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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def copy(self: T, deep: bool = False, data: Mapping = None) -> T: """Returns a copy of this dataset. If `deep=True`, a deep copy is made of each of the component variables. Otherwise, a shallow copy of each of the component variable is made, so that the underlying memory region of the new dataset is the same as in the original dataset. Use `data` to create a new object with the same structure as original but entirely new data. Parameters deep : bool, optional Whether each component variable is loaded into memory and copied onto the new object. Default is False. data : dict-like, optional Data to use in the new object. Each item in `data` must have same shape as corresponding data variable in original. When `data` is used, `deep` is ignored for the data variables and only used for coords. Returns ------- object : Dataset New object with dimensions, attributes, coordinates, name, encoding, and optionally data copied from original. Examples -------- Shallow copy versus deep copy coords={'x': ['one', 'two']}) <xarray.Dataset> Dimensions: (dim_0: 2, dim_1: 3, x: 2) Coordinates: * x (x) <U3 'one' 'two' Dimensions without coordinates: dim_0, dim_1 Data variables: foo (dim_0, dim_1) float64 -0.8079 0.3897 -1.862 -0.6091 -1.051 -0.3003 bar (x) int64 -1 2 <xarray.Dataset> Dimensions: (dim_0: 2, dim_1: 3, x: 2) Coordinates: * x (x) <U3 'one' 'two' Dimensions without coordinates: dim_0, dim_1 Data variables: foo (dim_0, dim_1) float64 7.0 0.3897 -1.862 -0.6091 -1.051 -0.3003 bar (x) int64 -1 2 <xarray.Dataset> Dimensions: (dim_0: 2, dim_1: 3, x: 2) Coordinates: * x (x) <U3 'one' 'two' Dimensions without coordinates: dim_0, dim_1 Data variables: foo (dim_0, dim_1) float64 7.0 0.3897 -1.862 -0.6091 -1.051 -0.3003 bar (x) int64 -1 2 Changing the data using the ``data`` argument maintains the structure of the original object, but with the new data. Original object is unaffected. <xarray.Dataset> Dimensions: (dim_0: 2, dim_1: 3, x: 2) Coordinates: * x (x) <U3 'one' 'two' Dimensions without coordinates: dim_0, dim_1 Data variables: foo (dim_0, dim_1) int64 0 1 2 3 4 5 bar (x) <U1 'a' 'b' <xarray.Dataset> Dimensions: (dim_0: 2, dim_1: 3, x: 2) Coordinates: * x (x) <U3 'one' 'two' Dimensions without coordinates: dim_0, dim_1 Data variables: foo (dim_0, dim_1) float64 7.0 0.3897 -1.862 -0.6091 -1.051 -0.3003 bar (x) int64 -1 2 See Also -------- pandas.DataFrame.copy """
  # noqa
        if data is None:
            variables = OrderedDict((k, v.copy(deep=deep))
                                    for k, v in self._variables.items())
        elif not utils.is_dict_like(data):
            raise ValueError('Data must be dict-like')
        else:
            var_keys = set(self.data_vars.keys())
            data_keys = set(data.keys())
            keys_not_in_vars = data_keys - var_keys
            if keys_not_in_vars:
                raise ValueError(
                    'Data must only contain variables in original '
                    'dataset. Extra variables: {}'
                    .format(keys_not_in_vars))
            keys_missing_from_data = var_keys - data_keys
            if keys_missing_from_data:
                raise ValueError(
                    'Data must contain all variables in original '
                    'dataset. Data is missing {}'
                    .format(keys_missing_from_data))
            variables = OrderedDict((k, v.copy(deep=deep, data=data.get(k)))
                                    for k, v in self._variables.items())

        attrs = copy.deepcopy(self._attrs) if deep else copy.copy(self._attrs)

        return self._replace(variables, attrs=attrs)