Complete Python NumPy Tutorial (Creating Arrays, Indexing, Math, Statistics, Reshaping)

I popped an adderall and watched this video. Fuckin great time, it was. Thank you for this, I feel like I know numpy now

Thanks man, appreciate your work

Very good introduction course for numpy entry. Do you have any recommendation to further numpy learning? Thank you

If anyone wants to attempt it, here's a challenge:

Write a function that makes a target with each ring having a progression of integers.
target(1) = [[0, 0, 0], [0, 1, 0], [0, 0, 0]]
target(2) = [[0, 0, 0, 0, 0], [0, 1, 1, 1, 0], [0, 1, 2, 1, 0], [0, 1, 1, 1, 0], [0, 0, 0, 0, 0,]]
target(3) = [[0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 2, 2, 2, 1, 0], [0, 1, 2, 3, 2, 1, 0], [0, 1, 2, 2, 2, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0]]

My solution is in the replies 😃

Keep different sentences dont overwrite (replacing one with another etc...

Thank you for the great course but most of all thank you for not being messy and going every where. Most tutorials dont follow any logic and jump from one thing to another without any logical line

Definitely the BEST tutorial i have watched !

Thanks so much! Amazing teaching!

Very useful tutorial! Really helped me. keep on!

This was super helpful, Thanks Keith!

Nice job doing an intro explaining why NumPy is so powerful before heading to the how-tos

thank you

Oh man, I started learning code watching your videos. Why don't you keep them coming?

goated

Anyone ever tell you you look like neville from Harry Potter??

hey man great content! i've done 3 of your tutorials!!! I'm doing this one right now and I have a question:

[[[[ 1 2 3 4 5]]

[[ 6 7 8 9 10]]]


[[[11 12 13 14 15]]

[[16 17 18 19 20]]]]

from this 3d array can I select in just one command:

from the 2nd table, the last 3 objects of the 1st row and the first 3 objects of de 2nd row

thanks in advance!!!

thanks, it actually let me through so i could download it.

In array reading the data is faster and in list appending is faster.

Thanks Keith

Fantastic video !

Watching from india

Great tutorials, very simplified

Thank u sooo much bro

Great content

Thanks Keith.

This was my solution to the first challenge, am I a n00b?

arr = np.zeros([5, 5])
arr[0, :] = 1
arr[-1, :] = 1
arr[:, 0] = 1
arr[:, -1] = 1
arr[2, 2] = 9

print(arr)

Thank you ✌️

informative

I am a PhD student in Statistics, but currently a ML intern at Microsoft and your videos are the only thing that help me transition from the statsy R-coding world to Python. Thank you!

Super helpful to understand!

Thanks for including the background..

Muchísimas gracias por el aporte genio :')

I'm halfway through the video and so far so good. Nice tutorial !

Nice tut, bro.

nice video, thank you

Hi Keith!!!, As you were telling about Lists and NumPy differences that Lists do not use contiguous memory then there is no point of indexing in Lists, but still, it supports.
Little confused with this. Help Appreciated.

Great examples! Thank you!!!

thanks sir

Hey Keith! Thank you for such a clear and concise intro to Numpy. My question is - does each array have to have the same amount of elements. For example, array a has 4 elements and array b has 4. One cannot have 4 or 6 on array b, would that be a correct assumption?

My lord I'm coming from Node and just needed something to handle big sets of data and as easy as the syntax is for python it's sooo different from node. I'm not saying there aren't any but I don't know of any other language that cares how far you indent things and it's driving me fucking nuts.

thank you so much!
i just start using python, and it really help me.

Imo:

Indexing and reshaping goes a long way to understanding rest of the library. There’s only a few functions that don’t necessarily apply the ‘same’ logic. Leveraging numpy efficiently saves you from writing a bunch of for loops, but it helps to know how to write these for loops if not simply to demonstrate your understanding.

hello keith, i am starting to learn the basics of programming using Python for Data science / ML, i have a long way to go and i am excited about the journey, thank you so much for this tutorial, i have just a question about loading the files, how does numpy locate the file to load??

This was simple, short, easy to understand while covering all major topics! plus if you know pandas then it's more easy ;)

Hi keith, you videos are really amazing and really helpfull. Thanks for this!!!!

Thank you.