IntervalIndex/IntervalArray __repr__ remove redundant closed (#39085)

Author: jbrockmendel

pandas/core/arrays/interval.py

@@ -149,7 +149,7 @@
     >>> pd.arrays.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
     <IntervalArray>
     [(0, 1], (1, 5]]
-    Length: 2, closed: right, dtype: interval[int64, right]
+    Length: 2, dtype: interval[int64, right]
 
     It may also be constructed using one of the constructor
     methods: :meth:`IntervalArray.from_arrays`,
@@ -354,7 +354,7 @@ def _from_factorized(cls, values, original):
         >>> pd.arrays.IntervalArray.from_breaks([0, 1, 2, 3])
         <IntervalArray>
         [(0, 1], (1, 2], (2, 3]]
-        Length: 3, closed: right, dtype: interval[int64, right]
+        Length: 3, dtype: interval[int64, right]
         """
             ),
         }
@@ -425,7 +425,7 @@ def from_breaks(
         >>> pd.arrays.IntervalArray.from_arrays([0, 1, 2], [1, 2, 3])
         <IntervalArray>
         [(0, 1], (1, 2], (2, 3]]
-        Length: 3, closed: right, dtype: interval[int64, right]
+        Length: 3, dtype: interval[int64, right]
         """
             ),
         }
@@ -484,7 +484,7 @@ def from_arrays(
         >>> pd.arrays.IntervalArray.from_tuples([(0, 1), (1, 2)])
         <IntervalArray>
         [(0, 1], (1, 2]]
-        Length: 2, closed: right, dtype: interval[int64, right]
+        Length: 2, dtype: interval[int64, right]
         """
             ),
         }
@@ -1071,11 +1071,7 @@ def __repr__(self) -> str:
         data = self._format_data()
         class_name = f"<{type(self).__name__}>\n"
 
-        template = (
-            f"{class_name}"
-            f"{data}\n"
-            f"Length: {len(self)}, closed: {self.closed}, dtype: {self.dtype}"
-        )
+        template = f"{class_name}{data}\nLength: {len(self)}, dtype: {self.dtype}"
         return template
 
     def _format_space(self):
@@ -1185,7 +1181,7 @@ def mid(self):
         >>> intervals
         <IntervalArray>
         [(0, 1], (1, 3], (2, 4]]
-        Length: 3, closed: right, dtype: interval[int64, right]
+        Length: 3, dtype: interval[int64, right]
         """
             ),
         }
@@ -1249,11 +1245,11 @@ def closed(self):
         >>> index
         <IntervalArray>
         [(0, 1], (1, 2], (2, 3]]
-        Length: 3, closed: right, dtype: interval[int64, right]
+        Length: 3, dtype: interval[int64, right]
         >>> index.set_closed('both')
         <IntervalArray>
         [[0, 1], [1, 2], [2, 3]]
-        Length: 3, closed: both, dtype: interval[int64, both]
+        Length: 3, dtype: interval[int64, both]
         """
             ),
         }
@@ -1452,7 +1448,7 @@ def repeat(self, repeats, axis=None):
         >>> intervals
         <IntervalArray>
         [(0, 1], (1, 3], (2, 4]]
-        Length: 3, closed: right, dtype: interval[int64, right]
+        Length: 3, dtype: interval[int64, right]
         """
             ),
         }

pandas/core/indexes/interval.py

@@ -51,7 +51,6 @@
     default_pprint,
     ensure_index,
     maybe_extract_name,
-    unpack_nested_dtype,
 )
 from pandas.core.indexes.datetimes import DatetimeIndex, date_range
 from pandas.core.indexes.extension import ExtensionIndex, inherit_names
@@ -157,7 +156,6 @@ def wrapped(self, other, sort=False):
 
     >>> pd.interval_range(start=0, end=5)
     IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],
-                  closed='right',
                   dtype='interval[int64, right]')
 
     It may also be constructed using one of the constructor
@@ -242,7 +240,6 @@ def _simple_new(cls, array: IntervalArray, name: Label = None):
         --------
         >>> pd.IntervalIndex.from_breaks([0, 1, 2, 3])
         IntervalIndex([(0, 1], (1, 2], (2, 3]],
-                      closed='right',
                       dtype='interval[int64, right]')
         """
             ),
@@ -273,7 +270,6 @@ def from_breaks(
         --------
         >>> pd.IntervalIndex.from_arrays([0, 1, 2], [1, 2, 3])
         IntervalIndex([(0, 1], (1, 2], (2, 3]],
-                      closed='right',
                       dtype='interval[int64, right]')
         """
             ),
@@ -305,7 +301,6 @@ def from_arrays(
         --------
         >>> pd.IntervalIndex.from_tuples([(0, 1), (1, 2)])
         IntervalIndex([(0, 1], (1, 2]],
-                       closed='right',
                        dtype='interval[int64, right]')
         """
             ),
@@ -445,7 +440,6 @@ def is_overlapping(self) -> bool:
         >>> index = pd.IntervalIndex.from_tuples([(0, 2), (1, 3), (4, 5)])
         >>> index
         IntervalIndex([(0, 2], (1, 3], (4, 5]],
-              closed='right',
               dtype='interval[int64, right]')
         >>> index.is_overlapping
         True
@@ -455,7 +449,6 @@ def is_overlapping(self) -> bool:
         >>> index = pd.interval_range(0, 3, closed='both')
         >>> index
         IntervalIndex([[0, 1], [1, 2], [2, 3]],
-              closed='both',
               dtype='interval[int64, both]')
         >>> index.is_overlapping
         True
@@ -465,7 +458,6 @@ def is_overlapping(self) -> bool:
         >>> index = pd.interval_range(0, 3, closed='left')
         >>> index
         IntervalIndex([[0, 1), [1, 2), [2, 3)],
-              closed='left',
               dtype='interval[int64, left]')
         >>> index.is_overlapping
         False
@@ -777,17 +769,11 @@ def _convert_list_indexer(self, keyarr):
     def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
         if not isinstance(dtype, IntervalDtype):
             return False
+        if self.closed != dtype.closed:
+            return False
         common_subtype = find_common_type([self.dtype.subtype, dtype.subtype])
         return not is_object_dtype(common_subtype)
 
-    def _should_compare(self, other) -> bool:
-        other = unpack_nested_dtype(other)
-        if is_object_dtype(other.dtype):
-            return True
-        if not self._is_comparable_dtype(other.dtype):
-            return False
-        return other.closed == self.closed
-
     # --------------------------------------------------------------------
 
     @cache_readonly
@@ -911,7 +897,7 @@ def _format_data(self, name=None):
         return summary + "," + self._format_space()
 
     def _format_attrs(self):
-        attrs = [("closed", repr(self.closed))]
+        attrs = []
         if self.name is not None:
             attrs.append(("name", default_pprint(self.name)))
         attrs.append(("dtype", f"'{self.dtype}'"))
@@ -1117,7 +1103,6 @@ def interval_range(
 
     >>> pd.interval_range(start=0, end=5)
     IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],
-                  closed='right',
                   dtype='interval[int64, right]')
 
     Additionally, datetime-like input is also supported.
@@ -1126,15 +1111,15 @@ def interval_range(
     ...                   end=pd.Timestamp('2017-01-04'))
     IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03],
                    (2017-01-03, 2017-01-04]],
-                  closed='right', dtype='interval[datetime64[ns], right]')
+                  dtype='interval[datetime64[ns], right]')
 
     The ``freq`` parameter specifies the frequency between the left and right.
     endpoints of the individual intervals within the ``IntervalIndex``.  For
     numeric ``start`` and ``end``, the frequency must also be numeric.
 
     >>> pd.interval_range(start=0, periods=4, freq=1.5)
     IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
-                  closed='right', dtype='interval[float64, right]')
+                  dtype='interval[float64, right]')
 
     Similarly, for datetime-like ``start`` and ``end``, the frequency must be
     convertible to a DateOffset.
@@ -1143,22 +1128,21 @@ def interval_range(
     ...                   periods=3, freq='MS')
     IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01],
                    (2017-03-01, 2017-04-01]],
-                  closed='right', dtype='interval[datetime64[ns], right]')
+                  dtype='interval[datetime64[ns], right]')
 
     Specify ``start``, ``end``, and ``periods``; the frequency is generated
     automatically (linearly spaced).
 
     >>> pd.interval_range(start=0, end=6, periods=4)
     IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
-              closed='right',
               dtype='interval[float64, right]')
 
     The ``closed`` parameter specifies which endpoints of the individual
     intervals within the ``IntervalIndex`` are closed.
 
     >>> pd.interval_range(end=5, periods=4, closed='both')
     IntervalIndex([[1, 2], [2, 3], [3, 4], [4, 5]],
-                  closed='both', dtype='interval[int64, both]')
+                  dtype='interval[int64, both]')
     """
     start = maybe_box_datetimelike(start)
     end = maybe_box_datetimelike(end)

pandas/tests/arrays/interval/test_interval.py

@@ -131,7 +131,7 @@ def test_repr():
     expected = (
         "<IntervalArray>\n"
         "[(0, 1], (1, 2]]\n"
-        "Length: 2, closed: right, dtype: interval[int64, right]"
+        "Length: 2, dtype: interval[int64, right]"
     )
     assert result == expected