def get_max_median_position_concentration(positions):
    """
    Finds the max and median long and short position concentrations
    in each time period specified by the index of positions.

    Parameters
    ----------
    positions : pd.DataFrame
        The positions that the strategy takes over time.

    Returns
    -------
    pd.DataFrame
        Columns are max long, max short, median long, and median short
        position concentrations. Rows are timeperiods.
    """

    expos = get_percent_alloc(positions)
    expos = expos.drop('cash', axis=1)

    longs = expos.where(expos.applymap(lambda x: x > 0))
    shorts = expos.where(expos.applymap(lambda x: x < 0))

    alloc_summary = pd.DataFrame()
    alloc_summary['max_long'] = longs.max(axis=1)
    alloc_summary['median_long'] = longs.median(axis=1)
    alloc_summary['median_short'] = shorts.median(axis=1)
    alloc_summary['max_short'] = shorts.min(axis=1)

    return alloc_summary
def get_max_median_position_concentration(positions):
    """
    Finds the max and median long and short position concentrations
    in each time period specified by the index of positions.

    Parameters
    ----------
    positions : pd.DataFrame
        The positions that the strategy takes over time.

    Returns
    -------
    pd.DataFrame
        Columns are max long, max short, median long, and median short
        position concentrations. Rows are timeperiods.
    """

    expos = get_percent_alloc(positions)
    expos = expos.drop('cash', axis=1)

    longs = expos.where(expos.applymap(lambda x: x > 0))
    shorts = expos.where(expos.applymap(lambda x: x < 0))

    alloc_summary = pd.DataFrame()
    alloc_summary['max_long'] = longs.max(axis=1)
    alloc_summary['median_long'] = longs.median(axis=1)
    alloc_summary['median_short'] = shorts.median(axis=1)
    alloc_summary['max_short'] = shorts.min(axis=1)

    return alloc_summary
def get_max_median_position_concentration ( positions ) : expos = get_percent_alloc ( positions ) expos = expos . drop ( 'cash' , axis = 1 ) longs = expos . where ( expos . applymap ( lambda x : x > 0 ) ) shorts = expos . where ( expos . applymap ( lambda x : x < 0 ) ) alloc_summary = pd . DataFrame ( ) alloc_summary [ 'max_long' ] = longs . max ( axis = 1 ) alloc_summary [ 'median_long' ] = longs . median ( axis = 1 ) alloc_summary [ 'median_short' ] = shorts . median ( axis = 1 ) alloc_summary [ 'max_short' ] = shorts . min ( axis = 1 ) return alloc_summary
Finds the max and median long and short position concentrations
    in each time period specified by the index of positions.

    Parameters
    ----------
    positions : pd.DataFrame
        The positions that the strategy takes over time.

    Returns
    -------
    pd.DataFrame
        Columns are max long, max short, median long, and median short
        position concentrations. Rows are timeperiods.
Finds the max and median long and short position concentrations in each time period specified by the index of positions .