NumPy Tutorial (2022): For Physicists, Engineers, and Mathematicians

So underrated, what a great channel ! Thank you from a physics engineering undergraduate.

Please, what is your PC configuration to use all this?

Brilliant presentation! You pretty much covered everything important for doing computational mathematics

np.sum(np.vectorize(lambda x: x if x % 4 != 0 and x % 7 != 0 else 0)(np.arange(0, 10000 + 1)))

Hey man ,you got one new subscriber 😊

you use the zeroes theorem

This is Awesome !!
Science girls should be in looove

Marvelous

Mr. P Solver, your videos have helped me a lot, but shouldn't the ODE of the simple pendulum in the thumbnail (d^2θ/dt^2 - sin(θ)*g/l = 0) have a plus (+) sign instead of a minus (-)? Thanks for the great video!

Man... This stuff is same as for machine learnig too? Or is there something new to learn?

Even after 2 years this is the most fun and informative video for numpy that i needed , really loved those exercises.
thank you for such an amazing content

This is the best channel I have come across for python, as an engineering student, I am so grateful! Thank you !!

i thought of an alternative to question 1 item 5:
crit_points = np.array([])
mindydx = np.array([])
deltasdydx = np.array([])
for i in range(0, len(dydx)):
if i != 1000:
deltasdydx = np.append(deltasdydx, x[i+1]-x[i])
# print(deltasdydx)
mindydx = deltasdydx.min()
print(mindydx)

for i in dydx:
if i+0.009999999999999787>=0 and i<=0:
pontos_crits = np.append(crit_points, i)
print(crit_points)

you take the 3 minimum values of the final array and that's the y values you are looking for, i don't know how to get back the x value tho
also, that 0.00999 number is the minimum difference between 2 consecutive y values

Can you please make a video where you write code for a nudged elastic band calculation? You use nudged elastic band methods to calculate the structure and energy of transition state(s) for a reaction. The classic example for a nudged elastic band calculation is determining the structure and energy of the transition state for H2 splitting.

Completed today. Thanks for this great resource Luke!

While using the Ferrari's method for solving a quartic equation, it showed up with a very lengthy solution with both real and imaginary components. How can I separate the real and imaginary components from the final solution?

Please continue making video

hello Mr. P Solver, I really love your videos but with regards to that multi-dimensional arrays, 3D animations would really help.

Thanks for this great tutorial.

Man you should get your line of courses on udemy: just like neetcode is a much better option than algoexpert for algorithms/data structures or to learn unreal engine, Stephen Ulibarri's courses are much better than Ben Tristem's, you could easily beat Jose Portilla in Python +Machine learning

In Question 3(tougher), how to know that meshgrid should have variables as (t, z) or (z, t)? Because this interchanges the plot for z=0 and t=0.. which one is correct way?

Thanks a lot mate. Please keep posting. I find these videos tremendously helpful for my Computational Nano electronics course.

These videos are great, man.

Dear Mr. P Solver, I am very thankful for your Python tutorial videos. I have learnt much more things. Thank you again.

Thank you.

better than most of the other video tutorials on numpy that I have seen...

I never compliment people but...this dude is fantastic.

Can numpy help an artist?

please meke a video about numba

Thanks

The illustration and speed is just amazing😎

Impressive, wonderful python skills.

so useful

Very good tutorial, thank you! I

best tutorial

Your tutorial are very easy to learn yet very concise, informative and in-depth. Please keep making such contents.

brilliant series, many people say that scientists use NumPy, scipy but you showed "HOW TO DO IT"

Thank you, Luke. Can you upload the meshgrids diagram , thanks!

i dont understand why but i am unable to have the graph appear anymore without doing plt.show() and it is very tedious how do i do it as .plot() only?

Canada seems to be a country with very good education system

I hope the algorithm blesses you. Best tutorial for NumPy on the internet hands down.