title: Method for Time Slicing in Netcdf similar to xarray
body: <p>I have a NetCDF data file containing sea ice concentration</p>
  
  <pre><code>from netCDF4 import Dataset
  ds = Dataset('file.nic', 'r')
  ds.variables.keys()
  &gt;&gt;odict_keys(['latitude', 'longitude', 'seaice_conc', 'seaice_source', 'time'])
  ds.dimensions.keys()
  &gt;&gt;odict_keys(['latitude', 'longitude', 'time'])
  </code></pre>
  
  <p><strong>Question</strong>: In this dataset, time is stored as days since 2001-01-01 00:00:00. Let's say I want seaice_conc for a particular time = 1990-12-01 then how do I approach it without using xarray or writing another function to calculate the days difference.
  Is it possible to do it like in xarrays, for eg;</p>
  
  <pre><code>import xarray as xr
  ds1 = xr.open_dataset('file.nc')
  seaice_data = ds1['seaice_conc'].sel(time = '1990-12-01')
  </code></pre>
  
  <p>To give further info on dataset, it looks like this:</p>
  
  <pre><code>ds1.seaice_conc
  &lt;xarray.DataArray 'seaice_conc' (time: 1968, latitude: 240, longitude: 
  1440)&gt;
  [680140800 values with dtype=float32]
  Coordinates:
  * latitude   (latitude) float32 89.875 89.625 89.375 89.125 88.875 88.625 
  ...
  * longitude  (longitude) float32 0.125 0.375 0.625 0.875 1.125 1.375 1.625 
  ...
  * time       (time) datetime64[ns] 1850-01-15 1850-02-15 1850-03-15 ...
  Attributes:
  short_name: concentration
  long_name: Sea_Ice_Concentration
  standard_name: Sea_Ice_Concentration
  units: Percent
  </code></pre>
  
  <p><em>Another thing</em> which I'm confused is that using netcdf it says that time is stored in days since 2001:01:01 but in xarrays it shows me the exact date in yyyy-mm-dd format instead of showing the 'days since...' definition?</p>
  
  <p>Thanks!</p>