DataFrame.to_xarray() [source]
从pandas对象返回一个xarray对象。
返回值 ： xarray.DataArray 或 xarray.Dataset
如果对象是DataFrame，则将pandas结构中的数据转换为Dataset，如果对象是Series，则转换为DataArray。
Notes
请参阅xarray文档
例子
>>> 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_legs0 falcon bird 389.0 21 parrot bird 24.0 22 lion mammal 80.5 43 monkey mammal NaN 4>>> df.to_xarray()Dimensions: (index: 4)Coordinates: * index (index) int64 0 1 2 3Data variables: name (index) object 'falcon' 'parrot' 'lion' 'monkey' class (index) object 'bird' 'bird' 'mammal' 'mammal' max_speed (index) float64 389.0 24.0 80.5 nan num_legs (index) int64 2 2 4 4
>>> df['max_speed'].to_xarray()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 speeddate animal2018-01-01 falcon 350 parrot 182018-01-02 falcon 361 parrot 15
>>> df_multiindex.to_xarray()Dimensions: (animal: 2, date: 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