add additional test

Author: mroeschke

pandas/core/reshape/tile.py

@@ -309,7 +309,7 @@ def _convert_bin_to_numeric_type(bins, dtype):
 
     Parameters
     ----------
-    bins : list-liek of bins
+    bins : list-like of bins
     dtype : dtype of data
 
     Raises

pandas/tests/reshape/test_tile.py

@@ -105,12 +105,10 @@ def test_cut_corner(self):
         pytest.raises(ValueError, cut, [1, 2, 3], 0.5)
 
     @pytest.mark.parametrize('arg', [2, np.eye(2), DataFrame(np.eye(2))])
-    @pytest.mark.parametrize('bins', [2, np.array(2), np.arange(1, 2), [1, 2],
-                                      Series([1, 2]), Index([1, 2])])
     @pytest.mark.parametrize('cut_func', [cut, qcut])
-    def test_cut_not_1d_arg(self, arg, bins, cut_func):
+    def test_cut_not_1d_arg(self, arg, cut_func):
         with pytest.raises(ValueError):
-            cut_func(arg, bins)
+            cut_func(arg, 2)
 
     def test_cut_out_of_range_more(self):
         # #1511
@@ -259,18 +257,6 @@ def test_qcut_nas(self):
         result = qcut(arr, 4)
         assert isna(result[:20]).all()
 
-    @pytest.mark.parametrize('s', [
-        Series(DatetimeIndex(['20180101', NaT, '20180103'])),
-        Series(TimedeltaIndex(['0 days', NaT, '2 days']))],
-        ids=lambda x: str(x.dtype))
-    def test_qcut_nat(self, s):
-        # GH 19768
-        intervals = IntervalIndex.from_tuples(
-            [(s[0] - Nano(), s[2] - Day()), np.nan, (s[2] - Day(), s[2])])
-        expected = Series(Categorical(intervals, ordered=True))
-        result = qcut(s, 2)
-        tm.assert_series_equal(result, expected)
-
     def test_qcut_index(self):
         result = qcut([0, 2], 2)
         intervals = [Interval(-0.001, 1), Interval(1, 2)]
@@ -460,6 +446,37 @@ def test_single_bin(self):
         result = cut(s, 1, labels=False)
         tm.assert_series_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "array_1_writeable, array_2_writeable",
+        [(True, True), (True, False), (False, False)])
+    def test_cut_read_only(self, array_1_writeable, array_2_writeable):
+        # issue 18773
+        array_1 = np.arange(0, 100, 10)
+        array_1.flags.writeable = array_1_writeable
+
+        array_2 = np.arange(0, 100, 10)
+        array_2.flags.writeable = array_2_writeable
+
+        hundred_elements = np.arange(100)
+
+        tm.assert_categorical_equal(cut(hundred_elements, array_1),
+                                    cut(hundred_elements, array_2))
+
+
+class TestDatelike(object):
+
+    @pytest.mark.parametrize('s', [
+        Series(DatetimeIndex(['20180101', NaT, '20180103'])),
+        Series(TimedeltaIndex(['0 days', NaT, '2 days']))],
+        ids=lambda x: str(x.dtype))
+    def test_qcut_nat(self, s):
+        # GH 19768
+        intervals = IntervalIndex.from_tuples(
+            [(s[0] - Nano(), s[2] - Day()), np.nan, (s[2] - Day(), s[2])])
+        expected = Series(Categorical(intervals, ordered=True))
+        result = qcut(s, 2)
+        tm.assert_series_equal(result, expected)
+
     def test_datetime_cut(self):
         # GH 14714
         # testing for time data to be present as series
@@ -496,11 +513,19 @@ def test_datetime_cut(self):
         result, bins = cut(data, 3, retbins=True)
         tm.assert_series_equal(Series(result), expected)
 
-    def test_datetimetz_cut(self):
+    @pytest.mark.parametrize('bins', [
+        3, [Timestamp('2013-01-01 04:57:07.200000').value,
+            Timestamp('2013-01-01 21:00:00').value,
+            Timestamp('2013-01-02 13:00:00').value,
+            Timestamp('2013-01-03 05:00:00').value]])
+    @pytest.mark.parametrize('const', [list, np.array, Index, Series])
+    def test_datetimetz_cut(self, bins, const):
         # GH 19872
         tz = 'US/Eastern'
         s = Series(date_range('20130101', periods=3, tz=tz))
-        result = cut(s, 3)
+        if not isinstance(bins, int):
+            bins = const(bins)
+        result = cut(s, bins)
         expected = (
             Series(IntervalIndex([
                 Interval(Timestamp('2012-12-31 23:57:07.200000', tz=tz),
@@ -512,7 +537,12 @@ def test_datetimetz_cut(self):
             .astype(CDT(ordered=True)))
         tm.assert_series_equal(result, expected)
 
-        result = qcut(s, 3)
+    @pytest.mark.parametrize('bins', [3, np.linspace(0, 1, 4)])
+    def test_datetimetz_qcut(self, bins):
+        # GH 19872
+        tz = 'US/Eastern'
+        s = Series(date_range('20130101', periods=3, tz=tz))
+        result = qcut(s, bins)
         expected = (
             Series(IntervalIndex([
                 Interval(Timestamp('2012-12-31 23:59:59.999999999', tz=tz),
@@ -559,19 +589,3 @@ def f():
         mask = result.isna()
         tm.assert_numpy_array_equal(
             mask, np.array([False, True, True, True, True]))
-
-    @pytest.mark.parametrize(
-        "array_1_writeable, array_2_writeable",
-        [(True, True), (True, False), (False, False)])
-    def test_cut_read_only(self, array_1_writeable, array_2_writeable):
-        # issue 18773
-        array_1 = np.arange(0, 100, 10)
-        array_1.flags.writeable = array_1_writeable
-
-        array_2 = np.arange(0, 100, 10)
-        array_2.flags.writeable = array_2_writeable
-
-        hundred_elements = np.arange(100)
-
-        tm.assert_categorical_equal(cut(hundred_elements, array_1),
-                                    cut(hundred_elements, array_2))