Round适用于单个元素但不适用于DataFrame，尝试使用DataFrame.round（）但不起作用......任何想法？感谢。
请输入以下代码：
print "Panda Version: ", pd.__version__
print "['5am'][0]: ", x3['5am'][0]
print "Round element: ", np.round(x3['5am'][0]*4) /4
print "Round Dataframe: \r\n", np.round(x3 * 4, decimals=2) / 4
df = np.round(x3 * 4, decimals=2) / 4
print "Round Dataframe Again: \r\n", df.round(2)
得到了结果：
Panda Version: 0.18.0
['5am'][0]: 0.279914529915
Round element: 0.25
Round Dataframe:
5am 6am 7am 8am 9am 10am 11am
Date
2016-07-11 0.279915 0.279915 2.85256 4.52778 6.23291 9.01496 8.53632
2016-07-12 0.339744 0.369658 2.67308 4.52778 5.00641 7.30983 6.98077
2016-07-13 0.399573 0.459402 2.61325 3.83974 5.48504 6.77137 5.24573
2016-07-14 0.339744 0.549145 2.64316 3.36111 5.66453 5.96368 7.87821
2016-07-15 0.309829 0.459402 2.55342 4.64744 4.46795 6.80128 6.17308
2016-07-16 0.25 0.369658 2.46368 2.67308 4.58761 6.35256 5.63462
2016-07-17 0.279915 0.369658 2.58333 2.91239 4.19872 5.51496 6.65171
Round Dataframe Again:
5am 6am 7am 8am 9am 10am 11am
Date
2016-07-11 0.279915 0.279915 2.85256 4.52778 6.23291 9.01496 8.53632
2016-07-12 0.339744 0.369658 2.67308 4.52778 5.00641 7.30983 6.98077
2016-07-13 0.399573 0.459402 2.61325 3.83974 5.48504 6.77137 5.24573
2016-07-14 0.339744 0.549145 2.64316 3.36111 5.66453 5.96368 7.87821
2016-07-15 0.309829 0.459402 2.55342 4.64744 4.46795 6.80128 6.17308
2016-07-16 0.25 0.369658 2.46368 2.67308 4.58761 6.35256 5.63462
2016-07-17 0.279915 0.369658 2.58333 2.91239 4.19872 5.51496 6.65171
答案 0 :(得分：11)
尝试强制转换为浮点类型：
x3.astype(float).round(2)
答案 1 :(得分：3)
就这么简单
df['col_name'] = df['col_name'].astype(float).round(2)
答案 2 :(得分：1)
您的代码说明：
In [166]: np.round(df * 4, decimals=2)
Out[166]:
a b c d
0 0.11 0.45 1.65 3.38
1 3.97 2.90 1.89 3.42
2 1.46 0.79 3.00 1.44
3 3.48 2.33 0.81 1.02
4 1.03 0.65 1.94 2.92
5 1.88 2.21 0.59 0.39
6 0.08 2.09 4.00 1.02
7 2.86 0.71 3.56 0.57
8 1.23 1.38 3.47 0.03
9 3.09 1.10 1.12 3.31
In [167]: np.round(df * 4, decimals=2) / 4
Out[167]:
a b c d
0 0.0275 0.1125 0.4125 0.8450
1 0.9925 0.7250 0.4725 0.8550
2 0.3650 0.1975 0.7500 0.3600
3 0.8700 0.5825 0.2025 0.2550
4 0.2575 0.1625 0.4850 0.7300
5 0.4700 0.5525 0.1475 0.0975
6 0.0200 0.5225 1.0000 0.2550
7 0.7150 0.1775 0.8900 0.1425
8 0.3075 0.3450 0.8675 0.0075
9 0.7725 0.2750 0.2800 0.8275
In [168]: np.round(np.round(df * 4, decimals=2) / 4, 2)
Out[168]:
a b c d
0 0.03 0.11 0.41 0.84
1 0.99 0.72 0.47 0.86
2 0.36 0.20 0.75 0.36
3 0.87 0.58 0.20 0.26
4 0.26 0.16 0.48 0.73
5 0.47 0.55 0.15 0.10
6 0.02 0.52 1.00 0.26
7 0.72 0.18 0.89 0.14
8 0.31 0.34 0.87 0.01
9 0.77 0.28 0.28 0.83
这对我来说很合适（pandas 0.18.1）
In [162]: df = pd.DataFrame(np.random.rand(10,4), columns=list('abcd'))
In [163]: df
Out[163]:
a b c d
0 0.028700 0.112959 0.412192 0.845663
1 0.991907 0.725550 0.472020 0.856240
2 0.365117 0.197468 0.750554 0.360272
3 0.870041 0.582081 0.203692 0.255915
4 0.257433 0.161543 0.483978 0.730548
5 0.470767 0.553341 0.146612 0.096358
6 0.020052 0.522482 0.999089 0.254312
7 0.714934 0.178061 0.889703 0.143701
8 0.308284 0.344552 0.868151 0.007825
9 0.771984 0.274245 0.280431 0.827999
In [164]: df.round(2)
Out[164]:
a b c d
0 0.03 0.11 0.41 0.85
1 0.99 0.73 0.47 0.86
2 0.37 0.20 0.75 0.36
3 0.87 0.58 0.20 0.26
4 0.26 0.16 0.48 0.73
5 0.47 0.55 0.15 0.10
6 0.02 0.52 1.00 0.25
7 0.71 0.18 0.89 0.14
8 0.31 0.34 0.87 0.01
9 0.77 0.27 0.28 0.83
答案 3 :(得分：0)
我试图重现你的情况。它看起来效果很好。
import pandas as pd
import numpy as np
from io import StringIO
s = """Date 5am 6am 7am 8am 9am 10am 11am
2016-07-11 0.279915 0.279915 2.85256 4.52778 6.23291 9.01496 8.53632
2016-07-12 0.339744 0.369658 2.67308 4.52778 5.00641 7.30983 6.98077
2016-07-13 0.399573 0.459402 2.61325 3.83974 5.48504 6.77137 5.24573
2016-07-14 0.339744 0.549145 2.64316 3.36111 5.66453 5.96368 7.87821
2016-07-15 0.309829 0.459402 2.55342 4.64744 4.46795 6.80128 6.17308
2016-07-16 0.25 0.369658 2.46368 2.67308 4.58761 6.35256 5.63462
2016-07-17 0.279915 0.369658 2.58333 2.91239 4.19872 5.51496 6.65171
"""
df = pd.read_table(StringIO(s), delim_whitespace=True)
df.set_index('Date').round(2)