Unutbu给出了一个非常完整的答案(他们也从我这里得到了+1)，但这里有一个低科技的替代方案:

>>> x=np.random.randn(5)
>>> x
array([ 0.25276524,  2.28334499, -1.88221637,  0.69949927,  1.0285625 ])
>>> ['{:.2f}'.format(i) for i in x]
['0.25', '2.28', '-1.88', '0.70', '1.03']

作为函数(使用format()语法进行格式化):

def ndprint(a, format_string ='{0:.2f}'):
    print [format_string.format(v,i) for i,v in enumerate(a)]

用法:

>>> ndprint(x)
['0.25', '2.28', '-1.88', '0.70', '1.03']

>>> ndprint(x, '{:10.4e}')
['2.5277e-01', '2.2833e+00', '-1.8822e+00', '6.9950e-01', '1.0286e+00']

>>> ndprint(x, '{:.8g}')
['0.25276524', '2.283345', '-1.8822164', '0.69949927', '1.0285625']

数组的索引可以在格式字符串中访问:

>>> ndprint(x, 'Element[{1:d}]={0:.2f}')
['Element[0]=0.25', 'Element[1]=2.28', 'Element[2]=-1.88', 'Element[3]=0.70', 'Element[4]=1.03']

gem使它太容易获得字符串形式的结果(在今天的numpy版本中)隐藏在denis answer中: np.array2string

>>> import numpy as np
>>> x=np.random.random(10)
>>> np.array2string(x, formatter={'float_kind':'{0:.3f}'.format})
'[0.599 0.847 0.513 0.155 0.844 0.753 0.920 0.797 0.427 0.420]'

很惊讶没有看到周围的方法提到-意思是没有搞乱打印选项。

import numpy as np

x = np.random.random([5,5])
print(np.around(x,decimals=3))

Output:
[[0.475 0.239 0.183 0.991 0.171]
 [0.231 0.188 0.235 0.335 0.049]
 [0.87  0.212 0.219 0.9   0.3  ]
 [0.628 0.791 0.409 0.5   0.319]
 [0.614 0.84  0.812 0.4   0.307]]

用np。Array_str只对单个打印语句应用格式化。它给出了np的一个子集。set_printoptions的功能。

例如:

In [27]: x = np.array([[1.1, 0.9, 1e-6]] * 3)

In [28]: print(x)
[[  1.10000000e+00   9.00000000e-01   1.00000000e-06]
 [  1.10000000e+00   9.00000000e-01   1.00000000e-06]
 [  1.10000000e+00   9.00000000e-01   1.00000000e-06]]

In [29]: print(np.array_str(x, precision=2))
[[  1.10e+00   9.00e-01   1.00e-06]
 [  1.10e+00   9.00e-01   1.00e-06]
 [  1.10e+00   9.00e-01   1.00e-06]]

In [30]: print(np.array_str(x, precision=2, suppress_small=True))
[[ 1.1  0.9  0. ]
 [ 1.1  0.9  0. ]
 [ 1.1  0.9  0. ]]

我经常希望不同的列具有不同的格式。以下是我如何通过将NumPy数组(切片)转换为元组来打印一个简单的2D数组:

import numpy as np
dat = np.random.random((10,11))*100  # Array of random values between 0 and 100
print(dat)                           # Lines get truncated and are hard to read
for i in range(10):
    print((4*"%6.2f"+7*"%9.4f") % tuple(dat[i,:]))

还有一种选择是使用十进制模块:

import numpy as np
from decimal import *

arr = np.array([  56.83,  385.3 ,    6.65,  126.63,   85.76,  192.72,  112.81, 10.55])
arr2 = [str(Decimal(i).quantize(Decimal('.01'))) for i in arr]

# ['56.83', '385.30', '6.65', '126.63', '85.76', '192.72', '112.81', '10.55']