Rows are candidate names and columns are rank numbers. Tuple]] get_cumulative_ranking_tables ( ) → Tuple # Tuple containing count table, percent table, and name of condorcet winner. Symmetric cells about the diagonal should sum to 100 (for the percent table).īallots used in condorcet calculation have election rules applied to them. The denominator is each cell is the number of ballots that ranked the row-candidate OR the column-candidate. The column-candidate (including ballots that only ranked the row-candidate). Also return the name of the condorcet winner, or None.Įach cell indicates the count/percentage of ballots that ranked the row-candidate over One contains counts and the other contains percents. Optional get_condorcet_tables ( ) → Tuple ] ] # Tabulation_num ( int, optional) – tabulation num, defaults to 1 Return type Generate table of candidate round by round vote counts. Get_candidate_details_table ( tabulation_num : int = 1 ) → Optional # Measure where winners ranked on ballots that ended up in their final pile. Get_winner_final_pile_rank_distribution_table() Get_round_by_round_table()Ĭreate a table containing round by round details for the tabulation.

Get_round_by_round_dict()Ĭreate a dictionary containing election round by round information that matches the nesting structure of RCVIS upload format. Return pandas dataframes containing first and second choice candidate distributions across ballots. Get_first_choice_to_finalist_table()Ĭreate a pandas dataframe describing the first choice candidate distribution and which finalist candidate those ballots ended the tabulation allocated to. Returns a two condorcet tables as a pandas data frame with candidate names as row and column indices.

Tablecruncher