Numpy exercises¶

# impoprt numpy

import numpy as np

# Create an arbitrary one dimensional array called x

x = np.array([1,4,0,10,8])

# Create a new array which consists of the even indices of x you created before

y = x[::2]
y

array([1, 0, 8])

# Create a new array in backwards ordering from x

z = x[::-1]
z

array([ 8, 10,  0,  4,  1])

x = np.array([3, 10, 1, 9, 21, 13])
y = x[2:5]
y[0] = 0
print(x[2])

#5) Create a two dimensional array called x

m = np.random.randn(3,4)
m

array([[-0.48543923, -0.46328568, -0.82910729,  0.67650504],
       [-2.59927498, -0.44642341,  0.12432377, -0.34605895],
       [-0.73963889, -1.40607813, -0.72125986,  1.52833794]])

# Create a new array from m, in which the elements of each row are in reverse order.

n = m[:,::-1]
n

array([[ 0.67650504, -0.82910729, -0.46328568, -0.48543923],
       [-0.34605895,  0.12432377, -0.44642341, -2.59927498],
       [ 1.52833794, -0.72125986, -1.40607813, -0.73963889]])

# Another one, where the rows are in reverse order.

k = m[::-1,:]
k

array([[-0.73963889, -1.40607813, -0.72125986,  1.52833794],
       [-2.59927498, -0.44642341,  0.12432377, -0.34605895],
       [-0.48543923, -0.46328568, -0.82910729,  0.67650504]])

# Create an array from m, where columns and rows are in reverse order.

l = m[::-1,::-1]
l

array([[ 1.52833794, -0.72125986, -1.40607813, -0.73963889],
       [-0.34605895,  0.12432377, -0.44642341, -2.59927498],
       [ 0.67650504, -0.82910729, -0.46328568, -0.48543923]])

# Cut of the first and last row and the first and last column.

m[1:-1,1:-1]

array([[-0.44642341,  0.12432377]])