Fix tests for CI, documentation

Author: Brian Tu

doc/source/whatsnew/v0.21.0.txt

@@ -130,7 +130,7 @@ Other Enhancements
 - `read_*` methods can now infer compression from non-string paths, such as ``pathlib.Path`` objects (:issue:`17206`).
 - :func:`pd.read_sas()` now recognizes much more of the most frequently used date (datetime) formats in SAS7BDAT files (:issue:`15871`).
 - :func:`DataFrame.items` and :func:`Series.items` is now present in both Python 2 and 3 and is lazy in all cases (:issue:`13918`, :issue:`17213`)
-- :func:`Series.reindex`, :func:`DataFrame.reindex`, :func:`Index.get_indexer` now support list-like argument for `tolerance`.
+- :func:`Series.reindex`, :func:`DataFrame.reindex`, :func:`Index.get_indexer` now support list-like argument for ``tolerance``.
 
 .. _whatsnew_0210.api_breaking:
 

pandas/core/generic.py

@@ -2659,6 +2659,7 @@ def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
             Maximum distance between original and new labels for inexact
             matches. The values of the index at the matching locations most
             satisfy the equation ``abs(index[indexer] - target) <= tolerance``.
+
             Tolerance may be a scalar value, which applies the same tolerance
             to all values, or list-like, which applies variable tolerance per
             element. List-like includes list, tuple, array, Series, and must be
@@ -2888,6 +2889,7 @@ def _reindex_multi(self, axes, copy, fill_value):
             Maximum distance between original and new labels for inexact
             matches. The values of the index at the matching locations most
             satisfy the equation ``abs(index[indexer] - target) <= tolerance``.
+
             Tolerance may be a scalar value, which applies the same tolerance
             to all values, or list-like, which applies variable tolerance per
             element. List-like includes list, tuple, array, Series, and must be

pandas/core/indexes/base.py

@@ -2443,7 +2443,9 @@ def _get_unique_index(self, dropna=False):
         tolerance : optional
             Maximum distance from index value for inexact matches. The value of
             the index at the matching location most satisfy the equation
-            ``abs(index[loc] - key) <= tolerance``. Tolerance may be a scalar
+            ``abs(index[loc] - key) <= tolerance``.
+
+            Tolerance may be a scalar
             value, which applies the same tolerance to all values, or
             list-like, which applies variable tolerance per element. List-like
             includes list, tuple, array, Series, and must be the same size as
@@ -2570,6 +2572,7 @@ def _get_level_values(self, level):
             Maximum distance between original and new labels for inexact
             matches. The values of the index at the matching locations most
             satisfy the equation ``abs(index[indexer] - target) <= tolerance``.
+
             Tolerance may be a scalar value, which applies the same tolerance
             to all values, or list-like, which applies variable tolerance per
             element. List-like includes list, tuple, array, Series, and must be
@@ -2599,8 +2602,8 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
         if tolerance is not None:
             tolerance = self._convert_tolerance(tolerance)
             if isinstance(tolerance, np.ndarray) and \
-               target.size != tolerance.size and tolerance.size > 1:
-                raise ValueError('ndarray tolerance size must match '
+               target.size != len(tolerance) and len(tolerance) > 1:
+                raise ValueError('list-like tolerance size must match '
                                  'target index size')
 
         pself, ptarget = self._maybe_promote(target)

pandas/core/indexes/datetimes.py

@@ -1438,8 +1438,8 @@ def get_loc(self, key, method=None, tolerance=None):
             except KeyError:
                 raise KeyError(key)
             except ValueError as e:
-                # ndarray tolerance size must match target index size
-                if 'ndarray' in str(e):
+                # list-like tolerance size must match target index size
+                if 'list-like' in str(e):
                     raise e
                 raise KeyError(key)
 

pandas/core/indexes/period.py

@@ -782,7 +782,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
             tolerance = self._convert_tolerance(tolerance)
             if isinstance(tolerance, np.ndarray) and \
                target.size != tolerance.size and tolerance.size > 1:
-                raise ValueError('ndarray tolerance size must match '
+                raise ValueError('list-like tolerance size must match '
                                  'target index size')
         return Index.get_indexer(self._int64index, target, method,
                                  limit, tolerance)

pandas/tests/indexes/datetimes/test_datetime.py

@@ -121,9 +121,9 @@ def test_get_indexer(self):
         tol_bad = [pd.Timedelta('2 hour').to_timedelta64(),
                    pd.Timedelta('1 hour').to_timedelta64(),
                    np.timedelta64(1, 'M'), ]
-        with (pytest.raises(
-                TypeError, match='All values.* convertible to \\[ns\\]'),
-              pytest.warns(UserWarning)):
+        with pytest.raises(
+               TypeError, match='All values.* convertible to \\[ns\\]'),\
+             pytest.warns(UserWarning):
             idx.get_indexer(target, 'nearest', tolerance=tol_bad)
         with pytest.raises(ValueError):
             idx.get_indexer(idx[[0]], method='nearest', tolerance='foo')

pandas/tests/indexes/period/test_period.py

@@ -91,7 +91,7 @@ def test_get_loc(self):
             idx.get_loc('2000-01-10', method='nearest', tolerance='1 day')
         with pytest.raises(
                 ValueError,
-                match='ndarray tolerance size must match target index size'):
+                match='list-like tolerance size must match target index size'):
             idx.get_loc('2000-01-10', method='nearest',
                         tolerance=[pd.Timedelta('1 day').to_timedelta64(),
                                    pd.Timedelta('1 day').to_timedelta64()])
@@ -180,10 +180,10 @@ def test_get_indexer(self):
         tol_bad = [pd.Timedelta('2 hour').to_timedelta64(),
                    pd.Timedelta('1 hour').to_timedelta64(),
                    np.timedelta64(1, 'M'), ]
-        with (pytest.raises(
-                TypeError,
-                match='All values.* convertible to \\[ns\\]'),
-              pytest.warns(UserWarning)):
+        with pytest.raises(
+               TypeError,
+               match='All values.* convertible to \\[ns\\]'),\
+             pytest.warns(UserWarning):
             idx.get_indexer(target, 'nearest', tolerance=tol_bad)
         with pytest.raises(
                 TypeError,