issues: 327591169

Code Sample, a copy-pastable example if possible

```python import numpy as np import pandas as pd import xarray as xr

time = np.arange('2007-02-01', '2007-03-02', dtype='datetime64').astype('datetime64[ns]') arr = xr.DataArray( np.arange(time.size), coords=[time,], dims=('time',), name='data' ) arr.resample(time='M').interpolate('linear')

---

ValueError Traceback (most recent call last) <ipython-input-20-ff65c4d138e7> in <module>() 7 np.arange(time.size), coords=[time,], dims=('time',), name='data' 8 ) ----> 9 arr.resample(time='M').interpolate('linear')

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/xarray/core/resample.py in interpolate(self, kind) 108 109 """ --> 110 return self._interpolate(kind=kind) 111 112 def _interpolate(self, kind='linear'):

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/xarray/core/resample.py in _interpolate(self, kind) 218 elif self._dim not in v.dims: 219 coords[k] = v --> 220 return DataArray(f(new_x), coords, dims, name=dummy.name, 221 attrs=dummy.attrs) 222

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/scipy/interpolate/polyint.py in call(self, x) 77 """ 78 x, x_shape = self._prepare_x(x) ---> 79 y = self._evaluate(x) 80 return self._finish_y(y, x_shape) 81

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/scipy/interpolate/interpolate.py in _evaluate(self, x_new) 632 y_new = self._call(self, x_new) 633 if not self._extrapolate: --> 634 below_bounds, above_bounds = self._check_bounds(x_new) 635 if len(y_new) > 0: 636 # Note fill_value must be broadcast up to the proper size

~/devel/c3s-cns/venv_op/lib/python3.6/site-packages/scipy/interpolate/interpolate.py in _check_bounds(self, x_new) 664 "range.") 665 if self.bounds_error and above_bounds.any(): --> 666 raise ValueError("A value in x_new is above the interpolation " 667 "range.") 668

ValueError: A value in x_new is above the interpolation range.

```

Problem description

It raise an error if I try to interpolate. If time range is exactly a month, then it works: ```python time = np.arange('2007-02-01', '2007-03-01', dtype='datetime64').astype('datetime64[ns]') arr = xr.DataArray( np.arange(time.size), coords=[time,], dims=('time',), name='data' ) arr.resample(time='M').interpolate('linear')

<xarray.DataArray 'data' (time: 1)> array([27.]) Coordinates: * time (time) datetime64[ns] 2007-02-28 ```

The problem for the interpolation seems to be that the resampler contains indices out bound ('2007-03-31'). It is ok for the aggregations, but it doesn't work with the interpolation.

```python resampler = arr.resample(time='M')

resampler._full_index DatetimeIndex(['2007-02-28', '2007-03-31'], dtype='datetime64[ns]', name='time', freq='M') ```

Expected Output

python <xarray.DataArray 'data' (time: 1)> array([27.]) Coordinates: * time (time) datetime64[ns] 2007-02-28

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.0.final.0 python-bits: 64 OS: Linux OS-release: 4.13.0-43-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 xarray: 0.10.3 pandas: 0.22.0 numpy: 1.14.3 scipy: 1.1.0 netCDF4: 1.3.1 h5netcdf: None h5py: None Nio: None zarr: None bottleneck: None cyordereddict: None dask: 0.17.4 distributed: None matplotlib: 2.2.2 cartopy: 0.16.0 seaborn: None setuptools: 39.2.0 pip: 10.0.1 conda: None pytest: 3.5.1 IPython: 6.4.0 sphinx: 1.7.4