Task 3: Using numpy with random#

In this section, we will practice using the numpy library. First, import the numpy library

import numpy as np

# Your Solution here

3.1: Create a vector#

Task: Create an empty vector of size 10 filled with NaN.

Hint: you need to use zeros() method or the empty() method

# Your Solution here

3.2: Working with Vectors#

Task: Create a random vector of size 10 and then find its mean, max, min, and sum value.

Hint: for random vector you need to use np.random.random() and for the mean, max, min, sum you need to use build-in numpy methods mean(),max(),min(),sum().

Sample output (Your numbers will be different)#

[0.66698639 0.32937943 0.12074085 0.21788496 0.75628444 0.56461791 0.38162184 0.60966053 0.00491222 0.80007239]
The max is: 0.800
The min is: 0.005
The sum is: 4.452
The mean is: 0.445

# Your Solution Here

3.4: More vectors#

Task: This is a multi-step question. Read all the directions before you start working on the question and plan out your solution.

  • First, using numpy, create a vector of size 15 which contains random values ranging from 10 to 90

  • Then, replace the maximum value of your vector with 500.

  • Then, replace and the minimum value with -500.

  • Print the list (sorted by ascending order) and its mean before replacement, as well as the sorted list after replacement with the new mean.

Hint: To do this problem as intended, you may need to use the following numpy functions: copy(), sort(), argmax(), and argmin(). Also, don’t forget about f-strings and triple-quoted strings for printing.

Sample output#

Before number replacement

vector: [12 14 14 19 22 25 25 28 28 35 45 47 68 69 73]

vector_mean = 34.93

After number replacement

vector: [-500 14 14 19 22 25 25 28 28 35 45 47 68 69 500]

new_vector_mean = 29.27

# Your solution here