Classe « Index »
Signature de la méthode shift
def shift(self, periods=1, freq=None)
Description
shift.__doc__
Shift index by desired number of time frequency increments.
This method is for shifting the values of datetime-like indexes
by a specified time increment a given number of times.
Parameters
----------
periods : int, default 1
Number of periods (or increments) to shift by,
can be positive or negative.
freq : pandas.DateOffset, pandas.Timedelta or str, optional
Frequency increment to shift by.
If None, the index is shifted by its own `freq` attribute.
Offset aliases are valid strings, e.g., 'D', 'W', 'M' etc.
Returns
-------
pandas.Index
Shifted index.
See Also
--------
Series.shift : Shift values of Series.
Notes
-----
This method is only implemented for datetime-like index classes,
i.e., DatetimeIndex, PeriodIndex and TimedeltaIndex.
Examples
--------
Put the first 5 month starts of 2011 into an index.
>>> month_starts = pd.date_range('1/1/2011', periods=5, freq='MS')
>>> month_starts
DatetimeIndex(['2011-01-01', '2011-02-01', '2011-03-01', '2011-04-01',
'2011-05-01'],
dtype='datetime64[ns]', freq='MS')
Shift the index by 10 days.
>>> month_starts.shift(10, freq='D')
DatetimeIndex(['2011-01-11', '2011-02-11', '2011-03-11', '2011-04-11',
'2011-05-11'],
dtype='datetime64[ns]', freq=None)
The default value of `freq` is the `freq` attribute of the index,
which is 'MS' (month start) in this example.
>>> month_starts.shift(10)
DatetimeIndex(['2011-11-01', '2011-12-01', '2012-01-01', '2012-02-01',
'2012-03-01'],
dtype='datetime64[ns]', freq='MS')
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