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Method from_series

xarray/core/dataarray.py:4649–4675  ·  view source on GitHub ↗

Convert a pandas.Series into an xarray.DataArray. If the series's index is a MultiIndex, it will be expanded into a tensor product of one-dimensional coordinates (filling in missing values with NaN). Thus this operation should be the inverse of the `to_series` method

(cls, series: pd.Series, sparse: bool = False)

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4647
4648 @classmethod
4649 def from_series(cls, series: pd.Series, sparse: bool = False) -> DataArray:
4650 """Convert a pandas.Series into an xarray.DataArray.
4651
4652 If the series's index is a MultiIndex, it will be expanded into a
4653 tensor product of one-dimensional coordinates (filling in missing
4654 values with NaN). Thus this operation should be the inverse of the
4655 `to_series` method.
4656
4657 Parameters
4658 ----------
4659 series : Series
4660 Pandas Series object to convert.
4661 sparse : bool, default: False
4662 If sparse=True, creates a sparse array instead of a dense NumPy array.
4663 Requires the pydata/sparse package.
4664
4665 See Also
4666 --------
4667 DataArray.to_series
4668 Dataset.from_dataframe
4669 """
4670 temp_name = "__temporary_name"
4671 df = pd.DataFrame({temp_name: series})
4672 ds = Dataset.from_dataframe(df, sparse=sparse)
4673 result = ds[temp_name]
4674 result.name = series.name
4675 return result
4676
4677 def to_iris(self) -> iris_Cube:
4678 """Convert this array into an iris.cube.Cube"""

Calls 1

from_dataframeMethod · 0.80