Python for Finance - Second Edition

Introduction to NumPy

In the following examples, the np.size() function from NumPy shows the number of data items of an array, and the np.std() function is used to calculate standard deviation:

>>>import numpy as np
>>>x= np.array([[1,2,3],[3,4,6]])     # 2 by 3 matrix
>>>np.size(x)                         # number of data items
6
>>>np.size(x,1)                       # show number of columns
3
>>>np.std(x)
1.5723301886761005
>>>np.std(x,1)
Array([ 0.81649658, 1.24721913]
>>>total=x.sum()                      # attention to the format
>>>z=np.random.rand(50)               #50 random obs from [0.0, 1)
>>>y=np.random.normal(size=100)       # from standard normal
>>>r=np.array(range(0,100),float)/100 # from 0, .01,to .99

Compared with a Python array, a NumPy array is a contiguous piece of memory that is passed directly to LAPACK, which is ...