如何将这个数组的par1和par2列中的每一项四舍五入到小数点后6位?下面是我尝试到目前为止,但我得到一个奇怪的错误。
(我猜它也不会工作,因为它会四舍五入的第一列?)
a = numpy.array([('54641', 5.2283950300822005e-19, 0.99986935998398196),
('19463068', 1.9641846381816301e-11, 3.9584362981756201e-24),
('19500889', 3.0296847410896202e-11, 1.05569703377661e-11),
('19528632', 3.5188395912917703e-11, 1.4213535554705201e-09)],
dtype=[('pos', 'S100'), ('par1', '<f8'), ('par2', '<f8')])
a = numpy.around(a, decimals=6)
奇怪的错误(知道为什么会这样吗?)
Traceback (most recent call last):
File "msg/combine.py", line 244, in <module>
a = numpy.around(a, decimals=6)
File "/usr/local/msg/lib/python2.6/site-packages/numpy/core/fromnumeric.py", line 2611, in around
return round(decimals, out)
TypeError: return arrays must be of ArrayType
不确定如果没有循环是否可以这样做:
>>> for col in ['par1','par2']:
... a[col] = numpy.around(a[col],2)
...
>>> a
array([('54641', 0.0, 1.0), ('19463068', 0.0, 0.0), ('19500889', 0.0, 0.0),
('19528632', 0.0, 0.0)],
dtype=[('pos', 'S100'), ('par1', '<f8'), ('par2', '<f8')])
当然你可以在结构化数组中使用pandas:
>>> import pandas as pd
>>> data = pd.DataFrame(a)
>>> data[['par1','par2']] = numpy.around(data[['par1','par2']], 2)
>>> data
pos par1 par2
0 54641 0 1
1 19463068 0 0
2 19500889 0 0