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Panel4D.to_xarray()
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Return an xarray object from the pandas object.
Returns: a DataArray for a Series
a Dataset for a DataFrame
a DataArray for higher dims
Notes
See the xarray docs
Examples
>>> df = pd.DataFrame({'A' : [1, 1, 2], 'B' : ['foo', 'bar', 'foo'], 'C' : np.arange(4.,7)}) >>> df A B C 0 1 foo 4.0 1 1 bar 5.0 2 2 foo 6.0
>>> df.to_xarray() <xarray.Dataset> Dimensions: (index: 3) Coordinates: * index (index) int64 0 1 2 Data variables: A (index) int64 1 1 2 B (index) object 'foo' 'bar' 'foo' C (index) float64 4.0 5.0 6.0
>>> df = pd.DataFrame({'A' : [1, 1, 2], 'B' : ['foo', 'bar', 'foo'], 'C' : np.arange(4.,7)} ).set_index(['B','A']) >>> df C B A foo 1 4.0 bar 1 5.0 foo 2 6.0
>>> df.to_xarray() <xarray.Dataset> Dimensions: (A: 2, B: 2) Coordinates: * B (B) object 'bar' 'foo' * A (A) int64 1 2 Data variables: C (B, A) float64 5.0 nan 4.0 6.0
>>> p = pd.Panel(np.arange(24).reshape(4,3,2), items=list('ABCD'), major_axis=pd.date_range('20130101', periods=3), minor_axis=['first', 'second']) >>> p <class 'pandas.core.panel.Panel'> Dimensions: 4 (items) x 3 (major_axis) x 2 (minor_axis) Items axis: A to D Major_axis axis: 2013-01-01 00:00:00 to 2013-01-03 00:00:00 Minor_axis axis: first to second
>>> p.to_xarray() <xarray.DataArray (items: 4, major_axis: 3, minor_axis: 2)> array([[[ 0, 1], [ 2, 3], [ 4, 5]], [[ 6, 7], [ 8, 9], [10, 11]], [[12, 13], [14, 15], [16, 17]], [[18, 19], [20, 21], [22, 23]]]) Coordinates: * items (items) object 'A' 'B' 'C' 'D' * major_axis (major_axis) datetime64[ns] 2013-01-01 2013-01-02 2013-01-03 # noqa * minor_axis (minor_axis) object 'first' 'second'
Panel4D.to_xarray()
2017-01-12 04:52:42
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