[WIP] fork of #31048 for CI testing DO NOT MERGE

doc/source/whatsnew/v1.1.0.rst

@@ -904,6 +904,7 @@ Indexing
 Missing
 ^^^^^^^
 - Calling :meth:`fillna` on an empty Series now correctly returns a shallow copied object. The behaviour is now consistent with :class:`Index`, :class:`DataFrame` and a non-empty :class:`Series` (:issue:`32543`).
+- Bug in :meth:`Series.interpolate` where kwarg ``limit_area`` had no effect when using methods ``pad``, ``ffill``, ``backfill`` and ``bfill`` (:issue:`26796`)
 - Bug in :meth:`replace` when argument ``to_replace`` is of type dict/list and is used on a :class:`Series` containing ``<NA>`` was raising a ``TypeError``. The method now handles this by ignoring ``<NA>`` values when doing the comparison for the replacement (:issue:`32621`)
 - Bug in :meth:`~Series.any` and :meth:`~Series.all` incorrectly returning ``<NA>`` for all ``False`` or all ``True`` values using the nulllable boolean dtype and with ``skipna=False`` (:issue:`33253`)
 - Clarified documentation on interpolate with method =akima. The ``der`` parameter must be scalar or None (:issue:`33426`)

pandas/core/internals/blocks.py

@@ -1,4 +1,5 @@
 from datetime import datetime, timedelta
+import functools
 import inspect
 import re
 from typing import TYPE_CHECKING, Any, List, Optional
@@ -1091,7 +1092,7 @@ def interpolate(
         if (self.is_bool or self.is_integer) and not self.is_timedelta:
             return self if inplace else self.copy()
 
-        # a fill na type method
+        # a fillna type method
         try:
             m = missing.clean_fill_method(method)
         except ValueError:
@@ -1103,6 +1104,7 @@ def interpolate(
                 axis=axis,
                 inplace=inplace,
                 limit=limit,
+                limit_area=limit_area,
                 fill_value=fill_value,
                 coerce=coerce,
                 downcast=downcast,
@@ -1131,6 +1133,7 @@ def _interpolate_with_fill(
         axis: int = 0,
         inplace: bool = False,
         limit: Optional[int] = None,
+        limit_area: Optional[str] = None,
         fill_value: Optional[Any] = None,
         coerce: bool = False,
         downcast: Optional[str] = None,
@@ -1152,15 +1155,43 @@ def _interpolate_with_fill(
         # We only get here for non-ExtensionBlock
         fill_value = convert_scalar_for_putitemlike(fill_value, self.values.dtype)
 
-        values = missing.interpolate_2d(
-            values,
+        interpolate_2d = functools.partial(
+            missing.interpolate_2d,
             method=method,
-            axis=axis,
             limit=limit,
             fill_value=fill_value,
             dtype=self.dtype,
         )
 
+        if limit_area is None:
+            values = interpolate_2d(values, axis=axis)
+        else:
+
+            def func(values):
+                invalid = isna(values)
+
+                if not invalid.any():
+                    return values
+
+                if not invalid.all():
+                    first = missing.find_valid_index(values, "first")
+                    last = missing.find_valid_index(values, "last")
+
+                    values = interpolate_2d(values)
+
+                    if limit_area == "inside":
+                        invalid[first : last + 1] = False
+                    elif limit_area == "outside":
+                        invalid[:first] = False
+                        invalid[last + 1 :] = False
+
+                    values[invalid] = np.nan
+                else:
+                    values = interpolate_2d(values)
+                return values
+
+            values = np.apply_along_axis(func, axis, values)
+
         blocks = [self.make_block_same_class(values, ndim=self.ndim)]
         return self._maybe_downcast(blocks, downcast)
 

pandas/tests/series/methods/test_interpolate.py

@@ -429,6 +429,70 @@ def test_interp_limit_area(self):
         with pytest.raises(ValueError, match=msg):
             s.interpolate(method="linear", limit_area="abc")
 
+    def test_interp_limit_area_with_pad(self):
+        # https://github.com/pandas-dev/pandas/issues/26796
+        s = Series([np.nan, np.nan, 3, np.nan, np.nan, np.nan, 7, np.nan, np.nan])
+
+        expected = Series([np.nan, np.nan, 3.0, 3.0, 3.0, 3.0, 7.0, np.nan, np.nan])
+        result = s.interpolate(method="pad", limit_area="inside")
+        tm.assert_series_equal(result, expected)
+
+        expected = Series(
+            [np.nan, np.nan, 3.0, 3.0, np.nan, np.nan, 7.0, np.nan, np.nan]
+        )
+        result = s.interpolate(method="pad", limit_area="inside", limit=1)
+        tm.assert_series_equal(result, expected)
+
+        expected = Series([np.nan, np.nan, 3.0, np.nan, np.nan, np.nan, 7.0, 7.0, 7.0])
+        result = s.interpolate(method="pad", limit_area="outside")
+        tm.assert_series_equal(result, expected)
+
+        expected = Series(
+            [np.nan, np.nan, 3.0, np.nan, np.nan, np.nan, 7.0, 7.0, np.nan]
+        )
+        result = s.interpolate(method="pad", limit_area="outside", limit=1)
+        tm.assert_series_equal(result, expected)
+
+    def test_interp_limit_area_with_backfill(self):
+        # https://github.com/pandas-dev/pandas/issues/26796
+        s = Series([np.nan, np.nan, 3, np.nan, np.nan, np.nan, 7, np.nan, np.nan])
+
+        expected = Series([np.nan, np.nan, 3.0, 7.0, 7.0, 7.0, 7.0, np.nan, np.nan])
+        result = s.interpolate(method="bfill", limit_area="inside")
+        tm.assert_series_equal(result, expected)
+
+        expected = Series(
+            [np.nan, np.nan, 3.0, np.nan, np.nan, 7.0, 7.0, np.nan, np.nan]
+        )
+        result = s.interpolate(method="bfill", limit_area="inside", limit=1)
+        tm.assert_series_equal(result, expected)
+
+        expected = Series([3.0, 3.0, 3.0, np.nan, np.nan, np.nan, 7.0, np.nan, np.nan])
+        result = s.interpolate(method="bfill", limit_area="outside")
+        tm.assert_series_equal(result, expected)
+
+        expected = Series(
+            [np.nan, 3.0, 3.0, np.nan, np.nan, np.nan, 7.0, np.nan, np.nan]
+        )
+        result = s.interpolate(method="bfill", limit_area="outside", limit=1)
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("method", ["backfill", "bfill", "pad", "ffill"])
+    @pytest.mark.parametrize("limit_area", ["inside", "outside", "both", None])
+    def test_interp_limit_area_all_missing(self, method, limit_area):
+        # https://github.com/pandas-dev/pandas/issues/26796
+        ser = Series([np.nan, np.nan, np.nan])
+        result = ser.interpolate(method=method, limit_area=limit_area)
+        tm.assert_series_equal(result, ser)
+
+    @pytest.mark.parametrize("method", ["backfill", "bfill", "pad", "ffill"])
+    @pytest.mark.parametrize("limit_area", ["inside", "outside", "both", None])
+    def test_interp_limit_area_none_missing(self, method, limit_area):
+        # https://github.com/pandas-dev/pandas/issues/26796
+        ser = Series([1, 2, 3])
+        result = ser.interpolate(method=method, limit_area=limit_area)
+        tm.assert_series_equal(result, ser)
+
     def test_interp_limit_direction(self):
         # These tests are for issue #9218 -- fill NaNs in both directions.
         s = Series([1, 3, np.nan, np.nan, np.nan, 11])