pospool

PospoolDefault

pospool(self, *, pool, posfilter, column_mapping, flex_positions=('RB', 'WR', 'TE'), **kwargs)

Creates initial position pool

Parameters:

Name	Type	Description	Default
pool	DataFrame		required
posfilter	Dict[str, int]	filter out low scorers by position	required
column_mapping	Dict[str, str]	column names for player, position, salary, projection	required
flex_positions	Iterable[str]	e.g. (WR, RB, TE)	('RB', 'WR', 'TE')
**kwargs		Keyword arguments for plugins (other than default)	{}

Returns:

Type	Description
Dict[str, pandas.core.frame.DataFrame]	Dict[str, pd.DataFrame] where keys == posfilter.keys

Source code in pangadfs/pospool.py

def pospool(self,
            *,
            pool: pd.DataFrame,
            posfilter: Dict[str, int],
            column_mapping: Dict[str, str],
            flex_positions: Iterable[str] = ('RB', 'WR', 'TE'),
            **kwargs
            ) -> Dict[str, pd.DataFrame]:
    """Creates initial position pool

    Args:
        pool (pd.DataFrame):
        posfilter (Dict[str, int]): filter out low scorers by position
        column_mapping (Dict[str, str]): column names for player, position, salary, projection
        flex_positions (Iterable[str]): e.g. (WR, RB, TE)
        **kwargs: Keyword arguments for plugins (other than default)

    Returns:
        Dict[str, pd.DataFrame] where keys == posfilter.keys

    """
    d = {}
    poscol = column_mapping.get('position', 'pos')
    pointscol = column_mapping.get('points', 'proj')
    salcol = column_mapping.get('salary', 'salary')
    for position, thresh in posfilter.items():
        if position == 'FLEX':
            tmp = pool.loc[(pool[poscol].isin(flex_positions)) & (pool[pointscol] >= thresh), [pointscol, salcol]]      
        else:           
            tmp = pool.loc[(pool[poscol] == position) & (pool[pointscol] >= thresh), [pointscol, salcol]]
        prob_ = (tmp[pointscol] / tmp[salcol]) * 1000
        prob_ = prob_ / prob_.sum()
        d[position] = tmp.assign(prob=prob_)
    return d