Merge remote-tracking branch 'upstream/master' into STY-repr-batch-3

Author: MomIsBestFriend

ci/deps/travis-36-cov.yaml

@@ -27,7 +27,8 @@ dependencies:
   - numexpr
   - numpy=1.15.*
   - odfpy
-  - openpyxl
+  - openpyxl<=3.0.1
+  # https://github.com/pandas-dev/pandas/pull/30009 openpyxl 3.0.2 broke
   - pandas-gbq
   # https://github.com/pydata/pandas-gbq/issues/271
   - google-cloud-bigquery<=1.11

doc/source/whatsnew/v1.0.0.rst

@@ -661,6 +661,7 @@ Numeric
 - Bug in :class:`UInt64Index` precision loss while constructing from a list with values in the ``np.uint64`` range (:issue:`29526`)
 - Bug in :class:`NumericIndex` construction that caused indexing to fail when integers in the ``np.uint64`` range were used (:issue:`28023`)
 - Bug in :class:`NumericIndex` construction that caused :class:`UInt64Index` to be casted to :class:`Float64Index` when integers in the ``np.uint64`` range were used to index a :class:`DataFrame` (:issue:`28279`)
+- Bug in :meth:`Series.interpolate` when using method=`index` with an unsorted index, would previously return incorrect results. (:issue:`21037`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/arrays/numpy_.py

@@ -1,4 +1,5 @@
 import numbers
+from typing import Union
 
 import numpy as np
 from numpy.lib.mixins import NDArrayOperatorsMixin
@@ -117,11 +118,12 @@ class PandasArray(ExtensionArray, ExtensionOpsMixin, NDArrayOperatorsMixin):
     # pandas internals, which turns off things like block consolidation.
     _typ = "npy_extension"
     __array_priority__ = 1000
+    _ndarray: np.ndarray
 
     # ------------------------------------------------------------------------
     # Constructors
 
-    def __init__(self, values, copy=False):
+    def __init__(self, values: Union[np.ndarray, "PandasArray"], copy: bool = False):
         if isinstance(values, type(self)):
             values = values._ndarray
         if not isinstance(values, np.ndarray):

pandas/core/missing.py

@@ -278,7 +278,11 @@ def interpolate_1d(
                 inds = lib.maybe_convert_objects(inds)
         else:
             inds = xvalues
-        result[invalid] = np.interp(inds[invalid], inds[valid], yvalues[valid])
+        # np.interp requires sorted X values, #21037
+        indexer = np.argsort(inds[valid])
+        result[invalid] = np.interp(
+            inds[invalid], inds[valid][indexer], yvalues[valid][indexer]
+        )
         result[preserve_nans] = np.nan
         return result
 

pandas/tests/io/excel/test_openpyxl.py

@@ -1,8 +1,11 @@
+from distutils.version import LooseVersion
 import os
 
 import numpy as np
 import pytest
 
+from pandas.compat import PY37, is_platform_mac
+
 import pandas as pd
 from pandas import DataFrame
 import pandas.util.testing as tm
@@ -13,6 +16,8 @@
 
 pytestmark = pytest.mark.parametrize("ext", [".xlsx"])
 
+openpyxl_gt301 = LooseVersion(openpyxl.__version__) > LooseVersion("3.0.1")
+
 
 def test_to_excel_styleconverter(ext):
     from openpyxl import styles
@@ -81,6 +86,9 @@ def test_write_cells_merge_styled(ext):
         assert xcell_a2.font == openpyxl_sty_merged
 
 
+@pytest.mark.xfail(
+    openpyxl_gt301 and PY37 and is_platform_mac(), reason="broken change in openpyxl"
+)
 @pytest.mark.parametrize(
     "mode,expected", [("w", ["baz"]), ("a", ["foo", "bar", "baz"])]
 )
@@ -107,7 +115,9 @@ def test_write_append_mode(ext, mode, expected):
             assert wb2.worksheets[index]["A1"].value == cell_value
 
 
-@pytest.mark.xfail(openpyxl.__version__ > "3.0.1", reason="broken change in openpyxl")
+@pytest.mark.xfail(
+    openpyxl_gt301 and PY37 and is_platform_mac(), reason="broken change in openpyxl"
+)
 def test_to_excel_with_openpyxl_engine(ext, tmpdir):
     # GH 29854
     # TODO: Fix this once newer version of openpyxl fixes the bug

pandas/tests/series/test_missing.py

@@ -1649,3 +1649,14 @@ def test_interpolate_timedelta_index(self, interp_methods_ind):
             pytest.skip(
                 "This interpolation method is not supported for Timedelta Index yet."
             )
+
+    @pytest.mark.parametrize(
+        "ascending, expected_values",
+        [(True, [1, 2, 3, 9, 10]), (False, [10, 9, 3, 2, 1])],
+    )
+    def test_interpolate_unsorted_index(self, ascending, expected_values):
+        # GH 21037
+        ts = pd.Series(data=[10, 9, np.nan, 2, 1], index=[10, 9, 3, 2, 1])
+        result = ts.sort_index(ascending=ascending).interpolate(method="index")
+        expected = pd.Series(data=expected_values, index=expected_values, dtype=float)
+        tm.assert_series_equal(result, expected)