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use pandas Grouper instead of TimeGrouper #1767

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Merged
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Dec 7, 2017
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use pandas Grouper instead of TimeGrouper #1767

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7 changes: 6 additions & 1 deletion doc/whats-new.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -21,8 +21,13 @@ v0.10.1 (unreleased)
Enhancements
~~~~~~~~~~~~

- :py:func:`~plot.contourf()` learned to contour 2D variables that have both a 1D co-ordinate (e.g. time) and a 2D co-ordinate (e.g. depth as a function of time).
- :py:func:`~plot.contourf()` learned to contour 2D variables that have both a
1D co-ordinate (e.g. time) and a 2D co-ordinate (e.g. depth as a function of
time) (:issue:`1737`).
By `Deepak Cherian <https://github.com/dcherian>`_.
- Use ``pandas.Grouper`` class in xarray resample methods rather than the
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Not sure this is really an enhancement? (not to detract from the honorable work!)

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Fair point. I have a few more small fixes coming so we can bump it down into a miscellaneous fixes category.

deprecated ``pandas.TimeGrouper`` class (:issue:`1766`).
By `Joe Hamman <https://github.com/jhamman>`_.


Bug fixes
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11 changes: 5 additions & 6 deletions xarray/core/common.py
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Expand Up @@ -590,10 +590,9 @@ def resample(self, freq=None, dim=None, how=None, skipna=None,
raise TypeError("Dimension name should be a string; "
"was passed %r" % dim)
group = DataArray(dim, [(dim.dims, dim)], name=RESAMPLE_DIM)
time_grouper = pd.TimeGrouper(freq=freq, closed=closed,
label=label, base=base)
grouper = pd.Grouper(freq=freq, closed=closed, label=label, base=base)
resampler = self._resample_cls(self, group=group, dim=dim_name,
grouper=time_grouper,
grouper=grouper,
resample_dim=RESAMPLE_DIM)

return resampler
Expand All @@ -615,9 +614,9 @@ def _resample_immediately(self, freq, dim, how, skipna,
if isinstance(dim, basestring):
dim = self[dim]
group = DataArray(dim, [(dim.dims, dim)], name=RESAMPLE_DIM)
time_grouper = pd.TimeGrouper(freq=freq, how=how, closed=closed,
label=label, base=base)
gb = self._groupby_cls(self, group, grouper=time_grouper)
grouper = pd.Grouper(freq=freq, how=how, closed=closed, label=label,
base=base)
gb = self._groupby_cls(self, group, grouper=grouper)
if isinstance(how, basestring):
f = getattr(gb, how)
if how in ['first', 'last']:
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