In [40]:

    

my_list = [1,2,3,4,6]


    

In [73]:

    

my_list1 =[7,8,9,10]


    

In [53]:

    

import numpy as np
np.array(my_list)


    

    
Out[53]:





array([1, 2, 3, 4, 6])

In [82]:

    

np.array(my_list)
arr1 = np.array(my_list1)
arr1.size
arr1.max()
arr1.min()
arr1.mean()
arr1[0]
i = 0
for item in arr1:
    i =i+1
    print("The value of aar1 at {} is {}".format(i,item))


    

    




The value of aar1 at 1 is 7
The value of aar1 at 2 is 8
The value of aar1 at 3 is 9
The value of aar1 at 4 is 10

In [84]:

    

np.arange(0,101,1)


    

    
Out[84]:





array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,
        13,  14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,
        26,  27,  28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,
        39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,
        52,  53,  54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,
        65,  66,  67,  68,  69,  70,  71,  72,  73,  74,  75,  76,  77,
        78,  79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,  90,
        91,  92,  93,  94,  95,  96,  97,  98,  99, 100])

In [12]:

    

np.zeros(4)


    

    
Out[12]:





array([ 0.,  0.,  0.,  0.])

In [13]:

    

np.zeros((5,5))


    

    
Out[13]:





array([[ 0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.]])

In [14]:

    

np.ones(5)


    

    
Out[14]:





array([ 1.,  1.,  1.,  1.,  1.])

In [15]:

    

np.ones((5,2))


    

    
Out[15]:





array([[ 1.,  1.],
       [ 1.,  1.],
       [ 1.,  1.],
       [ 1.,  1.],
       [ 1.,  1.]])

In [16]:

    

np.linspace(0,5,50)


    

    
Out[16]:





array([ 0.        ,  0.10204082,  0.20408163,  0.30612245,  0.40816327,
        0.51020408,  0.6122449 ,  0.71428571,  0.81632653,  0.91836735,
        1.02040816,  1.12244898,  1.2244898 ,  1.32653061,  1.42857143,
        1.53061224,  1.63265306,  1.73469388,  1.83673469,  1.93877551,
        2.04081633,  2.14285714,  2.24489796,  2.34693878,  2.44897959,
        2.55102041,  2.65306122,  2.75510204,  2.85714286,  2.95918367,
        3.06122449,  3.16326531,  3.26530612,  3.36734694,  3.46938776,
        3.57142857,  3.67346939,  3.7755102 ,  3.87755102,  3.97959184,
        4.08163265,  4.18367347,  4.28571429,  4.3877551 ,  4.48979592,
        4.59183673,  4.69387755,  4.79591837,  4.89795918,  5.        ])

In [17]:

    

np.eye(5)


    

    
Out[17]:





array([[ 1.,  0.,  0.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  0.],
       [ 0.,  0.,  1.,  0.,  0.],
       [ 0.,  0.,  0.,  1.,  0.],
       [ 0.,  0.,  0.,  0.,  1.]])

In [20]:

    

np.linspace(0,10,10)


    

    
Out[20]:





array([  0.        ,   1.11111111,   2.22222222,   3.33333333,
         4.44444444,   5.55555556,   6.66666667,   7.77777778,
         8.88888889,  10.        ])

In [21]:

    

np.eye(5)


    

    
Out[21]:





array([[ 1.,  0.,  0.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  0.],
       [ 0.,  0.,  1.,  0.,  0.],
       [ 0.,  0.,  0.,  1.,  0.],
       [ 0.,  0.,  0.,  0.,  1.]])

In [22]:

    

np.eye(3)


    

    
Out[22]:





array([[ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0.,  1.]])

In [23]:

    

np.random.rand(5)


    

    
Out[23]:





array([ 0.70805922,  0.32995075,  0.06563086,  0.52214724,  0.81509092])

In [24]:

    

np.random.rand(5,5)


    

    
Out[24]:





array([[ 0.29539325,  0.32063851,  0.8866138 ,  0.75890405,  0.98091661],
       [ 0.63651079,  0.84405269,  0.18893612,  0.50544975,  0.64778334],
       [ 0.35256194,  0.27860473,  0.08643649,  0.97122912,  0.81005978],
       [ 0.939974  ,  0.82899092,  0.02691882,  0.37543135,  0.83742037],
       [ 0.27595103,  0.3940467 ,  0.72893862,  0.58451407,  0.71038499]])

In [31]:

    

np.random.randint(1,100,10)


    

    
Out[31]:





array([34,  1, 19, 76, 42,  5, 35, 65, 63, 70])

In [32]:

    

ranarr = np.arange(0,10)


    

In [33]:

    

ranarr


    

    
Out[33]:





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

In [34]:

    

ranarr.max()


    

    
Out[34]:





9

In [35]:

    

ranarr.min()


    

    
Out[35]:





0

In [36]:

    

ranarr.argmax()


    

    
Out[36]:





9

In [37]:

    

ranarr.argmin()


    

    
Out[37]:





0

In [87]:

    

values = np.random.randint(0,10,7)


    

In [89]:

    

values


    

    
Out[89]:





array([2, 9, 3, 2, 2, 2, 7])

In [92]:

    

val = np.array(values)


    

In [98]:

    

val[1]
val.max()
val = np.sort(val)


    

In [99]:

    

val


    

    
Out[99]:





array([2, 2, 2, 2, 3, 7, 9])

In [100]:

    

val = np.random.randint(1,10,10)


    

In [101]:

    

val


    

    
Out[101]:





array([6, 6, 9, 5, 6, 5, 1, 9, 3, 6])

In [102]:

    

val = np.arange(1,10)


    

In [103]:

    

val


    

    
Out[103]:





array([1, 2, 3, 4, 5, 6, 7, 8, 9])

In [104]:

    

np.rand(4,4)


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-104-6b57edb0928a> in <module>()
----> 1 np.rand(4,4)

AttributeError: module 'numpy' has no attribute 'rand'

In [105]:

    

import datetime as dt
import time as tm


    

In [106]:

    

tm.time()


    

    
Out[106]:





1480952164.516208

In [107]:

    

tm("7:00")


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-107-d2158d9488a1> in <module>()
----> 1 tm("7:00")

TypeError: 'module' object is not callable

In [ ]: