def standings(self):
doc = self.get_sub_doc('<STR_LIT>')<EOL>east_table = doc('<STR_LIT>')<EOL>east_df = pd.DataFrame(sportsref.utils.parse_table(east_table))<EOL>east_df.sort_values('<STR_LIT>', ascending=False, inplace=True)<EOL>east_df['<STR_LIT>'] = range(<NUM_LIT:1>, len(east_df) + <NUM_LIT:1>)<EOL>east_df['<STR_LIT>'] = '<STR_LIT:E>'<EOL>west_table = doc('<STR_LIT>')<EOL>west_df = sportsref.utils.parse_table(west_table)<EOL>west_df.sort_values('<STR_LIT>', ascending=False, inplace=True)<EOL>west_df['<STR_LIT>'] = range(<NUM_LIT:1>, len(west_df) + <NUM_LIT:1>)<EOL>west_df['<STR_LIT>'] = '<STR_LIT>'<EOL>full_df = pd.concat([east_df, west_df], axis=<NUM_LIT:0>).reset_index(drop=True)<EOL>full_df['<STR_LIT>'] = full_df.team_id.str.extract(r'<STR_LIT>', expand=False)<EOL>full_df['<STR_LIT>'] = [gb if isinstance(gb, int) or isinstance(gb, float) else <NUM_LIT:0><EOL>for gb in full_df['<STR_LIT>']]<EOL>full_df = full_df.drop('<STR_LIT>', axis=<NUM_LIT:1>)<EOL>expanded_table = doc('<STR_LIT>')<EOL>expanded_df = sportsref.utils.parse_table(expanded_table)<EOL>full_df = pd.merge(full_df, expanded_df, on='<STR_LIT>')<EOL>return full_df<EOL>
Returns a DataFrame containing standings information.