added negative value support in pct_changes of generic.py

pandas/core/generic.py

@@ -11975,6 +11975,7 @@ def pct_change(
         fill_method: FillnaOptions | None | lib.NoDefault = lib.no_default,
         limit: int | None | lib.NoDefault = lib.no_default,
         freq=None,
+        use_absolute_value=False,
         **kwargs,
     ) -> Self:
         """
@@ -12145,7 +12146,10 @@ def pct_change(
 
         shifted = data.shift(periods=periods, freq=freq, axis=axis, **kwargs)
         # Unsupported left operand type for / ("Self")
-        rs = data / shifted - 1  # type: ignore[operator]
+        if use_absolute_value:
+            rs = (data - shifted) / abs(shifted)  # type: ignore[operator]
+        else:
+            rs = data / shifted - 1  # type: ignore[operator]
         if freq is not None:
             # Shift method is implemented differently when freq is not None
             # We want to restore the original index

pandas/core/groupby/groupby.py

@@ -5331,6 +5331,7 @@ def pct_change(
         fill_method: FillnaOptions | None | lib.NoDefault = lib.no_default,
         limit: int | None | lib.NoDefault = lib.no_default,
         freq=None,
+        use_absolute_value=False,
         axis: Axis | lib.NoDefault = lib.no_default,
     ):
         """
@@ -5422,6 +5423,7 @@ def pct_change(
                 limit=limit,
                 freq=freq,
                 axis=axis,
+                use_absolute_value=use_absolute_value,
             )
             return self._python_apply_general(f, self._selected_obj, is_transform=True)
 
@@ -5436,6 +5438,8 @@ def pct_change(
         shifted = fill_grp.shift(periods=periods, freq=freq)
         if self.axis == 1:
             shifted = shifted.T
+        if use_absolute_value:
+            return (filled - shifted) / abs(shifted)
         return (filled / shifted) - 1
 
     @final

pandas/tests/series/methods/test_pct_change.py

@@ -1,6 +1,7 @@
 import numpy as np
 import pytest
 
+import pandas as pd
 from pandas import (
     Series,
     date_range,
@@ -75,22 +76,30 @@ def test_pct_change_periods_freq(
         # GH#7292
         with tm.assert_produces_warning(FutureWarning, match=msg):
             rs_freq = datetime_series.pct_change(
-                freq=freq, fill_method=fill_method, limit=limit
+                freq=freq,
+                fill_method=fill_method,
+                limit=limit,
             )
         with tm.assert_produces_warning(FutureWarning, match=msg):
             rs_periods = datetime_series.pct_change(
-                periods, fill_method=fill_method, limit=limit
+                periods,
+                fill_method=fill_method,
+                limit=limit,
             )
         tm.assert_series_equal(rs_freq, rs_periods)
 
         empty_ts = Series(index=datetime_series.index, dtype=object)
         with tm.assert_produces_warning(FutureWarning, match=msg):
             rs_freq = empty_ts.pct_change(
-                freq=freq, fill_method=fill_method, limit=limit
+                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
+                periods,
+                fill_method=fill_method,
+                limit=limit,
             )
         tm.assert_series_equal(rs_freq, rs_periods)
 
@@ -118,3 +127,19 @@ def test_pct_change_no_warning_na_beginning():
     result = ser.pct_change()
     expected = Series([np.nan, np.nan, np.nan, 1, 0.5])
     tm.assert_series_equal(result, expected)
+
+
+def test_pct_changes_with_negative_values():
+    test = pd.DataFrame()
+    test_list = [1, -2, 3, 4, -5, 6, 7, -8, 9, 10]
+    test["data"] = test_list
+    test["pct_changes"] = test["data"].pct_change(use_absolute_value=True)
+
+    expected_result = [
+        None if i == 0 else (test_list[i] - test_list[i - 1]) / abs(test_list[i - 1])
+        for i in range(len(test_list))
+    ]
+
+    expected_result = Series(expected_result, dtype=float)
+    # assertion to check if the result matches the expected result
+    assert test["pct_changes"].equals(expected_result)