pandas.DataFrame.to_xarray — pandas 2.2.3 documentation (original) (raw)

DataFrame.to_xarray()[source]#

Return an xarray object from the pandas object.

Returns:

xarray.DataArray or xarray.Dataset

Data in the pandas structure converted to Dataset if the object is a DataFrame, or a DataArray if the object is a Series.

Notes

See the xarray docs

Examples

df = pd.DataFrame([('falcon', 'bird', 389.0, 2), ... ('parrot', 'bird', 24.0, 2), ... ('lion', 'mammal', 80.5, 4), ... ('monkey', 'mammal', np.nan, 4)], ... columns=['name', 'class', 'max_speed', ... 'num_legs']) df name class max_speed num_legs 0 falcon bird 389.0 2 1 parrot bird 24.0 2 2 lion mammal 80.5 4 3 monkey mammal NaN 4

df.to_xarray()
<xarray.Dataset> Dimensions: (index: 4) Coordinates:

• index (index) int64 32B 0 1 2 3 Data variables: name (index) object 32B 'falcon' 'parrot' 'lion' 'monkey' class (index) object 32B 'bird' 'bird' 'mammal' 'mammal' max_speed (index) float64 32B 389.0 24.0 80.5 nan num_legs (index) int64 32B 2 2 4 4

df['max_speed'].to_xarray()
<xarray.DataArray 'max_speed' (index: 4)> array([389. , 24. , 80.5, nan]) Coordinates:

• index (index) int64 0 1 2 3

dates = pd.to_datetime(['2018-01-01', '2018-01-01', ... '2018-01-02', '2018-01-02']) df_multiindex = pd.DataFrame({'date': dates, ... 'animal': ['falcon', 'parrot', ... 'falcon', 'parrot'], ... 'speed': [350, 18, 361, 15]}) df_multiindex = df_multiindex.set_index(['date', 'animal'])

df_multiindex speed date animal 2018-01-01 falcon 350 parrot 18 2018-01-02 falcon 361 parrot 15

df_multiindex.to_xarray()
<xarray.Dataset> Dimensions: (date: 2, animal: 2) Coordinates:

• date (date) datetime64[ns] 2018-01-01 2018-01-02
• animal (animal) object 'falcon' 'parrot' Data variables: speed (date, animal) int64 350 18 361 15