ENH: Allow adjust=False when times is provided (#59142)

* add adjust parameter to the ewma variable times test. Add tests for disallowed decay-specification parameters when times is specified and adjust=False

* allow adjust=False when times is provided

* re-calculate alpha each iteration for irregular-spaced time series

* whatsnew entry for allowing adjust=False with times

* pre-commit style fixes

* reduce line lengths to comply with pre-commit

* reduce line lengths and apply ruff-reformat changes

Author: tserrao

doc/source/whatsnew/v3.0.0.rst

@@ -42,6 +42,7 @@ Other enhancements
 - :func:`DataFrame.to_excel` argument ``merge_cells`` now accepts a value of ``"columns"`` to only merge :class:`MultiIndex` column header header cells (:issue:`35384`)
 - :meth:`DataFrame.corrwith` now accepts ``min_periods`` as optional arguments, as in :meth:`DataFrame.corr` and :meth:`Series.corr` (:issue:`9490`)
 - :meth:`DataFrame.cummin`, :meth:`DataFrame.cummax`, :meth:`DataFrame.cumprod` and :meth:`DataFrame.cumsum` methods now have a ``numeric_only`` parameter (:issue:`53072`)
+- :meth:`DataFrame.ewm` now allows ``adjust=False`` when ``times`` is provided (:issue:`54328`)
 - :meth:`DataFrame.fillna` and :meth:`Series.fillna` can now accept ``value=None``; for non-object dtype the corresponding NA value will be used (:issue:`57723`)
 - :meth:`DataFrame.pivot_table` and :func:`pivot_table` now allow the passing of keyword arguments to ``aggfunc`` through ``**kwargs`` (:issue:`57884`)
 - :meth:`Series.cummin` and :meth:`Series.cummax` now supports :class:`CategoricalDtype` (:issue:`52335`)

pandas/_libs/window/aggregations.pyx

@@ -1813,6 +1813,9 @@ def ewm(const float64_t[:] vals, const int64_t[:] start, const int64_t[:] end,
                             if normalize:
                                 # avoid numerical errors on constant series
                                 if weighted != cur:
+                                    if not adjust and com == 1:
+                                        # update in case of irregular-interval series
+                                        new_wt = 1. - old_wt
                                     weighted = old_wt * weighted + new_wt * cur
                                     weighted /= (old_wt + new_wt)
                                 if adjust:

pandas/core/window/ewm.py

@@ -134,8 +134,10 @@ class ExponentialMovingWindow(BaseWindow):
     Provide exponentially weighted (EW) calculations.
 
     Exactly one of ``com``, ``span``, ``halflife``, or ``alpha`` must be
-    provided if ``times`` is not provided. If ``times`` is provided,
+    provided if ``times`` is not provided. If ``times`` is provided and ``adjust=True``,
     ``halflife`` and one of ``com``, ``span`` or ``alpha`` may be provided.
+    If ``times`` is provided and ``adjust=False``, ``halflife`` must be the only
+    provided decay-specification parameter.
 
     Parameters
     ----------
@@ -358,8 +360,6 @@ def __init__(
         self.ignore_na = ignore_na
         self.times = times
         if self.times is not None:
-            if not self.adjust:
-                raise NotImplementedError("times is not supported with adjust=False.")
             times_dtype = getattr(self.times, "dtype", None)
             if not (
                 is_datetime64_dtype(times_dtype)
@@ -376,6 +376,11 @@ def __init__(
             # Halflife is no longer applicable when calculating COM
             # But allow COM to still be calculated if the user passes other decay args
             if common.count_not_none(self.com, self.span, self.alpha) > 0:
+                if not self.adjust:
+                    raise NotImplementedError(
+                        "None of com, span, or alpha can be specified if "
+                        "times is provided and adjust=False"
+                    )
                 self._com = get_center_of_mass(self.com, self.span, None, self.alpha)
             else:
                 self._com = 1.0

pandas/core/window/numba_.py

@@ -149,6 +149,9 @@ def ewm(
                             # note that len(deltas) = len(vals) - 1 and deltas[i]
                             # is to be used in conjunction with vals[i+1]
                             old_wt *= old_wt_factor ** deltas[start + j - 1]
+                            if not adjust and com == 1:
+                                # update in case of irregular-interval time series
+                                new_wt = 1.0 - old_wt
                         else:
                             weighted = old_wt_factor * weighted
                         if is_observation:
@@ -324,6 +327,9 @@ def ewm_table(
                             # note that len(deltas) = len(vals) - 1 and deltas[i]
                             # is to be used in conjunction with vals[i+1]
                             old_wt[j] *= old_wt_factor ** deltas[i - 1]
+                            if not adjust and com == 1:
+                                # update in case of irregular-interval time series
+                                new_wt = 1.0 - old_wt[j]
                         else:
                             weighted[j] = old_wt_factor * weighted[j]
                         if is_observations[j]:

pandas/tests/window/test_ewm.py

@@ -102,7 +102,8 @@ def test_ewma_with_times_equal_spacing(halflife_with_times, times, min_periods):
     tm.assert_frame_equal(result, expected)
 
 
-def test_ewma_with_times_variable_spacing(tz_aware_fixture, unit):
+def test_ewma_with_times_variable_spacing(tz_aware_fixture, unit, adjust):
+    # GH 54328
     tz = tz_aware_fixture
     halflife = "23 days"
     times = (
@@ -112,8 +113,11 @@ def test_ewma_with_times_variable_spacing(tz_aware_fixture, unit):
     )
     data = np.arange(3)
     df = DataFrame(data)
-    result = df.ewm(halflife=halflife, times=times).mean()
-    expected = DataFrame([0.0, 0.5674161888241773, 1.545239952073459])
+    result = df.ewm(halflife=halflife, times=times, adjust=adjust).mean()
+    if adjust:
+        expected = DataFrame([0.0, 0.5674161888241773, 1.545239952073459])
+    else:
+        expected = DataFrame([0.0, 0.23762518642226227, 1.534926369128742])
     tm.assert_frame_equal(result, expected)
 
 
@@ -148,13 +152,56 @@ def test_ewm_getitem_attributes_retained(arg, adjust, ignore_na):
     assert result == expected
 
 
-def test_ewma_times_adjust_false_raises():
-    # GH 40098
+def test_ewma_times_adjust_false_with_disallowed_com():
+    # GH 54328
+    with pytest.raises(
+        NotImplementedError,
+        match=(
+            "None of com, span, or alpha can be specified "
+            "if times is provided and adjust=False"
+        ),
+    ):
+        Series(range(1)).ewm(
+            0.1,
+            adjust=False,
+            times=date_range("2000", freq="D", periods=1),
+            halflife="1D",
+        )
+
+
+def test_ewma_times_adjust_false_with_disallowed_alpha():
+    # GH 54328
     with pytest.raises(
-        NotImplementedError, match="times is not supported with adjust=False."
+        NotImplementedError,
+        match=(
+            "None of com, span, or alpha can be specified "
+            "if times is provided and adjust=False"
+        ),
+    ):
+        Series(range(1)).ewm(
+            0.1,
+            adjust=False,
+            times=date_range("2000", freq="D", periods=1),
+            alpha=0.5,
+            halflife="1D",
+        )
+
+
+def test_ewma_times_adjust_false_with_disallowed_span():
+    # GH 54328
+    with pytest.raises(
+        NotImplementedError,
+        match=(
+            "None of com, span, or alpha can be specified "
+            "if times is provided and adjust=False"
+        ),
     ):
         Series(range(1)).ewm(
-            0.1, adjust=False, times=date_range("2000", freq="D", periods=1)
+            0.1,
+            adjust=False,
+            times=date_range("2000", freq="D", periods=1),
+            span=10,
+            halflife="1D",
         )