test

Author: chean.wei.khor

pandas/core/indexes/interval.py

@@ -1016,7 +1016,7 @@ def interval_range(
     Additionally, datetime-like input is also supported.
 
     >>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
-    ...                   end=pd.Timestamp('2017-01-04'))
+    ...                   end=pd.Timestamp('2017-01-04'), inclusive="right")
     IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03],
                    (2017-01-03, 2017-01-04]],
                   dtype='interval[datetime64[ns], right]')
@@ -1025,23 +1025,23 @@ def interval_range(
     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)
+    >>> pd.interval_range(start=0, periods=4, freq=1.5, inclusive="right")
     IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
                   dtype='interval[float64, right]')
 
     Similarly, for datetime-like ``start`` and ``end``, the frequency must be
     convertible to a DateOffset.
 
     >>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
-    ...                   periods=3, freq='MS')
+    ...                   periods=3, freq='MS', inclusive="right")
     IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01],
                    (2017-03-01, 2017-04-01]],
                   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)
+    >>> pd.interval_range(start=0, end=6, periods=4, inclusive="right")
     IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
               dtype='interval[float64, right]')