本文介绍了在 Pandas 中将字符串转换为 timedelta的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个系列,其中时间戳的格式为 HHHHH:MM
:
I have a series where the timestamp is in the format HHHHH:MM
:
timestamp = pd.Series(['34:23', '125:26', '15234:52'], index=index)
我想将其转换为 timedelta 系列.
I would like to convert it to a timedelta series.
现在我设法在单个字符串上做到这一点:
For now I manage to do that on a single string:
str[:-3]
str[-2:]
timedelta(hours=int(str[:-3]),minutes=int(str[-2:]))
如果可能,我想以更简洁的方式将其应用于整个系列.有没有办法做到这一点?
I would like to apply it to the whole series, if possible in a cleaner way. Is there a way to do this?
推荐答案
你可以使用 column-wise Pandas 方法:
You can use column-wise Pandas methods:
s = pd.Series(['34:23','125:26','15234:52'])
v = s.str.split(':', expand=True).astype(int)
s = pd.to_timedelta(v[0], unit='h') + pd.to_timedelta(v[1], unit='m')
print(s)
0 1 days 10:23:00
1 5 days 05:26:00
2 634 days 18:52:00
dtype: timedelta64[ns]
正如评论中所指出的,这也可以在一行中实现,尽管不太清楚:
As pointed out in comments, this can also be achieved in one line, albeit less clear:
s = pd.to_timedelta((s.str.split(':', expand=True).astype(int) * (60, 1)).sum(axis=1), unit='min')
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