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leaguedata.data

get_dataset(select_columns=None)

Load the dataset from the Hugging Face Hub and return it as a Polars DataFrame.

PARAMETER DESCRIPTION
select_columns

The columns to select from the dataset. If None, all columns are selected.

TYPE: list DEFAULT: None

RETURNS DESCRIPTION
DataFrame

pl.DataFrame: The dataset as a Polars DataFrame.
Source code in leaguedata/data.py 
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def get_dataset(select_columns=None) -> pl.DataFrame:
    """
    Load the dataset from the Hugging Face Hub and return it as a Polars DataFrame.

    Parameters:
        select_columns (list): The columns to select from the dataset. If None, all columns are selected.

    Returns:
        pl.DataFrame: The dataset as a Polars DataFrame.
    """

    dataset = load_dataset("renecotyfanboy/leagueData", split="train")

    if select_columns is None:
        return dataset.to_polars()

    return dataset.select_columns(select_columns).to_polars()

get_history_dict()

Return a two level dictionary containing the history of all players in the reference sample. Accessed by elo and then by puuid.

Source code in leaguedata/data.py 
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def get_history_dict():
    """
    Return a two level dictionary containing the history of all players in the reference sample.
    Accessed by elo and then by puuid.
    """

    columns = ['elo', 'puuid', 'gameStartTimestamp', 'is_in_reference_sample', 'win']
    df = get_dataset(columns)
    unique_elo = df.filter(is_in_reference_sample=True)['elo'].unique()

    history = {}

    for elo in unique_elo:
        loc_df = df.filter(elo=elo, is_in_reference_sample=True)
        history[elo] = {}
        unique_puuid = loc_df['puuid'].unique()

        for puuid in unique_puuid:
            loc_history = loc_df.filter(puuid=puuid)
            history[elo][puuid] = np.asarray(loc_history.sort(by='gameStartTimestamp')['win'])

    return history

get_tier_batch()

Return batches of tiers in League of Legends, sorted from the lowest to the highest.

Source code in leaguedata/data.py 
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def get_tier_batch() -> list:
    """
    Return batches of tiers in League of Legends, sorted from the lowest to the highest.
    """

    tier_list = ['IRON', 'BRONZE', 'SILVER', 'GOLD', 'PLATINUM', 'EMERALD', 'DIAMOND', 'MASTER', 'GRANDMASTER',
                 'CHALLENGER']
    division_list = ['I', 'II', 'III', 'IV'][::-1]


    for tier in tier_list:

        tier_with_sub = []

        if tier not in ['MASTER', 'GRANDMASTER', 'CHALLENGER']:
            for division in division_list:
                tier_with_sub.append(f'{tier}_{division}')

            yield tier_with_sub

        else:
            yield [tier]

get_tier_sorted()

Return a list of all the tiers in League of Legends, sorted from the lowest to the highest.

RETURNS DESCRIPTION
list

The list of all tiers in League of Legends, sorted from the lowest to the highest.

TYPE: list

Source code in leaguedata/data.py 
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def get_tier_sorted() -> list:
    """
    Return a list of all the tiers in League of Legends, sorted from the lowest to the highest.

    Returns:
        list: The list of all tiers in League of Legends, sorted from the lowest to the highest.
    """

    tier_list = ['IRON', 'BRONZE', 'SILVER', 'GOLD', 'PLATINUM', 'EMERALD', 'DIAMOND', 'MASTER', 'GRANDMASTER',
                 'CHALLENGER']
    division_list = ['I', 'II', 'III', 'IV'][::-1]
    tier_with_sub = []

    for tier in tier_list:

        if tier not in ['MASTER', 'GRANDMASTER', 'CHALLENGER']:
            for division in division_list:
                tier_with_sub.append(f'{tier}_{division}')

    return tier_with_sub + ['MASTER', 'GRANDMASTER', 'CHALLENGER']