如何将日期时间格式转换为分钟 - pandas
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How to convert a datetime format to minutes - pandas
提问by Jithesh Erancheri
I have a data frame which has a column usage_duration (which is the difference of two another columns in datetime format). It looks like below:
我有一个数据框，它有一列usage_duration（这是日期时间格式的另外两列的差异）。它看起来像下面：
processid, userid, usage_duration
17613,root,0 days 23:41:03.000000000
17641,root,2 days 04:05:26.000000000
13848,acs,0 days 00:00:50.000000000
3912,acs,0 days 06:07:38.000000000
6156,acs,0 days 17:22:43.000000000
Now I wanted to convert the same into minutes. It should look like as below:
现在我想将其转换为分钟。它应该如下所示：
processid, userid, usage_duration_min
17613,root,1421
17641,root,3125
13848,acs,0
3912,acs,367
6156,acs,1042
Can someone let me know how is it possible?
有人可以让我知道怎么可能吗？
Highly appreciate your support
非常感谢您的支持
回答by jezrael
Use total_secondsor secondsand divide by 60, last cast to integers:
使用total_secondsorseconds和除以60，最后转换为integers：
#if necessary converting to timedelta
#df['usage_duration'] = pd.to_timedelta(df['usage_duration'])
df['new'] = df['usage_duration'].dt.total_seconds().div(60).astype(int)
Or:
或者：
df['new'] = (df['usage_duration'].dt.seconds.div(60).astype(int)
+ df['usage_duration'].dt.days.multiply(1440).astype(int) )
print (df)
processid userid usage_duration new
0 17613 root 0 days 23:41:03 1421
1 17641 root 2 days 04:05:26 3125
2 13848 acs 0 days 00:00:50 0
3 3912 acs 0 days 06:07:38 367
4 6156 acs 0 days 17:22:43 1042
回答by jpp
This is one way:
这是一种方式：
s = pd.Series(['0 days 23:41:03.000000000', '2 days 04:05:26.000000000',
'0 days 00:00:50.000000000', '0 days 06:07:38.000000000',
'0 days 17:22:43.000000000'])
s = pd.to_timedelta(s).astype('timedelta64[m]').astype(int)
print(s)
0 1421
1 3125
2 0
3 367
4 1042
dtype: int32
