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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 _init_dict(self, data, index=None, dtype=None):
 """ Derive the "_data" and "index" attributes of a new Series from a dictionary input. Parameters data : dict or dict-like Data used to populate the new Series index : Index or index-like, default None index for the new Series: if None, use dict keys dtype : dtype, default None dtype for the new Series: if None, infer from data Returns ------- _data : BlockManager for the new Series index : index for the new Series """

        # Looking for NaN in dict doesn't work ({np.nan : 1}[float('nan')]
        # raises KeyError), so we iterate the entire dict, and align
        if data:
            keys, values = zip(*data.items())
            values = list(values)
        elif index is not None:
            # fastpath for Series(data=None). Just use broadcasting a scalar
            # instead of reindexing.
            values = na_value_for_dtype(dtype)
            keys = index
        else:
            keys, values = [], []

        # Input is now list-like, so rely on "standard" construction:
        s = Series(values, index=keys, dtype=dtype)

        # Now we just make sure the order is respected, if any
        if data and index is not None:
            s = s.reindex(index, copy=False)
        elif not PY36 and not isinstance(data, OrderedDict) and data:
            # Need the `and data` to avoid sorting Series(None, index=[...])
            # since that isn't really dict-like
            try:
                s = s.sort_index()
            except TypeError:
                pass
        return s._data, s.index