opt/scitools/environments/default/2021_03_18-1/lib/python3.6/site-packages/xarray/core/dataset.py in update(self, other) opt/scitools/environments/default/2021_03_18-1/lib/python3.6/site-packages/xarray/core/dataset.py in _set_numpy_data_from_dataframe(self, idx, arrays, dims)ĥ062 data = np.zeros(shape, values.dtype)ġ431 def _delitem_(self, key: Hashable) -> None: > 5133 obj._set_numpy_data_from_dataframe(idx, arrays, dims) > 2820 return _dataframe(self)Ģ822 in from_dataframe(cls, dataframe, sparse)ĥ131 obj._set_sparse_data_from_dataframe(idx, arrays, dims) opt/scitools/environments/default/2021_03_18-1/lib/python3.6/site-packages/pandas/core/generic.py in to_xarray(self)Ģ818 return _series(self) (v1.0.1 gives "ValueError: all arrays must be same length"). It seems to me it ought to be straightfoward enough using pandas.crosstab followed by DataFrame.to_xarray() but I'm getting "TypeError: Cannot interpret 'interval' as a data type" in pandas v1.1.5. I want to create a multiway contingency table from my pandas dataframe and store it in an xarray.
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