campus-fryslan-introduction-to-python/Week-2/02. Vector operations.ipynb

In this exercise, we'll do calculations on many numbers at once. Python provides the numpy library for that.

In [ ]:

# !pip install numpy

In [ ]:

import numpy as np

%matplotlib notebook
from matplotlib import pyplot

Exercise: Use np.arange(..., ...) to create a vector from 0 up to and including 5.

In [ ]:

x = None

print('x: ', x)

Exercise: Extract 1 from all the numbers

In [ ]:

y = None
print('y: ', y)

Exercise: Take the square root of all these numbers, either using ** 0.5 or np.sqrt( ... )

In [ ]:

y = None
print('y: ', y)

Notice that the square root of -1 is not defined, and hence the result is not a number (nan).

The cell below will make a plot of x and y.

In [ ]:

pyplot.plot(x, y)
pyplot.xlabel('x')
pyplot.ylabel('y')
None

You have learned to use numpy for so called vector operations, these are mathematical operations on many numbers as well. This field is called linear algebra, and is a usefull field on its own, in particular often used in artificial intelligence.