In [8]: import numpy as np

In [9]: a = [1,2,3,4]

In [10]: x1 = np.array(a)

In [11]: x1

Out[11]: array([1, 2, 3, 4])

In [12]: type(x1)

Out[12]: numpy.ndarray

In [13]: x2 = np.arange(11)

In [14]: x2

Out[14]: array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])

x = np.loadtxt('01.csv',delimiter=',',skiprows=1,usecols=(1,4,6),unpack=False)

In [18]: x.shape

Out[18]: (242, 3)

In [24]: open,close,volume = np.loadtxt('01.csv',delimiter=',',skiprows=1,usecols=(1,4,6),unpack=True)

In [26]: open.shape

Out[26]: (242,)

In [36]: c = np.random.randint(1,100,10)

In [37]: c

Out[37]: array([44, 26, 40, 87, 32, 82, 20, 70, 62, 14])

In [38]: c.min()

Out[38]: 14

In [39]: c.max()

Out[39]: 87

In [40]: c.mean()

Out[40]: 47.7

In [43]: y = np.sort(c)

In [44]: y

Out[44]: array([14, 20, 26, 32, 40, 44, 62, 70, 82, 87])