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object : the return type of ``func``.
Notes
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Use ``.pipe`` when chaining together functions that expect
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>>> f(g(h(ds), arg1=a), arg2=b, arg3=c)
You can write
>>> (ds.pipe(h)
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If "group" is a dimension of any arrays in this dataset, `squeeze`
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that dimension or if the dimension is squeezed out.
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object, they will be given the value ``NaN``.
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freq : str
String in the '#offset' to specify the step-size along the
resampled dimension, where '#' is an (optional) integer multipler
(default 1) and 'offset' is any pandas date offset alias. Examples
of valid offsets include:
* 'AS': year start
* 'QS-DEC': quarterly, starting on December 1
* 'MS': month start
* 'D': day
* 'H': hour
* 'Min': minute
The full list of these offset aliases is documented in pandas [1]_.
dim : str
Name of the dimension to resample along (e.g., 'time').
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ndarray values along the given axis. Valid choices that can be
provided as a string include all the usual Dataset/DataArray
aggregations (``all``, ``any``, ``argmax``, ``argmin``, ``max``,
``mean``, ``median``, ``min``, ``prod``, ``sum``, ``std`` and
``var``), as well as ``first`` and ``last``.
skipna : bool, optional
Whether to skip missing values when aggregating in downsampling.
closed : 'left' or 'right', optional
Side of each interval to treat as closed.
label : 'left or 'right', optional
Side of each interval to use for labeling.
base : int, optionalt
For frequencies that evenly subdivide 1 day, the "origin" of the
aggregated intervals. For example, for '24H' frequency, base could
range from 0 through 23.
Returns
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This object resampled.
References
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.. [1] http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
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Examples
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>>> import numpy as np
>>> a = xr.DataArray(np.arange(25).reshape(5, 5), dims=('x', 'y'))
>>> a.where((a > 6) & (a < 18))
<xarray.DataArray (x: 5, y: 5)>
array([[ nan, nan, nan, nan, nan],
[ nan, nan, 7., 8., 9.],
[ 10., 11., 12., 13., 14.],
[ 15., 16., 17., nan, nan],
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