目录

数据的CSV文件存取

np.random的随机数函数

NumPy统计函数 

数据的CSV文件存取

保存文件：savetxt()方法保存文件

csv文件格式：

np.savetxt(frame,array,fmt='%.18e',delimiter=None)

示例：

In [1]: import numpy as np
In [2]: a = np.arange(100).reshape(5,20)
In [3]: np.savetxt('a.csv', a, fmt='%d', delimiter=',')

读取文件： loadtxt()方法读取文件

示例：

In [5]: b = np.loadtxt('a1.csv', delimiter=',')
In [6]: b

np.random的随机数函数

示例：

In [18]: a = np.random.rand(3,4,5)
In [19]: a
Out[19]: 
array([[[ 0.97845512,  0.90466706,  0.92576248,  0.77775142,  0.84334893],
        [ 0.39599821,  0.31917683,  0.7961439 ,  0.01324569,  0.97660396],
        [ 0.5049603 ,  0.80952265,  0.67359257,  0.89334316,  0.94496225],
        [ 0.04840473,  0.04665257,  0.20956817,  0.62255095,  0.36600489]],

       [[ 0.58059326,  0.28464266,  0.23596248,  0.16677631,  0.86467069],
        [ 0.14691968,  0.60863245,  0.71725038,  0.69206766,  0.18301705],
        [ 0.73197901,  0.99051723,  0.10489076,  0.33979432,  0.0354286 ],
        [ 0.73696453,  0.48268632,  0.99294233,  0.06285961,  0.93090147]],

       [[ 0.07853777,  0.827061  ,  0.66325364,  0.52289669,  0.96894828],
        [ 0.41912388,  0.01883408,  0.80978245,  0.93082898,  0.98095581],
        [ 0.58614214,  0.55996867,  0.37734444,  0.79280598,  0.03626233],
        [ 0.233132  ,  0.22514788,  0.32245147,  0.13739658,  0.18866422]]])

 

示例：

In [28]: a = np.random.randint(100,200,(3,4))
In [29]: a
Out[29]: 
array([[116, 111, 154, 188],
       [162, 133, 172, 178],
       [149, 151, 154, 177]])

NumPy统计函数 

np.random的统计函数 ：

 

 

示例： 

In [47]: a = np.arange(15).reshape(3,5)
In [48]: a
Out[48]: 
array([[ 0,  1,  2,  3,  4],
       [ 5,  6,  7,  8,  9],
       [10, 11, 12, 13, 14]])

In [49]: np.sum(a)
Out[49]: 105
In [50]: np.mean(a,axis=1)      # 2. = (0+5+10)/3
Out[50]: array([  2.,   7.,  12.])