Python 4 Engineers — Even More Exercises!

More Practising Coding Questions in Python! — #PySeries#Episode 09

What follows are 10 Q&A plus 2 bonus:

Let’s get it on!

01#PyEx — Python — Imaginary Number:

Given z_1=3+4j and z_2=-5+14j. Compute z_1/z_2:

Solution:

z_1=3+4j
z_2=-5+14j
z_1/z_2
(0.18552036199095023-0.28054298642533937j)

02#PyEx — Python — Linear System:

What is the function in Python to solve Linear Systems?

Solution:

np.linalg.solve()

03#PyEx — Python — Definite Integral:

Using Python, compute integral of f(x) = x³+cos(x) in a range [0,3]:

Solution:

from sympy import *
x,f=symbols(“x f”)
init_printing()
f=x**3+cos(x)
integrate(f,(x,0,3))
sin(3)+4/81​

04#PyEx — Python — Indefinite Integral:

Calculate the indefinite integral of the function:
 f’(x) = 6x⁵+cos(x);

Solution:

from sympy import *
x,f=symbols(“x f”)
init_printing()
f=6*x**5+cos(x)
integrate(f,x)
x^6+sin(x)

05#PyEx — Python — Vectorial:

What is the function in Python to solve vector products?

Solution:

uXv=np.cross(u,v)

06#PyEx — Python — Linear System:

Using python, solve the following linear system:
4x-3y+z=15
x+y+3z=27
2x+3y-4z=31

Solution:

import numpy as np
A=np.array([[4,-3,1],[1,1,3],[2,3,-4]])
b=np.array([[15],[27],[31]])
x=np.linalg.solve(A, b)
print(x)
[[9.2345679 ]
[8.35802469]
[3.13580247]]

07#PyEx — Python —Points Interpolations:

Get through python the function that interpolates the points: 
A(1,5), B(3,4), C(5,9) and D(9,11):

Solution:

from scipy.interpolate import *
x=[1,3,5,9]
y=[5,4,9,11]
f=lagrange(x,y)
print(f)
-0.1354 x^3 + 1.969 x^2 - 6.615 x + 9.781

08#PyEx — Python — Linear Regression:

Which best line that fits these points? 
A(1,5), B(3,4), C(5,9), and D(9,11)

Solution:

import numpy as np
import matplotlib.pyplot as pyp
from scipy import stats
x=np.array([1,2,3,4,5])
y=np.array([180,120,150,190,210])
a,b,correlation,p,error=stats.linregress(x,y)
print(‘Regression line: y=%.2fx+%.2f’% (a,b))
print(‘Correlation Coefficient: r=%.2f’% correlation)
f=a*x+b
Regression line: y=13.00x+131.00 
Correlation Coefficient: r=0.58

09#PyEx — Python —Vectorial:

Given the vectors: 
u = (7, -22, 13) and 
v = (-1, 11, 23); 
calculate u.v and uXv:

Solution:

import numpy as np
u=np.array([[7,-22,13]])
v=np.array([[-1,11,23]])
uv=np.inner(u,v)
uXv=np.cross(u,v)
print(uv)
print(uXv)
[[50]] 
[[-649 -174   55]]

10#PyEx — Python — Trigonometry:

What is the angle which cosine is -0.6544?

Solution:

import numpy as np
angle=np.arccos(-0.6544)
np.rad2deg(angle)
130.87417042181528

01Bonus#PyEx — Python — Derivative:

Can we calculate the derivative in python using?

Solution:

Yes. use lib simpy and diff command

02Bonus#PyEx — Python — Derivative:

Can we calculate the integrate in python using?

Solution

Yes. Use lib simpy and integrate command

See you in next PySeries!

Bye, for now, o/

Download all Files from the Colab Repo

References & Credits

Thank you, Mr. Ricardo A. Deckmann Zanardini — You are an Awesome Teacher! o/; Text published while I’m studying Computer Engineer at Escola Superior Politécnica Uninter🏋!

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