我怎样才能把这段代码变成更惯用的熊猫？

Question

有点宽泛的问题，但我不确定如何获得有关如何改进此代码的指针。

我有一个包含投注赔率和比赛结果的数据框，我想计算投资于某支球队的回报。

我现在拥有的代码可以运行，但我觉得它只是依靠apply 方法并进入 Python 来完成 Pandas 可以做的大部分事情。

数据框如下所示：

这是我的代码：

def compute_payout(odds, amount=1):
    if odds < 0:
        return amount/(-1.0 * odds/100.0)
    elif odds > 0:
        return amount/(100.0/odds)

def game_payout(row, team_name):
    if row['home_team'] == team_name:
        if row['home_score'] > row['away_score']:
            return compute_payout(row['home_odds'])
        else:
            return -1
    elif row['away_team'] == team_name:
        if row['away_score'] > row['home_score']:
            return compute_payout(row['away_odds'])
        else:
            return -1

payout = df.apply(lambda row: game_payout(row, team_name), axis=1)

非常感谢任何建议！

Answer 1

将numpy.select 与& 链接的条件用于bitwise AND 和~ 用于反转布尔掩码：

m11 = df['home_team'] == team_name
m21 = df['away_team'] == team_name

m12 = df['home_score'] > df['away_score']
m22 = df['home_score'] < df['away_score']

vals = [df['home_odds'].apply(compute_payout), -1, df['away_odds'].apply(compute_payout), -1]
payout = np.select([m11 & m12, m11 & ~m12, m21 & m22, m21 & ~m22], vals, default=np.nan)