@@ -1016,7 +1016,7 @@ def interval_range(
10161016 Additionally, datetime-like input is also supported.
10171017
10181018 >>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
1019- ... end=pd.Timestamp('2017-01-04'))
1019+ ... end=pd.Timestamp('2017-01-04'), inclusive="right" )
10201020 IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03],
10211021 (2017-01-03, 2017-01-04]],
10221022 dtype='interval[datetime64[ns], right]')
@@ -1025,23 +1025,23 @@ def interval_range(
10251025 endpoints of the individual intervals within the ``IntervalIndex``. For
10261026 numeric ``start`` and ``end``, the frequency must also be numeric.
10271027
1028- >>> pd.interval_range(start=0, periods=4, freq=1.5)
1028+ >>> pd.interval_range(start=0, periods=4, freq=1.5, inclusive="right" )
10291029 IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
10301030 dtype='interval[float64, right]')
10311031
10321032 Similarly, for datetime-like ``start`` and ``end``, the frequency must be
10331033 convertible to a DateOffset.
10341034
10351035 >>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
1036- ... periods=3, freq='MS')
1036+ ... periods=3, freq='MS', inclusive="right" )
10371037 IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01],
10381038 (2017-03-01, 2017-04-01]],
10391039 dtype='interval[datetime64[ns], right]')
10401040
10411041 Specify ``start``, ``end``, and ``periods``; the frequency is generated
10421042 automatically (linearly spaced).
10431043
1044- >>> pd.interval_range(start=0, end=6, periods=4)
1044+ >>> pd.interval_range(start=0, end=6, periods=4, inclusive="right" )
10451045 IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
10461046 dtype='interval[float64, right]')
10471047
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