

toarstats/trends/utils.py

@@ -22,4 +22,8 @@ def deseasonalize(data):
         "+np.cos(month*4*np.pi/12)+np.sin(month*4*np.pi/12)",
         pd.DataFrame({"value": data["value"], "month": data.index.month})
     ).fit(method="qr").predict(pd.DataFrame({"month": range(1, 13)}))
-    return data
+    idx = data.index
+    return pd.DataFrame({
+        "value": data["value"].values - seasonal_cycle[idx.month-1].values,
+        "datetime": (idx.year-2000)*12 + idx.month
+    })