You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
@jreback I'll spend some time getting a better feel for how/if we could push some of the backend into pandas' HDFStore. Certainly, we'd like to leverage other more powerful packages (pandas, numpy) as much as possible. Thanks for the suggestion.
I'm going to close this, given that pandas doesn't currently have appropriate data structures for representing arbitrary dimensional NetCDF variables. These data structures (N-dimensional labeled arrays like xray.DataArray) are a major motivation for why we wrote xray.
You can represent higher dimensional arrays as a pandas.Series with a hierarchical index, but this representation has a much less directly connection to NetCDF datasets on disk. I think it makes more sense to make the objects in xray first (since our data models basically matches netCDF), and then convert xray Datasets into pandas DataFrames. We do in fact support this via the to_series and to_dataframe methods, e.g., xray.open_dataset('foo.nc').to_dataframe().
That said, I am not opposed to integrating some or all of xray into pandas -- but that's a much bigger discussion.
see this related issue: pandas-dev/pandas#5487
this is actually not hard to do, and might allow you to push some of your backends to pandas.
The text was updated successfully, but these errors were encountered: