pandas 如何对数据框中的时间求和
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How to sum time in a dataframe
提问by LMLPP
I have a dataframe of time data in the format
我有一个格式为时间数据的数据框
hh:mm:ss
hh:mm:ss
(type string)
（输入字符串）
I need to be able to sum the values (to acquire total time) in a few of the columns. I'm wondering if anyone has any recommendations on the best way to do this and get the sum in the same format.
我需要能够对几列中的值求和（以获取总时间）。我想知道是否有人对执行此操作并以相同格式获得总和的最佳方法有任何建议。
回答by Jeff
You can do this using timedelta:
您可以使用 timedelta 执行此操作：
import pandas as pd
import datetime
data = {'t1':['01:15:31',
'00:47:15'],
't2':['01:13:02',
'00:51:33']
}
def make_delta(entry):
h, m, s = entry.split(':')
return datetime.timedelta(hours=int(h), minutes=int(m), seconds=int(s))
df = pd.DataFrame(data)
df = df.applymap(lambda entry: make_delta(entry))
df['elapsed'] = df['t1'] + df['t2']
In [23]: df
Out[23]:
t1 t2 elapsed
0 01:15:31 01:13:02 02:28:33
1 00:47:15 00:51:33 01:38:48
Edit: I see you need to do this by column, not row. In that case do the same thing, but:
编辑：我看到您需要按列执行此操作，而不是按行执行此操作。在这种情况下，做同样的事情，但是：
In [24]: df['t1'].sum()
Out[24]: Timedelta('0 days 02:02:46')
回答by jezrael
You can use to_timedeltawith sum:
你可以用to_timedelta与sum：
import pandas as pd
df = pd.DataFrame({'A': ['18:22:28', '12:15:10']})
df['A'] = pd.to_timedelta(df.A)
print (df)
A
0 18:22:28
1 12:15:10
print (df.dtypes)
A timedelta64[ns]
dtype: object
print (df.A.sum())
1 days 06:37:38
回答by Alyssa Haroldsen
Maybe try using datetime.timedelta?
也许尝试使用datetime.timedelta？
import re
from datetime import timedelta
_TIME_RE = re.compile(r'(\d+):(\d+):(\d+)')
def parse_timedelta(line):
# Invalid lines (such as blank) will be considered 0 seconds
m = _TIME_RE.match(line)
if m is None:
return timedelta()
hours, minutes, seconds = [int(i) for i in m.groups()]
return timedelta(hours=hours, minutes=minutes, seconds=seconds)
def format_timedelta(delta):
hours, rem = divmod(delta.seconds + delta.days * 86400, 3600)
minutes, seconds = divmod(rem, 60)
return '{:02}:{:02}:{:02}'.format(hours, minutes, seconds)
If datais a list containing the lines:
如果data是包含以下行的列表：
print(format_timedelta(sum(parse_timedelta(line) for line in data)))
