Intro to Numerical Computing with NumPy (Beginner) | SciPy 2018 Tutorial | Alex Chabot-Leclerc 

This is THE BEST numpy tutorial I've even seen so far. Underrated!

I love how he gives pauses for questions instead of constantly asking "any questions? Anyone?"

This is by far the most clear and comprehensive tutorial on numpy basics I have seen on the Internet. Great teacher, Great example and nice questions from audience as well.

Best introduction to NumPy and SciPy 👍🏽

Wow. This is much better than anything i found about NumPy all over the WWW.

Oh my God this just too good to be true resource I am an absolute beginner thanks for such a step by step approach.

The best NumPy tutorial I have come across. Thank you so much!!!

Another solution to the modulo 3: a = np.arange(25.0).reshape(5,5) a[(a%3)!=0]=np.nan

just excellent! Great job alex. 100% clear and followable

He has split second laughter and immediately changes into a serious mood haha

Thank you for the tutorial; very well explained! Great work Alex

Amazing content and Alex is just a superb teacher; very likeable and approachable. Great video, hope to see more like this!

Excellent tutorial. Even though I'm not a beginner, learned few new things

Thank you so much Enthought and Alex .....Superb Content !

Congrats! This is the best video I have seen so far on the matter. Kudos!

Alex, I learned a lot from your video. Thanks a lot for sharing :)

Thank you very much Alex sir.Superb explanation.

Best tutorial ! Awesome presentation. Thank You.

36:00 for negative indexes just replace the negative index by index + length, e.g a[-4,3] is same as a[5 - 4,3] = a[1,3]

Thank you! This is an excellent training!

Great video, a big thank you for sharing such amazing content. It was of much help. THANK YOU!!

Superb content. Thanks for the Instruction!

such amazing content , thanks for sharing . It will help a lot for me

Great content, presented well. It's nice to see some basic data analysis in plain old numpy, as opposed to pandas.

Great Video! Just a little rectification at 1:05:09 you stated that (and), (or) and (not) are binary operators. (not) is not a binary Operator, as a binary operator works on two operands, but a (not) just works on one.

Thanks a lot, Alex

4:16 start here

a = np.array(['Thank you! ']) a[0] * 1,000,000 That's all I have to say. 😊

"Why would the axis argument be the dimension that you collapse?" what other dimension would you collapse? (does your answer generalize to any operation and any number of dimensions? consider non-commutative operations and dimensions greater than 2)

Great content!

Very good explanation, Unfortunately I can not access the study material.

very informative ... this helped

Quick question : When both slicing and fancy indexing is used over 2D array, it why it does not return a copy and instead returns view?

at 02:36:35, alex slices the dates array and masks all january entries as true. When this mask is used as an argument in the winds array, how are boolean values converted to index of the winds array.

Method are define in class and applied to to particular class . Function are not define in class. Function in the class called methods

great video

Kindly help with the link to the tutorial materials; the one provided leads to a dead-end. Thanks.

Ohh yeah that is super duper..thanks

Hi, Seems like Link for tutorial materials is not available. Can you provide the link where i can find the materials used in this video

is it substituting MATLAB ?

Hello. How should I go about creating a mask specifically for a diagonal, given that all elements have the same value? For example, i have this: identity = np.arange(16).reshape(4, 4) identity.fill(0) Now i want to apply some mask such that i am able to convert the main diagonal to 1

very good teacher. it is hard to find here. unlike other assholes here "teach" python on youtube.

at 2:31:02, alex uses the second technique of finding the date of max. wind speed. i couldnt understand this, can someone explain it

Bravo!!!!!!!

Whenever he types a variable for example "a" and hit enters, the output is automatically the value i.e. "array.a=([1 2 3])". Why is it on my microsoft visual studio, it produces no output when i hit "a"? Is it because the ide Canopy automatically produces a result? So is this a capability of ide rather than python?

Is it any video's on data science or machine learning

Hi Alex I don't know if its just me, but I can't access the material via the link in the description. All I get is an XML file with an error tag at the end.

Can anyone provide the link for the material used on this clip , current link not working BTW awesome video

here's the link to slides and other files of this talk, github.com/enthought/Numpy-Tutorial-SciPyConf-2018

2:04:13 how do you do this in pycharm(access the documentation ) ?? please help

Where can I find the material and github link? the one in video description is not working.

Need PANDAS tutorial from same author!

20:30 you could use lambda function eh?

Link to the slides and the data for the class?

thx

Where is their githup repo?

can we have end question? =)

Am I the only one who thinks the instructor looks like zac efron?

where is the Github ripo?

where to download the slice ?

6:44 7 ms per loop? i got 78. damn my laptop is ancient