Woj*_*ski 0 python datetime dataframe pandas
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, 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, 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,...we had our bikes and I took a different route home",1/17/2004,28.9783333,-96.6458333
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完整的 csv 文件在这里。
我将其加载到数据框中。在列名中'datetime',我有格式'object'。我试图将类型转换'object'为这样的类型'datetime':
df['datetime'] = pd.to_datetime(df.datetime)
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结果我收到了这个错误:
ValueError: hour must be in 0..23
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任何帮助将不胜感激!
很显然的问题是24:00,解决办法是Series.str.split,date人民共同转换to_datetime,并time通过to_timedelta与加在一起:
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
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