NumPy Arrays: Selecting Array Elements

gist_numpy_2.py

import numpy as np

# select array elements
np1 = np.arange(0, 10)
np1

# select 3rd and 5th elements
np1[2]
np1[4]

# two dimensional array
a2 = np.arange(0, 12).reshape(3, 4)
a2

# retrieve element in 1st row/2nd column
a2[0, 1]

# retrieve element in 3rd row/4th column
a2[2, 3]

# retrieve second row
a2[1,]

# retrieve third column
a2[:, 2]

# logical expressions
np1 = np.arange(0, 10)
np1 < 4

# complex expressions
(np1 < 4) | (np1 > 7)

# specify expressions within [] operator
np1[np1 < 4]

# complex expression
np1[(np1 < 4) | (np1 > 7)]

# slicing arrays
np1 = np.arange(0, 10)
np1

# retieve elements from 3 to 7
np1[2:7]

# retrieve all elements from 3rd position
np1[2:]

# retrieve all elements upto 6th position
np1[:6]

# skip every third element
np1[::3]

# select element 2 throuugh 8 while skipping every second element
np1[1:9:2]

# retrieve data in reverse order
np1[::-1]

# retrieve element 8 through 2 while skipping every second element in reverse
np1[8:2:-2]

# two dimensional array
np2 = np.arange(0, 12).reshape(3, 4)
np2

# retrieve columns 1 and 2
np2[:, 1:3]

# retrieve rows 2 and 3
np2[1:3,:]

# retrieve rows 2 and 3 and columns 3 and 4
np2[1:3, 2:4]

# select non-contiguous rows: rows 1 and 3
np2[[0, 2], :]

# select non-contiguous columns: columns 2 and 4
np2[:, [1, 3]]