从每个us检索以前的结果/行

2024-09-27 00:13:12 发布

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我对熊猫不熟悉

我有一个数据帧,它看起来像这样(只是大得多):

    Horses        RaceDate Position
1   RedHorse      1/2/00   2
2   BlueHorse     1/2/00   6
3   YellowHorse   1/2/00   7
4   RedHorse      15/1/00  3

我想为以前的结果添加列。所以我的数据框可能会变成:

    Horses        RaceDate Position   PrevPosition
1   RedHorse      1/2/00   2          3
2   BlueHorse     1/2/00   6          -
3   YellowHorse   1/2/00   7          -
4   RedHorse      15/1/00  3          -

我试过以下方法:

def prevRuns(horseName, raceDate):
    horseDf = df.loc[df['Horse'] == horseName]
    currentRace = horseDf.index[horseDf['RaceDate'] == raceDate]

    if len(horseDf.index) >= currentRace:
        return horseDf.at[currentRace+1,'Position']
    else:
        return 0


df['prevRun'] = df['Horse'].apply(prevRuns, raceDate = df['RaceDate'])

但它不起作用

ValueError: Can only compare identically-labeled Series objects

为什么不起作用

有没有更优雅的方法来实现我的目标


Tags: 数据方法dfpositionhorsehorsesracedatebluehorse
1条回答
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1楼 · 发布于 2024-09-27 00:13:12

您可以使用groupby+shift

# convert dates to datetime and sort descending
df['RaceDate'] = pd.to_datetime(df['RaceDate'], dayfirst=True)
df = df.sort_values('RaceDate', ascending=False)

# groupby and shift for previous position
df['PrevPosition'] = df.groupby('Horses')['Position'].shift(-1)

print(df)

        Horses   RaceDate  Position  PrevPosition
1     RedHorse 2000-02-01         2           3.0
2    BlueHorse 2000-02-01         6           NaN
3  YellowHorse 2000-02-01         7           NaN
4     RedHorse 2000-01-15         3           NaN

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