使用Numpy向量化替代循环时Pandas代码报错：Draws列全为None

兄弟，你碰到的Draws列全是None的问题，核心原因非常直观——你的soc_iter函数没有返回任何值，Python中没有return语句的函数默认返回None，所以最后执行leaguedf['Draws']=soc_iter(...)时，整列就被赋值成None了。

另外还有个小细节：你调用函数时传入的是.values（比如leaguedf['HomeTeam'].values），这会把Pandas Series转换成numpy数组，丢失了索引信息，后续用loc操作时容易出问题，直接传入Series会更稳妥。

下面给你两种修复方案，按需选择：

方案一：让函数返回处理后的结果（推荐，更规范） #

这种方式不依赖全局变量，函数只负责计算并返回结果，代码更健壮、可复用：

import pandas as pd
data = {'HomeTeam':['Burnley','Crystal Palace','Everton','Hull','Man City','Middlesbrough','Southampton', 'Arsenal','Bournemouth','Chelsea','Man United','Burnley','Leicester','Stoke'], 'AwayTeam':['Swansea','West Brom','Tottenham','Leicester','Sunderland','Stoke','Watford','Liverpool','Man United', 'West Ham','Southampton','Liverpool','Arsenal','Man City'], 'FTR': ['A','A','D','H','H','D','D','A','A','H','H','H','D','A']}
leaguedf = pd.DataFrame(data)

def soc_iter(TEAM, home, away, ftr):
    # 初始化一个全为'No_Game'的Series，保留原索引
    draws = pd.Series(['No_Game'] * len(home), index=home.index)
    # 标记该球队参与的平局场次
    draws.loc[((home == TEAM) & (ftr == 'D')) | ((away == TEAM) & (ftr == 'D'))] = 'Draw'
    # 标记该球队参与的非平局场次
    draws.loc[((home == TEAM) & (ftr != 'D')) | ((away == TEAM) & (ftr != 'D'))] = 'No_Draw'
    # 返回处理好的Series
    return draws

# 调用函数并赋值给Draws列
leaguedf['Draws'] = soc_iter('Arsenal', leaguedf['HomeTeam'], leaguedf['AwayTeam'], leaguedf['FTR'])
leaguedf

方案二：直接让函数修改全局DataFrame（快速修复，不推荐） #

如果只是想快速验证结果，可以让函数直接操作全局的leaguedf，调用后不需要赋值：

import pandas as pd
data = {'HomeTeam':['Burnley','Crystal Palace','Everton','Hull','Man City','Middlesbrough','Southampton', 'Arsenal','Bournemouth','Chelsea','Man United','Burnley','Leicester','Stoke'], 'AwayTeam':['Swansea','West Brom','Tottenham','Leicester','Sunderland','Stoke','Watford','Liverpool','Man United', 'West Ham','Southampton','Liverpool','Arsenal','Man City'], 'FTR': ['A','A','D','H','H','D','D','A','A','H','H','H','D','A']}
leaguedf = pd.DataFrame(data)

def soc_iter(TEAM):
    # 初始化Draws列
    leaguedf['Draws'] = 'No_Game'
    # 标记平局场次
    leaguedf.loc[((leaguedf['HomeTeam'] == TEAM) & (leaguedf['FTR'] == 'D')) | ((leaguedf['AwayTeam'] == TEAM) & (leaguedf['FTR'] == 'D')), 'Draws'] = 'Draw'
    # 标记非平局场次
    leaguedf.loc[((leaguedf['HomeTeam'] == TEAM) & (leaguedf['FTR'] != 'D')) | ((leaguedf['AwayTeam'] == TEAM) & (leaguedf['FTR'] != 'D')), 'Draws'] = 'No_Draw'

# 直接调用函数，无需赋值
soc_iter('Arsenal')
leaguedf

执行任意一种方案后，你就能看到Draws列正确显示为Draw、No_Draw或No_Game了。

内容的提问来源于stack exchange，提问作者jack homareau