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python - 转换为 'datetime' 类型 : "hour must be in 0..23" 时出现问题

转载 作者:行者123 更新时间:2023-12-02 16:58:49 25 4
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这些是我的 csv 文件中的一些示例行:

10/10/1949 20:30,san marcos,tx,us,cylinder,2700,45 minutes,"This event took place in early fall around 1949-50. It occurred after a Boy Scout meeting in the Baptist Church. The Baptist Church sit",4/27/2004,29.8830556,-97.9411111
10/10/1949 21:00,lackland afb,tx,,light,7200,1-2 hrs,"1949 Lackland AFB&#44 TX. Lights racing across the sky & making 90 degree turns on a dime.",12/16/2005,29.38421,-98.581082
10/10/1955 17:00,chester (uk/england),,gb,circle,20,20 seconds,"Green/Orange circular disc over Chester&#44 England",1/21/2008,53.2,-2.916667
10/10/1956 21:00,edna,tx,us,circle,20,1/2 hour,"My older brother and twin sister were leaving the only Edna theater at about 9 PM&#44...we had our bikes and I took a different route home",1/17/2004,28.9783333,-96.6458333

完整的 csv 文件是 here .

我将其加载到数据框中。在列名称 'datetime' 中,我有格式 'object'。我尝试将 'object' 类型转换为 'datetime' 类型,如下所示:

df['datetime'] = pd.to_datetime(df.datetime)

结果我得到这个错误:

ValueError: hour must be in 0..23

我们将不胜感激!

最佳答案

显然问题是 24:00,解决方案是 Series.str.split , dateto_datetime 转换和 time by to_timedelta并加在一起:

print (df)
datetime
0 10/10/1949 20:30
1 10/10/1949 21:00
2 10/10/1955 17:00
3 10/10/1956 24:00

df[['date','time']] = df['datetime'].str.split(expand=True)
df['datetime'] = (pd.to_datetime(df.pop('date'), format='%d/%m/%Y') +
pd.to_timedelta(df.pop('time') + ':00'))
print (df)
datetime
0 1949-10-10 20:30:00
1 1949-10-10 21:00:00
2 1955-10-10 17:00:00
3 1956-10-11 00:00:00

关于python - 转换为 'datetime' 类型 : "hour must be in 0..23" 时出现问题,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/55135059/

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