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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 difference(self, other, sort=None):
 """ Return a new Index with elements from the index that are not in `other`. This is the set difference of two Index objects. Parameters other : Index or array-like sort : False or None, default None Whether to sort the resulting index. By default, the values are attempted to be sorted, but any TypeError from incomparable elements is caught by pandas. * None : Attempt to sort the result, but catch any TypeErrors from comparing incomparable elements. * False : Do not sort the result. .. versionadded:: 0.24.0 .. versionchanged:: 0.24.1 Changed the default value from ``True`` to ``None`` (without change in behaviour). Returns ------- difference : Index Examples -------- Int64Index([1, 2], dtype='int64') Int64Index([2, 1], dtype='int64') """

        self._validate_sort_keyword(sort)
        self._assert_can_do_setop(other)

        if self.equals(other):
            # pass an empty np.ndarray with the appropriate dtype
            return self._shallow_copy(self._data[:0])

        other, result_name = self._convert_can_do_setop(other)

        this = self._get_unique_index()

        indexer = this.get_indexer(other)
        indexer = indexer.take((indexer != -1).nonzero()[0])

        label_diff = np.setdiff1d(np.arange(this.size), indexer,
                                  assume_unique=True)
        the_diff = this.values.take(label_diff)
        if sort is None:
            try:
                the_diff = sorting.safe_sort(the_diff)
            except TypeError:
                pass

        return this._shallow_copy(the_diff, name=result_name, freq=None)