我有2018年和2017年的数据，使用24:00小时：
Hour Ending X Y Z
12/31/2017 24:00 11452.16 1834.87 2856.94
12/31/2017 23:00 11579.85 1855.94 2898.57
12/31/2017 22:00 11754.25 1890.36 2942.23
12/31/2017 21:00 11883.11 1907.59 2970.85
12/31/2017 20:00 12015.66 1910.72 2989.82
12/31/2017 19:00 12061.55 1923.56 3002.77
12/31/2017 18:00 11663.43 1891.09 2915.28
12/31/2017 17:00 11008.23 1803.92 2871.94
12/31/2017 16:00 10904.93 1730.49 2864.33
12/31/2017 15:00 11014.92 1673.37 2862.77
12/31/2017 14:00 11099.28 1604.28 2853.98
12/31/2017 13:00 11088.55 1585.55 2841.05
12/31/2017 12:00 10989.86 1578.52 2822.75
12/31/2017 11:00 10849.49 1578.38 2802.3
12/31/2017 10:00 10600.86 1581.44 2774.18
12/31/2017 09:00 10184.76 1532.89 2715.56
12/31/2017 08:00 9826.52 1461.63 2672.01
12/31/2017 07:00 9556.41 1399.1 2611.86
12/31/2017 06:00 9260.16 1341.11 2578.8
12/31/2017 05:00 9113.75 1328.5 2581.56
12/31/2017 04:00 9025.76 1346.87 2582.43
12/31/2017 03:00 9044.65 1343.63 2584.13
12/31/2017 02:00 9194.51 1358.57 2600.79
12/31/2017 01:00 9444.48 1379.35 2621.97
12/30/2017 24:00 9794.9 1426.91 2679.92
而2016-2013年的其余数据是在23:00时间，如下所示：
Hour Ending X Y Z
01/04/2013 0:00 9166.3577 1377.48441 1646.06411
01/03/2013 23:00 9700.616845999999 1454.42221 1684.4460960000001
01/03/2013 22:00 10236.5831 1518.723561 1747.198325
01/03/2013 21:00 10622.79608 1550.834297 1787.9794949999998
01/03/2013 20:00 10845.332390000001 1562.49244 1793.3864859999999
01/03/2013 19:00 10948.436590000001 1578.140944 1797.555973
01/03/2013 18:00 10601.329259999999 1515.094035 1752.964543
01/03/2013 17:00 10043.38204 1434.163607 1725.7288989999997
01/03/2013 16:00 9927.267078 1394.351864 1708.8579579999998
01/03/2013 15:00 9882.591065999999 1365.690266 1711.5373809999999
01/03/2013 14:00 10047.71838 1406.555055 1723.633549
01/03/2013 13:00 10290.2543 1445.03692 1717.541841
01/03/2013 12:00 10585.86702 1519.160058 1739.736317
01/03/2013 11:00 10895.58775 1617.807443 1742.36163
01/03/2013 10:00 10918.89208 1686.252509 1730.4538109999999
01/03/2013 9:00 10929.63421 1747.157416 1769.523491
01/03/2013 8:00 10944.18396 1749.1523829999999 1722.127739
01/03/2013 7:00 10624.5241 1690.290167 1680.816472
01/03/2013 6:00 9924.627883 1570.496102 1621.679814
01/03/2013 5:00 9370.169947 1475.116882 1580.4176400000001
01/03/2013 4:00 9170.732963 1424.242721 1576.282469
01/03/2013 3:00 9142.024671 1401.497276 1564.750211
01/03/2013 2:00 9240.30997 1438.449286 1565.629803
01/03/2013 1:00 9455.203629000001 1445.505592 1580.642498
01/03/2013 0:00 9822.1846 1428.1571800000002 1582.02934
我只想将2018-2017数据从24:00小时转换为23:00小时，但还要保持与时间相关联的X，Y和Z值不变，这意味着我需要更改（例如）：
Hour Ending X Y Z
12/31/2017 24:00 11452.16 1834.87 2856.94
到
Hour Ending X Y Z
01/01/2018 00:00 11452.16 1834.87 2856.94
我知道这是一个非常简单的修复程序，但是仅尝试pd.to_datetime访问该列显然需要23:00小时格式。
有没有简单的方法可以更改这些日期？
答案 0 :(得分：3)
您可以使用pd.to_timedelta帮助：
s = df['Hour Ending'].str.split()
df['Hour Ending'] = pd.to_datetime(s.str[0]) + pd.to_timedelta(s.str[1].str.split(':').str[0] +' hours')
print(df)
输出：
Hour Ending X Y Z
0 2018-01-01 00:00:00 11452.16 1834.87 2856.94
1 2017-12-31 23:00:00 11579.85 1855.94 2898.57
2 2017-12-31 22:00:00 11754.25 1890.36 2942.23
3 2017-12-31 21:00:00 11883.11 1907.59 2970.85
4 2017-12-31 20:00:00 12015.66 1910.72 2989.82
5 2017-12-31 19:00:00 12061.55 1923.56 3002.77
6 2017-12-31 18:00:00 11663.43 1891.09 2915.28
7 2017-12-31 17:00:00 11008.23 1803.92 2871.94
8 2017-12-31 16:00:00 10904.93 1730.49 2864.33
9 2017-12-31 15:00:00 11014.92 1673.37 2862.77
10 2017-12-31 14:00:00 11099.28 1604.28 2853.98
11 2017-12-31 13:00:00 11088.55 1585.55 2841.05
12 2017-12-31 12:00:00 10989.86 1578.52 2822.75
13 2017-12-31 11:00:00 10849.49 1578.38 2802.30
14 2017-12-31 10:00:00 10600.86 1581.44 2774.18
15 2017-12-31 09:00:00 10184.76 1532.89 2715.56
16 2017-12-31 08:00:00 9826.52 1461.63 2672.01
17 2017-12-31 07:00:00 9556.41 1399.10 2611.86
18 2017-12-31 06:00:00 9260.16 1341.11 2578.80
19 2017-12-31 05:00:00 9113.75 1328.50 2581.56
20 2017-12-31 04:00:00 9025.76 1346.87 2582.43
21 2017-12-31 03:00:00 9044.65 1343.63 2584.13
22 2017-12-31 02:00:00 9194.51 1358.57 2600.79
23 2017-12-31 01:00:00 9444.48 1379.35 2621.97
24 2017-12-31 00:00:00 9794.90 1426.91 2679.92
答案 1 :(得分：0)
我不知道您的数据的结构，只是对其进行遍历并拼接字符串（如果是字符串）以查看“ 24”是否出现在倒数第5位至第3位。然后使用datetime模块在日期中添加一个。
import datetime
lines = ['12/31/2017 24:00', '12/31/2017 23:00', '12/30/2017 24:00']
for line in lines:
print('PREVIOUS : ' + line)
# Convert a 24 hour to 0 hour
if line[-5:-3] == '24':
(date, time) = line.split()
time = time[:-5] + '0' + time[-3:]
date = datetime.datetime.strptime(date, '%m/%d/%Y') + datetime.timedelta(days=1)
print('CHANGED : ' + date.strftime('%m/%d/%Y') + ' ' + time)
else:
print('UNCHANGED: ' + line)
输出：
PREVIOUS : 12/31/2017 24:00
AFTER : 01/01/2018 0:00
PREVIOUS : 12/31/2017 23:00
UNCHANGED: 12/31/2017 23:00
PREVIOUS : 12/30/2017 24:00
AFTER : 12/31/2017 0:00