API Documentation¶
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class
candystore.
CandyStore
(seasons: Union[int, Tuple[int, int]] = 1)¶ Data factory for different data sets related to AFL matches.
Parameters: seasons – The seasons to generate data for. If an integer, will start from a random year for which AFL data exists and increment for the given number of years. If a tuple of integers, will generate fixtures for the given range of years (same rules as Python’s range). -
seasons
¶ The seasons for which fake data is generated.
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betting_odds
(to_dict: Optional[str] = None) → Union[pandas.core.frame.DataFrame, List[candystore.betting_odds.BettingData]]¶ Generate betting odds data for the given seasons.
Parameters: to_dict – Type of dictionary data to return (passed directly to Panda’s to_dict method). None returns a DataFrame. Returns: DataFrame or list of betting odds dictionaries that replicate fitzRoy’s get_footywire_betting_odds function, but with Pythonic conventions (e.g. snake_case keys) Return type: pd.DataFrame or list(dict) Examples
{ "date": "1967-03-21 18:40:59", "season": 1967, "home_team": "Sydney", "away_team": "Fremantle", "venue": "Wellington", "round": 1, "home_score": 26, "away_score": 89, "home_margin": -63, "away_margin": 63, "home_win_odds": 2.71, "away_win_odds": 1.13, "home_win_paid": 0.0, "away_win_paid": 1.13, "home_line_odds": 33, "away_line_odds": -33, "home_line_paid": 0.0, "away_line_paid": 1.92 }
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fixtures
(to_dict: Optional[str] = None) → Union[pandas.core.frame.DataFrame, List[candystore.fixtures.FixtureData]]¶ Generate fixture data for the given seasons.
Parameters: to_dict – Type of dictionary data to return (passed directly to Panda’s to_dict method). None returns a DataFrame. Returns: DataFrame or list of fixture dictionaries that replicate fitzRoy’s get_fixture function, but with Pythonic conventions (e.g. snake_case keys) Return type: pd.DataFrame or list(dict) Examples
{ "date": "1967-03-16 12:37:19", "season": 1967, "season_game": 1, "round": 1, "home_team": "Melbourne", "away_team": "Brisbane Lions", "venue": "Sydney Showground" }
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match_results
(to_dict: Optional[str] = None) → Union[pandas.core.frame.DataFrame, List[candystore.match_results.MatchResultsData]]¶ Generate match results data data for the given seasons.
Parameters: to_dict – Type of dictionary data to return (passed directly to Panda’s to_dict method). None returns a DataFrame. Returns: DataFrame or list of match dictionaries that replicate fitzRoy’s get_match_results function, but with Pythonic conventions (e.g. snake_case keys) Return type: pd.DataFrame or list(dict) Examples
{ "date": "1933-03-18", "season": 1933, "round": "R1", "home_team": "Gold Coast", "away_team": "Adelaide", "venue": "Princes Park", "game": 0, "round_number": 1, "round_type": "Regular", "home_goals": 2, "home_behinds": 11, "home_points": 23, "away_goals": 21, "away_behinds": 17, "away_points": 143, "margin": -120 }
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players
(to_dict: Optional[str] = None) → Union[pandas.core.frame.DataFrame, List[candystore.players.PlayerData]]¶ Generate player data data for the given seasons.
Parameters: to_dict – Type of dictionary data to return (passed directly to Panda’s to_dict method). None returns a DataFrame. Returns: DataFrame or list of player dictionaries that replicate fitzRoy’s get_afltables_stats function, but with Pythonic conventions (e.g. snake_case keys) Return type: pd.DataFrame or list(dict) Examples
{ "date": "1933-03-18", "season": 1933, "round": 1, "home_team": "Gold Coast", "away_team": "Adelaide", "venue": "Princes Park", "local_start_time": 1437, "attendance": 42853, "hq1g": 3, "hq1b": 3, "hq2g": 2, "hq2b": 1, "hq3g": 1, "hq3b": 5, "hq4g": 3, "hq4b": 4, "home_score": 67, "aq1g": 1, "aq1b": 2, "aq2g": 5, "aq2b": 1, "aq3g": 0, "aq3b": 1, "aq4g": 2, "aq4b": 1, "away_score": 67, "umpire_1": "William Mayo", "umpire_2": "Justin Washington", "umpire_3": "Brian Nicholson", "umpire_4": "Barbara Lamb", "group_id": 353, "first_name": "Elizabeth", "surname": "Lewis", "id": 0, "jumper_no": 18, "playing_for": "Gold Coast", "kicks": 6, "marks": 8, "handballs": 10, "goals": 1, "behinds": 0, "hit_outs": 10, "tackles": 3, "rebounds": 4, "inside_50s": 4, "clearances": 2, "clangers": 0, "frees_for": 3, "frees_against": 4, "brownlow_votes": 1, "contested_possessions": 2, "uncontested_possessions": 6, "contested_marks": 2, "marks_inside_50": 1, "one_percenters": 3, "bounces": 2, "goal_assists": 0, "time_on_ground": 14, "substitute": 1 }
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