DEPR fill_method and limit keywords in pct_change

doc/source/whatsnew/v2.1.0.rst

@@ -227,6 +227,7 @@ Other API changes
 Deprecations
 ~~~~~~~~~~~~
 - Deprecated 'broadcast_axis' keyword in :meth:`Series.align` and :meth:`DataFrame.align`, upcast before calling ``align`` with ``left = DataFrame({col: left for col in right.columns}, index=right.index)`` (:issue:`51856`)
+- Deprecated 'fill_method' and 'limit' keywords in :meth:`DataFrame.pct_change`, :meth:`Series.pct_change`, :meth:`DataFrameGroupBy.pct_change`, and :meth:`SeriesGroupBy.pct_change`, explicitly call ``ffill`` or ``bfill`` before calling ``pct_change`` instead (:issue:`53491`)
 - Deprecated 'method', 'limit', and 'fill_axis' keywords in :meth:`DataFrame.align` and :meth:`Series.align`, explicitly call ``fillna`` on the alignment results instead (:issue:`51856`)
 - Deprecated 'quantile' keyword in :meth:`Rolling.quantile` and :meth:`Expanding.quantile`, renamed as 'q' instead (:issue:`52550`)
 - Deprecated :meth:`.DataFrameGroupBy.apply` and methods on the objects returned by :meth:`.DataFrameGroupBy.resample` operating on the grouping column(s); select the columns to operate on after groupby to either explicitly include or exclude the groupings and avoid the ``FutureWarning`` (:issue:`7155`)

pandas/core/generic.py

@@ -11219,8 +11219,8 @@ def describe(
     def pct_change(
         self,
         periods: int = 1,
-        fill_method: Literal["backfill", "bfill", "pad", "ffill"] | None = "pad",
-        limit: int | None = None,
+        fill_method: FillnaOptions | None | lib.NoDefault = lib.no_default,
+        limit: int | None | lib.NoDefault = lib.no_default,
         freq=None,
         **kwargs,
     ) -> Self:
@@ -11244,8 +11244,14 @@ def pct_change(
             Periods to shift for forming percent change.
         fill_method : {'backfill', 'bfill', 'pad', 'ffill', None}, default 'pad'
             How to handle NAs **before** computing percent changes.
+
+            .. deprecated:: 2.1
+
         limit : int, default None
             The number of consecutive NAs to fill before stopping.
+
+            .. deprecated:: 2.1
+
         freq : DateOffset, timedelta, or str, optional
             Increment to use from time series API (e.g. 'M' or BDay()).
         **kwargs
@@ -11298,7 +11304,7 @@ def pct_change(
         3    85.0
         dtype: float64
 
-        >>> s.pct_change(fill_method='ffill')
+        >>> s.ffill().pct_change()
         0         NaN
         1    0.011111
         2    0.000000
@@ -11345,6 +11351,31 @@ def pct_change(
         GOOG  0.179241  0.094112   NaN
         APPL -0.252395 -0.011860   NaN
         """
+        # GH#53491
+        if fill_method is not lib.no_default or limit is not lib.no_default:
+            warnings.warn(
+                "The 'fill_method' and 'limit' keywords in "
+                f"{type(self).__name__}.pct_change are deprecated and will be "
+                "removed in a future version. Call "
+                f"{'bfill' if fill_method in ('backfill', 'bfill') else 'ffill'} "
+                "before calling pct_change instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        if fill_method is lib.no_default:
+            if self.isna().values.any():
+                warnings.warn(
+                    "The default fill_method='pad' in "
+                    f"{type(self).__name__}.pct_change is deprecated and will be "
+                    "removed in a future version. Call ffill before calling "
+                    "pct_change to retain current behavior and silence this warning.",
+                    FutureWarning,
+                    stacklevel=find_stack_level(),
+                )
+            fill_method = "pad"
+        if limit is lib.no_default:
+            limit = None
+
         axis = self._get_axis_number(kwargs.pop("axis", "index"))
         if fill_method is None:
             data = self

pandas/core/groupby/groupby.py

@@ -4787,8 +4787,8 @@ def diff(
     def pct_change(
         self,
         periods: int = 1,
-        fill_method: FillnaOptions = "ffill",
-        limit: int | None = None,
+        fill_method: FillnaOptions | lib.NoDefault = lib.no_default,
+        limit: int | None | lib.NoDefault = lib.no_default,
         freq=None,
         axis: Axis | lib.NoDefault = lib.no_default,
     ):
@@ -4838,6 +4838,30 @@ def pct_change(
          catfish    NaN    NaN
         goldfish    0.2  0.125
         """
+        # GH#53491
+        if fill_method is not lib.no_default or limit is not lib.no_default:
+            warnings.warn(
+                "The 'fill_method' and 'limit' keywords in "
+                f"{type(self).__name__}.pct_change are deprecated and will be "
+                "removed in a future version. Call "
+                f"{'bfill' if fill_method in ('backfill', 'bfill') else 'ffill'} "
+                "before calling pct_change instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        if fill_method is lib.no_default:
+            if any(grp.isna().values.any() for _, grp in self):
+                warnings.warn(
+                    "The default fill_method='ffill' in "
+                    f"{type(self).__name__}.pct_change is deprecated and will be "
+                    "removed in a future version. Call ffill before calling "
+                    "pct_change to retain current behavior and silence this warning.",
+                    FutureWarning,
+                    stacklevel=find_stack_level(),
+                )
+            fill_method = "ffill"
+        if limit is lib.no_default:
+            limit = None
 
         if axis is not lib.no_default:
             axis = self.obj._get_axis_number(axis)

pandas/tests/frame/methods/test_pct_change.py

@@ -10,7 +10,7 @@
 
 class TestDataFramePctChange:
     @pytest.mark.parametrize(
-        "periods,fill_method,limit,exp",
+        "periods, fill_method, limit, exp",
         [
             (1, "ffill", None, [np.nan, np.nan, np.nan, 1, 1, 1.5, 0, 0]),
             (1, "ffill", 1, [np.nan, np.nan, np.nan, 1, 1, 1.5, 0, np.nan]),
@@ -28,7 +28,12 @@ def test_pct_change_with_nas(
         vals = [np.nan, np.nan, 1, 2, 4, 10, np.nan, np.nan]
         obj = frame_or_series(vals)
 
-        res = obj.pct_change(periods=periods, fill_method=fill_method, limit=limit)
+        msg = (
+            "The 'fill_method' and 'limit' keywords in "
+            f"{type(obj).__name__}.pct_change are deprecated"
+        )
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            res = obj.pct_change(periods=periods, fill_method=fill_method, limit=limit)
         tm.assert_equal(res, frame_or_series(exp))
 
     def test_pct_change_numeric(self):
@@ -40,21 +45,34 @@ def test_pct_change_numeric(self):
         pnl.iat[1, 1] = np.nan
         pnl.iat[2, 3] = 60
 
+        msg = (
+            "The 'fill_method' and 'limit' keywords in "
+            "DataFrame.pct_change are deprecated"
+        )
+
         for axis in range(2):
             expected = pnl.ffill(axis=axis) / pnl.ffill(axis=axis).shift(axis=axis) - 1
-            result = pnl.pct_change(axis=axis, fill_method="pad")
 
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                result = pnl.pct_change(axis=axis, fill_method="pad")
             tm.assert_frame_equal(result, expected)
 
     def test_pct_change(self, datetime_frame):
-        rs = datetime_frame.pct_change(fill_method=None)
+        msg = (
+            "The 'fill_method' and 'limit' keywords in "
+            "DataFrame.pct_change are deprecated"
+        )
+
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            rs = datetime_frame.pct_change(fill_method=None)
         tm.assert_frame_equal(rs, datetime_frame / datetime_frame.shift(1) - 1)
 
         rs = datetime_frame.pct_change(2)
         filled = datetime_frame.ffill()
         tm.assert_frame_equal(rs, filled / filled.shift(2) - 1)
 
-        rs = datetime_frame.pct_change(fill_method="bfill", limit=1)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            rs = datetime_frame.pct_change(fill_method="bfill", limit=1)
         filled = datetime_frame.bfill(limit=1)
         tm.assert_frame_equal(rs, filled / filled.shift(1) - 1)
 
@@ -69,7 +87,10 @@ def test_pct_change_shift_over_nas(self):
 
         df = DataFrame({"a": s, "b": s})
 
-        chg = df.pct_change()
+        msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            chg = df.pct_change()
+
         expected = Series([np.nan, 0.5, 0.0, 2.5 / 1.5 - 1, 0.2])
         edf = DataFrame({"a": expected, "b": expected})
         tm.assert_frame_equal(chg, edf)
@@ -88,18 +109,31 @@ def test_pct_change_shift_over_nas(self):
     def test_pct_change_periods_freq(
         self, datetime_frame, freq, periods, fill_method, limit
     ):
-        # GH#7292
-        rs_freq = datetime_frame.pct_change(
-            freq=freq, fill_method=fill_method, limit=limit
-        )
-        rs_periods = datetime_frame.pct_change(
-            periods, fill_method=fill_method, limit=limit
+        msg = (
+            "The 'fill_method' and 'limit' keywords in "
+            "DataFrame.pct_change are deprecated"
         )
+
+        # GH#7292
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            rs_freq = datetime_frame.pct_change(
+                freq=freq, fill_method=fill_method, limit=limit
+            )
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            rs_periods = datetime_frame.pct_change(
+                periods, fill_method=fill_method, limit=limit
+            )
         tm.assert_frame_equal(rs_freq, rs_periods)
 
         empty_ts = DataFrame(index=datetime_frame.index, columns=datetime_frame.columns)
-        rs_freq = empty_ts.pct_change(freq=freq, fill_method=fill_method, limit=limit)
-        rs_periods = empty_ts.pct_change(periods, fill_method=fill_method, limit=limit)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            rs_freq = empty_ts.pct_change(
+                freq=freq, fill_method=fill_method, limit=limit
+            )
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            rs_periods = empty_ts.pct_change(
+                periods, fill_method=fill_method, limit=limit
+            )
         tm.assert_frame_equal(rs_freq, rs_periods)
 
 
@@ -109,7 +143,14 @@ def test_pct_change_with_duplicated_indices(fill_method):
     data = DataFrame(
         {0: [np.nan, 1, 2, 3, 9, 18], 1: [0, 1, np.nan, 3, 9, 18]}, index=["a", "b"] * 3
     )
-    result = data.pct_change(fill_method=fill_method)
+
+    msg = (
+        "The 'fill_method' and 'limit' keywords in "
+        "DataFrame.pct_change are deprecated"
+    )
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        result = data.pct_change(fill_method=fill_method)
+
     if fill_method is None:
         second_column = [np.nan, np.inf, np.nan, np.nan, 2.0, 1.0]
     else:

pandas/tests/groupby/test_groupby_dropna.py

@@ -622,8 +622,15 @@ def test_categorical_transformers(
         "x", dropna=False, observed=observed, sort=sort, as_index=as_index
     )
     gb_dropna = df.groupby("x", dropna=True, observed=observed, sort=sort)
-    result = getattr(gb_keepna, transformation_func)(*args)
+
+    msg = "The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
+    if transformation_func == "pct_change":
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = getattr(gb_keepna, "pct_change")(*args)
+    else:
+        result = getattr(gb_keepna, transformation_func)(*args)
     expected = getattr(gb_dropna, transformation_func)(*args)
+
     for iloc, value in zip(
         df[df["x"].isnull()].index.tolist(), null_group_result.values.ravel()
     ):

pandas/tests/groupby/transform/test_transform.py

@@ -408,11 +408,24 @@ def mock_op(x):
         test_op = lambda x: x.transform(transformation_func)
         mock_op = lambda x: getattr(x, transformation_func)()
 
-    result = test_op(df.groupby("A"))
+    msg = "The default fill_method='pad' in DataFrame.pct_change is deprecated"
+    groupby_msg = (
+        "The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
+    )
+    if transformation_func == "pct_change":
+        with tm.assert_produces_warning(FutureWarning, match=groupby_msg):
+            result = test_op(df.groupby("A"))
+    else:
+        result = test_op(df.groupby("A"))
+
     # pass the group in same order as iterating `for ... in df.groupby(...)`
     # but reorder to match df's index since this is a transform
     groups = [df[["B"]].iloc[4:6], df[["B"]].iloc[6:], df[["B"]].iloc[:4]]
-    expected = concat([mock_op(g) for g in groups]).sort_index()
+    if transformation_func == "pct_change":
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            expected = concat([mock_op(g) for g in groups]).sort_index()
+    else:
+        expected = concat([mock_op(g) for g in groups]).sort_index()
     # sort_index does not preserve the freq
     expected = expected.set_axis(df.index)
 
@@ -973,9 +986,14 @@ def test_pct_change(frame_or_series, freq, periods, fill_method, limit):
     else:
         expected = expected.to_frame("vals")
 
-    result = gb.pct_change(
-        periods=periods, fill_method=fill_method, limit=limit, freq=freq
+    msg = (
+        "The 'fill_method' and 'limit' keywords in "
+        f"{type(gb).__name__}.pct_change are deprecated"
     )
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        result = gb.pct_change(
+            periods=periods, fill_method=fill_method, limit=limit, freq=freq
+        )
     tm.assert_equal(result, expected)
 
 
@@ -1412,7 +1430,12 @@ def test_null_group_str_transformer(request, dropna, transformation_func):
         # ngroup/cumcount always returns a Series as it counts the groups, not values
         expected = expected["B"].rename(None)
 
-    result = gb.transform(transformation_func, *args)
+    msg = "The default fill_method='ffill' in DataFrameGroupBy.pct_change is deprecated"
+    if transformation_func == "pct_change" and not dropna:
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = gb.transform("pct_change", *args)
+    else:
+        result = gb.transform(transformation_func, *args)
 
     tm.assert_equal(result, expected)