Click on New in the upper right-hand side of the screen, then select Python 3 (pykernel) to open up a new Jupyter Notebook file. Copy the code snippets below into the In window and run the code. Copy the results below each code snippet and briefly explain the actions the code performed. Click on the plus sign, to open a new In window for each code snippet.

a) Creating and reshaping arrays
1)
import numpy as np
a_arr = np.array((1, 2, 3, 4))
a_arr

2)
b_arr = np.arange(0, 16)
b_arr

3)
c_arr = b_arr.reshape(4, 4)
c_arr

4)
d_arr = np.arange(10, 26).reshape(4, 4)
d_arr

b) Accessing and altering elements within an array,
1)
a_arr[2]

2)
a_arr[2] = 5
a_arr

3)
a_arr.dtype
a_arr.ndim
a_arr.shape
a_arr.size

c) Aggregate functions

1)
d_arr.sum()
d_arr.min()
d_arr.max()
d_arr.mean()
d_arr.median()
d_arr.std()

d) Arithmetic Operations, Matrix Operations, Broadcasting, and Comparisons

1) Arithmetic operations
a_arr + 5
e_arr = c_arr + d_arr
e_arr
e_arr = c_arr - d_arr
e_arr
e_arr = c_arr * d_arr
e_arr
e_arr = d_arr / c_arr
e_arr

Question:
• What is the problem with the statement above

e_arr = np.sqrt(d_arr)
e_arr

2) Matric operations

f_arr = np.dot(c_arr, d_arr)
f_arr

3) Broadcasting

g_arr = a_arr * c_arr
g_arr

4) Comparisons

c_arr< 6
c_arr = c_arr * 10
c_arr < f_arr

e) Joining, Splitting, and Splicing Arrays

1) Joining
w_arr = np.vstack((c_arr, f_arr))
w_arr
w_arr = np.hstack((c_arr, f_arr))
w_arr

2) Splitting

x_arr = np.hsplit(c_arr, 2)
x_arr

x_arr = np.vsplit(c_arr, 2)
x_arr

3) Slicing

One dimensional array

b_arr[2:10:3]

b_arr[:10:3]

b_arr[::3]

Two-dimensional array

c_arr[0:1, :]

c_arr[0:1, 1:3]

c_arr[1:3, 1:3]

f) Saving and Loading Arrays

1) Saving

np.save('c_arr.npy',c_arr)

2) Loading
np.load('c_arr.npy')