pandas.DataFrame.to_xarray — pandas 3.0.0.dev0+2103.g41968a550a 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[s] 2018-01-01 2018-01-02
• animal (animal) object 'falcon' 'parrot' Data variables: speed (date, animal) int64 350 18 361 15