我有一个输入和日期,时间的数据集。我只想将输入栏中包含的特定值的时间转换为00:00:00,其他时间将按原样显示。
我尝试了一个代码,它为我提供了00:00:00的特定值,但其他时间显示为NaT。
谁能帮助我解决错误?
我的代码:
df['time_diff']= pd.to_datetime(df['date'] + " " + df['time'],
format='%d/%m/%Y %H:%M:%S', dayfirst=True)
mask = df['x3'].eq(5)
df['Duration'] = np.where(df['x3']== 5, df['time_diff'], np.datetime64('NaT') )
df['Duration'] = df['time_diff'].sub(df['Duration']).dt.total_seconds().div(3600)
然后它给了我这个输出:
date time x3 duration
10/3/2018 6:15:00 0 NaN
10/3/2018 6:45:00 5 00:00:00
10/3/2018 7:45:00 0 NaN
10/3/2018 9:00:00 0 NaN
10/3/2018 9:25:00 0 NaN
10/3/2018 9:30:00 0 NaN
10/3/2018 11:00:00 0 NaN
10/3/2018 11:30:00 0 NaN
10/3/2018 13:30:00 0 NaN
10/3/2018 13:50:00 5 00:00:00
10/3/2018 15:00:00 0 NaN
10/3/2018 15:25:00 0 NaN
10/3/2018 16:25:00 0 NaN
10/3/2018 18:00:00 0 NaN
10/3/2018 19:00:00 0 NaN
10/3/2018 19:30:00 0 NaN
10/3/2018 20:00:00 0 NaN
10/3/2018 22:05:00 0 NaN
10/3/2018 22:15:00 5 00:00:00
10/3/2018 23:40:00 0 NaN
10/4/2018 6:58:00 5 00:00:00
10/4/2018 13:00:00 0 NaN
10/4/2018 16:00:00 0 NaN
10/4/2018 17:00:00 0 NaN
但是我期望的输出是:
date time x3 duration expected output is
10/3/2018 6:15:00 0 NaN 6:15:00
10/3/2018 6:45:00 5 00:00:00 00:00:00
10/3/2018 7:45:00 0 NaN 7:45:00
10/3/2018 9:00:00 0 NaN 9:00:00
10/3/2018 9:25:00 0 NaN 9:25:00
10/3/2018 9:30:00 0 NaN 9:30:00
10/3/2018 11:00:00 0 NaN 11:00:00
10/3/2018 11:30:00 0 NaN 11:30:00
10/3/2018 13:30:00 0 NaN 13:30:00
10/3/2018 13:50:00 5 00:00:00 00:00:00
10/3/2018 15:00:00 0 NaN 15:00:00
10/3/2018 15:25:00 0 NaN 15:25:00
10/3/2018 16:25:00 0 NaN 16:25:00
10/3/2018 18:00:00 0 NaN 18:00:00
10/3/2018 19:00:00 0 NaN 19:00:00
10/3/2018 19:30:00 0 NaN 19:30:00
10/3/2018 20:00:00 0 NaN 20:00:00
10/3/2018 22:05:00 0 NaN 22:05:00
10/3/2018 22:15:00 5 00:00:00 00:00:00
10/3/2018 23:40:00 0 NaN 23:40:00
10/4/2018 6:58:00 5 00:00:00 00:00:00
10/4/2018 13:00:00 0 NaN 13:00:00
10/4/2018 16:00:00 0 NaN 16:00:00
10/4/2018 17:00:00 0 NaN 17:00:00
numpy.where
与按条件创建新列一起使用-0 timedelta
和将列time
转换为timedeltas:
df['Duration'] = np.where(df['x3'].eq(5), np.timedelta64(0), pd.to_timedelta(df['time']))
print (df)
date time x3 Duration
0 10/3/2018 6:15:00 0 06:15:00
1 10/3/2018 6:45:00 5 00:00:00
2 10/3/2018 7:45:00 0 07:45:00
3 10/3/2018 9:00:00 0 09:00:00
4 10/3/2018 9:25:00 0 09:25:00
5 10/3/2018 9:30:00 0 09:30:00
6 10/3/2018 11:00:00 0 11:00:00
7 10/3/2018 11:30:00 0 11:30:00
8 10/3/2018 13:30:00 0 13:30:00
9 10/3/2018 13:50:00 5 00:00:00
10 10/3/2018 15:00:00 0 15:00:00
11 10/3/2018 15:25:00 0 15:25:00
12 10/3/2018 16:25:00 0 16:25:00
13 10/3/2018 18:00:00 0 18:00:00
14 10/3/2018 19:00:00 0 19:00:00
15 10/3/2018 19:30:00 0 19:30:00
16 10/3/2018 20:00:00 0 20:00:00
17 10/3/2018 22:05:00 0 22:05:00
18 10/3/2018 22:15:00 5 00:00:00
19 10/3/2018 23:40:00 0 23:40:00
20 10/4/2018 6:58:00 5 00:00:00
21 10/4/2018 13:00:00 0 13:00:00
22 10/4/2018 16:00:00 0 16:00:00
23 10/4/2018 17:00:00 0 17:00:00
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