5.19 indexing and selection of array elements

In [1]:

    

import numpy as np


    

In [2]:

    

arr = np.arange(0,11)


    

In [3]:

    

arr


    

    
Out[3]:





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

In [4]:

    

arr[8]


    

    
Out[4]:





8

In [5]:

    

arr[1:5]


    

    
Out[5]:





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

In [6]:

    

arr[:6]


    

    
Out[6]:





array([0, 1, 2, 3, 4, 5])

In [10]:

    

arr[0:5] = 100


    

In [8]:

    

arr


    

    
Out[8]:





array([100, 100, 100, 100, 100,   5,   6,   7,   8,   9,  10])

In [9]:

    

arr = np.arange(0,11)


    

In [11]:

    

slice_of_arr = arr[:6]


    

In [12]:

    

slice_of_arr[:] = 99


    

In [16]:

    

arr # it's linked! slice_of_arr is just a view of the original array.


    

    
Out[16]:





array([99, 99, 99, 99, 99, 99,  6,  7,  8,  9, 10])

In [21]:

    

arr_copy = arr.copy() # this actually copies to a new array instead of linking


    

In [18]:

    

arr_copy[:] = 100


    

In [19]:

    

arr_copy


    

    
Out[19]:





array([100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100])

In [20]:

    

arr


    

    
Out[20]:





array([99, 99, 99, 99, 99, 99,  6,  7,  8,  9, 10])

In [25]:

    

arr_2d = np.array([[5,10,15],[20,25,30],[35,40,45]])
arr_2d


    

    
Out[25]:





array([[ 5, 10, 15],
       [20, 25, 30],
       [35, 40, 45]])

In [27]:

    

arr_2d[2][1] # double-bracket index notation


    

    
Out[27]:





40

In [29]:

    

arr_2d[2,1] # single-bracket index notation


    

    
Out[29]:





40

In [30]:

    

arr_2d[:2,1:]


    

    
Out[30]:





array([[10, 15],
       [25, 30]])

In [31]:

    

arr_2d[1:,:]


    

    
Out[31]:





array([[20, 25, 30],
       [35, 40, 45]])

In [34]:

    

arr_2d_big = np.array([[5,10,15,20],[25,30,35,40],[45,50,55,60],[65,70,75,80]])


    

In [38]:

    

arr_2d_big[1:3,1:3] # centerpunch the shit out of this new array


    

    
Out[38]:





array([[30, 35],
       [50, 55]])

In [40]:

    

arr = np.arange(1,11)
arr


    

    
Out[40]:





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

In [44]:

    

bool_arr = arr > 5
bool_arr # whaaaaat


    

    
Out[44]:





array([False, False, False, False, False,  True,  True,  True,  True,  True], dtype=bool)

In [47]:

    

arr[bool_arr] # mind: blown


    

    
Out[47]:





array([ 6,  7,  8,  9, 10])

In [48]:

    

arr[arr>5]


    

    
Out[48]:





array([ 6,  7,  8,  9, 10])

In [49]:

    

arr[arr<3]


    

    
Out[49]:





array([1, 2])

In [50]:

    

arr_2d = np.arange(50).reshape(5,10)


    

In [51]:

    

arr_2d


    

    
Out[51]:





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]])

In [52]:

    

arr_2d[1:3,3:5]


    

    
Out[52]:





array([[13, 14],
       [23, 24]])

In [ ]: