jezrael
2020-01-31 16:44
我认为唯一值不是必需的，您可以将dt.strftime2列用于replace带有NaT值的2列：
Sunday_Starting_Point = pd.to_datetime('Sunday 2015')
x = pd.to_numeric(df.Value, errors='coerce')
s = Sunday_Starting_Point + pd.to_timedelta(x, unit='h')
df['Day'] = s.dt.strftime('%A').replace('NaT','No Day')
df['Hour'] = s.dt.strftime('%I:%M%p').replace('NaT','No Time')
print (df)
Value Day Hour
0 0.0 Sunday 12:00AM
1 4.0 Sunday 04:00AM
2 10.0 Sunday 10:00AM
3 24.0 Monday 12:00AM
4 NaN No Day No Time
5 49.0 Tuesday 01:00AM
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谢谢，当我尝试收到ValueError的值错误：w / oa number @jezrael的单位缩写
@ Chris90 -这似乎有些非数值，您可以检查是否工作
s = Sunday_Starting_Point + pd.to_timedelta(df.Value, unit='h', errors='coerce')，而不是s = Sunday_Starting_Point + pd.to_timedelta(df.Value, unit='h')谢谢，它运行了，但是每一行它给Day和Day的值分别为Sunday和12:00 AM
@ Chris90-似乎非数字值，如何工作
x = pd.to_numeric(df.Value, errors='coerce') s = Sunday_Starting_Point + pd.to_timedelta(x, unit='h')？是的，这似乎在填充并检查我得到了什么，感谢您的验证！