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Module « pandas »

Fonction interval_range - module pandas

Signature de la fonction interval_range

def interval_range(start=None, end=None, periods=None, freq=None, name: 'Hashable | None' = None, closed: 'IntervalClosedType' = 'right') -> 'IntervalIndex' 

Description

help(pandas.interval_range)

Return a fixed frequency IntervalIndex.

Parameters
----------
start : numeric or datetime-like, default None
    Left bound for generating intervals.
end : numeric or datetime-like, default None
    Right bound for generating intervals.
periods : int, default None
    Number of periods to generate.
freq : numeric, str, Timedelta, datetime.timedelta, or DateOffset, default None
    The length of each interval. Must be consistent with the type of start
    and end, e.g. 2 for numeric, or '5H' for datetime-like.  Default is 1
    for numeric and 'D' for datetime-like.
name : str, default None
    Name of the resulting IntervalIndex.
closed : {'left', 'right', 'both', 'neither'}, default 'right'
    Whether the intervals are closed on the left-side, right-side, both
    or neither.

Returns
-------
IntervalIndex

See Also
--------
IntervalIndex : An Index of intervals that are all closed on the same side.

Notes
-----
Of the four parameters ``start``, ``end``, ``periods``, and ``freq``,
exactly three must be specified. If ``freq`` is omitted, the resulting
``IntervalIndex`` will have ``periods`` linearly spaced elements between
``start`` and ``end``, inclusively.

To learn more about datetime-like frequency strings, please see `this link
<https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.

Examples
--------
Numeric ``start`` and  ``end`` is supported.

>>> pd.interval_range(start=0, end=5)
IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],
              dtype='interval[int64, right]')

Additionally, datetime-like input is also supported.

>>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
...                   end=pd.Timestamp('2017-01-04'))
IntervalIndex([(2017-01-01 00:00:00, 2017-01-02 00:00:00],
               (2017-01-02 00:00:00, 2017-01-03 00:00:00],
               (2017-01-03 00:00:00, 2017-01-04 00:00:00]],
              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]],
              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')
IntervalIndex([(2017-01-01 00:00:00, 2017-02-01 00:00:00],
               (2017-02-01 00:00:00, 2017-03-01 00:00:00],
               (2017-03-01 00:00:00, 2017-04-01 00:00:00]],
              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]],
          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]],
              dtype='interval[int64, both]')

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