Implement DataFrame pct_change (#9805)

Fixes: #9603

Next steps:

- [ ] Fix #10314 
- [ ] Move `diff `and `pct_change` to `indexed_frame`  so that both are accessible to `Series` as well

Authors:
  - Sheilah Kirui (https://github.com/skirui-source)

Approvers:
  - Karthikeyan (https://github.com/karthikeyann)
  - Michael Wang (https://github.com/isVoid)

URL: #9805

python/cudf/cudf/core/column/column.py

@@ -335,6 +335,14 @@ def _fill(
         return self
 
     def shift(self, offset: int, fill_value: ScalarLike) -> ColumnBase:
+        # libcudf currently doesn't handle case when offset > len(df)
+        # ticket to fix the bug in link below:
+        # https://github.com/rapidsai/cudf/issues/10314
+        if abs(offset) > len(self):
+            if fill_value is None:
+                return column_empty_like(self, masked=True)
+            else:
+                return full(len(self), fill_value, dtype=self.dtype)
         return libcudf.copying.shift(self, offset, fill_value)
 
     @property

python/cudf/cudf/core/dataframe.py

@@ -6196,6 +6196,46 @@ def explode(self, column, ignore_index=False):
 
         return super()._explode(column, ignore_index)
 
+    def pct_change(
+        self, periods=1, fill_method="ffill", limit=None, freq=None
+    ):
+        """
+        Calculates the percent change between sequential elements
+        in the DataFrame.
+
+        Parameters
+        ----------
+        periods : int, default 1
+            Periods to shift for forming percent change.
+        fill_method : str, default 'ffill'
+            How to handle NAs before computing percent changes.
+        limit : int, optional
+            The number of consecutive NAs to fill before stopping.
+            Not yet implemented.
+        freq : str, optional
+            Increment to use from time series API.
+            Not yet implemented.
+
+        Returns
+        -------
+        DataFrame
+        """
+        if limit is not None:
+            raise NotImplementedError("limit parameter not supported yet.")
+        if freq is not None:
+            raise NotImplementedError("freq parameter not supported yet.")
+        elif fill_method not in {"ffill", "pad", "bfill", "backfill"}:
+            raise ValueError(
+                "fill_method must be one of 'ffill', 'pad', "
+                "'bfill', or 'backfill'."
+            )
+
+        data = self.fillna(method=fill_method, limit=limit)
+
+        return data.diff(periods=periods) / data.shift(
+            periods=periods, freq=freq
+        )
+
     def __dataframe__(
         self, nan_as_null: bool = False, allow_copy: bool = True
     ):

python/cudf/cudf/tests/test_dataframe.py

@@ -3442,29 +3442,37 @@ def test_get_numeric_data():
 
 
 @pytest.mark.parametrize("dtype", NUMERIC_TYPES)
-@pytest.mark.parametrize("period", [-1, -5, -10, -20, 0, 1, 5, 10, 20])
+@pytest.mark.parametrize("period", [-15, -1, 0, 1, 15])
 @pytest.mark.parametrize("data_empty", [False, True])
 def test_shift(dtype, period, data_empty):
-
+    # TODO : this function currently tests for series.shift()
+    # but should instead test for dataframe.shift()
     if data_empty:
         data = None
     else:
         if dtype == np.int8:
             # to keep data in range
-            data = gen_rand(dtype, 100000, low=-2, high=2)
+            data = gen_rand(dtype, 10, low=-2, high=2)
         else:
-            data = gen_rand(dtype, 100000)
+            data = gen_rand(dtype, 10)
 
-    gdf = cudf.DataFrame({"a": cudf.Series(data, dtype=dtype)})
-    pdf = pd.DataFrame({"a": pd.Series(data, dtype=dtype)})
+    gs = cudf.DataFrame({"a": cudf.Series(data, dtype=dtype)})
+    ps = pd.DataFrame({"a": pd.Series(data, dtype=dtype)})
 
-    shifted_outcome = gdf.a.shift(period).fillna(0)
-    expected_outcome = pdf.a.shift(period).fillna(0).astype(dtype)
+    shifted_outcome = gs.a.shift(period)
+    expected_outcome = ps.a.shift(period)
 
+    # pandas uses NaNs to signal missing value and force converts the
+    # results columns to float types
     if data_empty:
-        assert_eq(shifted_outcome, expected_outcome, check_index_type=False)
+        assert_eq(
+            shifted_outcome,
+            expected_outcome,
+            check_index_type=False,
+            check_dtype=False,
+        )
     else:
-        assert_eq(shifted_outcome, expected_outcome)
+        assert_eq(shifted_outcome, expected_outcome, check_dtype=False)
 
 
 @pytest.mark.parametrize("dtype", NUMERIC_TYPES)
@@ -9295,3 +9303,24 @@ def test_dataframe_rename_duplicate_column():
         ValueError, match="Duplicate column names are not allowed"
     ):
         gdf.rename(columns={"a": "b"}, inplace=True)
+
+
+@pytest.mark.parametrize(
+    "data",
+    [
+        np.random.RandomState(seed=10).randint(-50, 50, (10, 10)),
+        np.random.RandomState(seed=10).random_sample((4, 4)),
+        np.array([1.123, 2.343, 5.890, 0.0]),
+        {"a": [1.123, 2.343, np.nan, np.nan], "b": [None, 3, 9.08, None]},
+    ],
+)
+@pytest.mark.parametrize("periods", [-5, -2, 0, 2, 5])
+@pytest.mark.parametrize("fill_method", ["ffill", "bfill", "pad", "backfill"])
+def test_dataframe_pct_change(data, periods, fill_method):
+    gdf = cudf.DataFrame(data)
+    pdf = gdf.to_pandas()
+
+    actual = gdf.pct_change(periods=periods, fill_method=fill_method)
+    expected = pdf.pct_change(periods=periods, fill_method=fill_method)
+
+    assert_eq(expected, actual)