xarray/core/variable.py
def copy(self, deep=True, data=None):
        """Returns a copy of this object.

        `deep` is ignored since data is stored in the form of
        pandas.Index, which is already immutable. Dimensions, attributes
        and encodings are always copied.

        Use `data` to create a new object with the same structure as
        original but entirely new data.

        Parameters
        ----------
        deep : bool, optional
            Deep is ignored when data is given. Whether the data array is
            loaded into memory and copied onto the new object. Default is True.
        data : array_like, optional
            Data to use in the new object. Must have same shape as original.

        Returns
        -------
        object : Variable
            New object with dimensions, attributes, encodings, and optionally
            data copied from original.
        """
        if data is None:
            data = self._data.copy(deep=deep)
        else:
            data = as_compatible_data(data)
            if self.shape != data.shape:
                raise ValueError(
                    "Data shape {} must match shape of object {}".format(
                        data.shape, self.shape
                    )
                )
        return type(self)(self.dims, data, self._attrs, self._encoding, fastpath=True)
Returns a copy of this object.

        `deep` is ignored since data is stored in the form of
        pandas.Index, which is already immutable. Dimensions, attributes
        and encodings are always copied.

        Use `data` to create a new object with the same structure as
        original but entirely new data.

        Parameters
        ----------
        deep : bool, optional
            Deep is ignored when data is given. Whether the data array is
            loaded into memory and copied onto the new object. Default is True.
        data : array_like, optional
            Data to use in the new object. Must have same shape as original.

        Returns
        -------
        object : Variable
            New object with dimensions, attributes, encodings, and optionally
            data copied from original.
        
Returns a copy of this object.
`deep` is ignored since data is stored in the form of
pandas.Index, which is already immutable. Dimensions, attributes
and encodings are always copied.

Use `data` to create a new object with the same structure as
original but entirely new data.

Parameters

deep : bool, optional
Deep is ignored when data is given. Whether the data array is
loaded into memory and copied onto the new object. Default is True.
data : array_like, optional
Data to use in the new object. Must have same shape as original.

Returns

object : Variable
New object with dimensions, attributes, encodings, and optionally
data copied from original.
Returns a copy of this object . ` deep ` is ignored since data is stored in the form of pandas . Index which is already immutable . Dimensions attributes and encodings are always copied . Use ` data ` to create a new object with the same structure as original but entirely new data . Parameters deep : bool optional Deep is ignored when data is given . Whether the data array is loaded into memory and copied onto the new object . Default is True . data : array_like optional Data to use in the new object . Must have same shape as original . Returns object : Variable New object with dimensions attributes encodings and optionally data copied from original .
def copy(self, deep=True, data=None):
        if data is None:
            data = self._data.copy(deep=deep)
        else:
            data = as_compatible_data(data)
            if self.shape != data.shape:
                raise ValueError(
                    "Data shape {} must match shape of object {}".format(
                        data.shape, self.shape
                    )
                )
        return type(self)(self.dims, data, self._attrs, self._encoding, fastpath=True)
def copy ( self , deep = True , data = None ) : if data is None : data = self . _data . copy ( deep = deep ) else : data = as_compatible_data ( data ) if self . shape != data . shape : raise ValueError ( "Data shape {} must match shape of object {}" . format ( data . shape , self . shape ) ) return type ( self ) ( self . dims , data , self . _attrs , self . _encoding , fastpath = True )
Returns a copy of this object.
Returns a copy of this object .
"""Returns a copy of this object.

        `deep` is ignored since data is stored in the form of
        pandas.Index, which is already immutable. Dimensions, attributes
        and encodings are always copied.

        Use `data` to create a new object with the same structure as
        original but entirely new data.

        Parameters
        ----------
        deep : bool, optional
            Deep is ignored when data is given. Whether the data array is
            loaded into memory and copied onto the new object. Default is True.
        data : array_like, optional
            Data to use in the new object. Must have same shape as original.

        Returns
        -------
        object : Variable
            New object with dimensions, attributes, encodings, and optionally
            data copied from original.
        """
self
deep
data