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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 _process_diff(self, yes_work, maybe_work, work_dir, ym_results_path, yn_results_path, stats):
 """Returns statistics on the difference between the intersection of `yes_work` and `maybe_work` and the intersection of `yes_work` and "no" works. :param yes_work: name of work for which stats are collected :type yes_work: `str` :param maybe_work: name of work being compared with `yes_work` :type maybe_work: `str` :param work_dir: directory where generated files are saved :type work_dir: `str` :param ym_results_path: path to results intersecting `yes_work` with `maybe_work` :type yn_results_path: `str` :param yn_results_path: path to results intersecting `yes_work` with "no" works :type yn_results_path: `str` :param stats: data structure to hold the statistical data :type stats: `dict` :rtype: `dict` """

        distinct_results_path = os.path.join(
            work_dir, 'distinct_{}.csv'.format(maybe_work))
        results = [yn_results_path, ym_results_path]
        labels = [self._no_label, self._maybe_label]
        self._run_query(distinct_results_path, self._store.diff_supplied,
                        [results, labels, self._tokenizer])
        return self._update_stats('diff', work_dir, distinct_results_path,
                                  yes_work, maybe_work, stats, SHARED, COMMON)