我想根据特定条件从数据集中的值创建一个列表

Question

我正在使用一个数据集，其中包含了1985年以来每场三月疯狂比赛的信息。我想知道哪些球队赢得了所有比赛，以及每场赢了多少次

我屏蔽了主数据集并创建了一个只包含冠军赛信息的新数据集。现在我正在尝试创建一个循环，比较两支参加冠军赛的球队的得分，检测胜利者并将该球队添加到列表中。数据集是这样的：https://imgur.com/tXhPYSm

tourney = pd.read_csv('ncaa.csv')

champions = tourney.loc[tourney['Region Name'] == "Championship", ['Year','Seed','Score','Team','Team.1','Score.1','Seed.1']]

list_champs = []

for i in champions:
    if champions['Score'] > champions['Score.1']:
        list_champs.append(i['Team'])
    else:
        list_champs.append(i['Team.1'])

Answer 1

为什么需要循环遍历DataFrame

基本过滤应该很好。像这样：

champs1 = champions.loc[champions['Score'] > champions['Score.1'], 'Team']
champs2 = champions.loc[champions['Score'] < champions['Score.1'], 'Team.1']

list_champs = list(champs1) + list(champs2)

Answer 2

使代码正常工作的最简单的更改（不是最有效的）：

tourney = pd.read_csv('ncaa.csv')

champions = tourney.loc[tourney['Region Name'] == "Championship", ['Year','Seed','Score','Team','Team.1','Score.1','Seed.1']]

list_champs = []

for row in champions.iterrows():
    if row['Score'] > row['Score.1']:
        list_champs.append(row['Team'])
    else:
        list_champs.append(row['Team.1'])

否则，您可以简单地执行以下操作：

df.apply(lambda row: row['Team'] if row['Score'] > row['Score.1'] else row['Team.1'], axis=1).values