NumPy Full Python Course - Data Science Fundamentals

This video is a full crash course for NumPy in Python. We learn everything from scratch.
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Timestamps:
(0:00) Intro
(1:21) Installation
(2:19) NumPy Arrays
(5:26) Array Attributes
(8:14) Numpy Data Types
(15:09) Filling Arrays
(20:16) NaN & Inf
(22:34) Mathematical Operations
(28:31) Array Methods
(32:50) Structuring Methods
(40:25) Concatenating, Stacking, Splitting
(45:35) Aggregate Functions
(46:43) NumPy Random
(49:38) Exporting & Importing
(51:46) Outro

[@ChromaDotNova]

Appreciate the quick overview, especially on saving data and importing data to and from files.

[@nunolopes3910]

Great video, really appreciate this quick crash courses!

[@raymondvaldepenas7758]

This is great! Thank you for this awesome numpy course😁

[@PlexAlanche]

Was waiting for this! Thanks a lot!

[@sifarathussain1335]

No Time Waste, To the point video, Thank you, Sir.
You made a lot of students life easy

[@Synthetic_geth]

Underrated channel
Great work!

[@NiepoprawnyKomentator]

This channel is my discovery of this week! :)

[@muralidhar40]

This is my intro to numpy and mind blown!

[@abhinavchoudhary6849]

Thank you bro for such amazing numpy crash course

[@fahmidhossainSakib]

Great content ! Thanks a lot !

[@EkwuziMunachi]

Thanks bro for such a nice course!

[@iltrovatoremanrico]

Great tutorial, thanks!

[@rio5172]

Bro is a menace. Thank you!

[@reubenthomas1033]

One each for Pandas, matplotlib and seaborn also please!

[@thunderskull258]

Yes

[@I_am_AmanSingh]

yes please that would be amazing

[@YazhShah]

Nice one brother!

[@abhijitmondal7831]

Aahhhh... Finaly ❤️

[@thunderskull258]

Best course on numpy on yt

[@HaniCreateTV]

thanks for that!💚

[@Stephen-ed4pp]

Splendid crash course

[@user-lt6uu5ud9u]

Full of useful information, i.e. without extra

[@nmelqonyan2561]

After wasting my time for 1 month and understanding nothing from those courses explaining Numpy with anaconda, I found this course, simple, understandable, finally!!!!!!!!!!thanks

[@SzTz100]

Top notch tutorial

[@IronBen117]

thank you!

[@faridibadov2000]

saved my time and nerves!

[@mob5383]

Thanks!

[@leolee1089]

awesome tutorial

[@piotrmazgaj]

Great! By all means, please do Panadas as well!

[@lets_code_this2678]

GOOD AND THX SO MUCH

[@brighttech8146]

Hey man you are the best python teacher keep it up and i have questions if u can answer me

[@nicolasvargas6846]

Thanks😁

[@hirentank5260]

Thank you so much

[@979259]

great tutorial

[@hamidrezaakbari7611]

Thank you

[@Smaug1248]

Thanks a lot

[@kklol07]

amazing mate, even if i know this, i cant stop viewing, haha

[@kazisamir123]

you are the best

[@linnmoe3953]

Thanks.

[@tcgvsocg1458]

i hit the like button only because he look so pride of his knowledge...

[@ankidokolo]

Just in time.
Would be great to do one for matplotlib also.
Thanks.

[@user-wj5xe2tm4d]

Thank u for the course. I am from india

[@loknathsaha9393]

Great

[@giovannicordova4803]

Will there be more videos on C programming?

[@sinistral941]

Very nice👌 Please also make a Video for pandas. Thank you.

[@thunderskull258]

I wanted to know if we can find determinant, minor, cofactor, adjoint
in numpy

[@b391i]

I'm sorry guys, but I have to say it: this channel is awesome.

[@Sinke_100]

U could also said something about dot

[@Sinke_100]

Not sure why for me default is int64

[@user-el8bf5vn7q]

In the first part of video understanding, I have one question. Why did u wrote print(a_mul[0][0]) if u can print(a_mul[0,0]) ?

[@boghost2997]

these are the same thing, you can write the one u prefer

[@Alan-lw4kk]

which IDE are you using

[@davidzwitser]

So basically it's just APL or BQN but way worse because it's not idiomatic to the language. Super cool that array programming is secretly very populair tho 😄

[@JuanCarlosMH]

Pandas!

[@markkennedy9767]

From 13:30 to 14:00 ,wha? 🤔
At 26:50, you say whenever you have arrays that we can think of matrices or vectors, you can do the arithmetic operations. What is meant by this: Can't all arrays be thought of as either matrices or vectors.
It would have been more helpful if you explained broadcastability of arrays when applying these arithmetic operations rather than just moving on to the next topic. Its an important topic.
At 34:00, can you explain why the syntax is a.reshape((2,3)), i.e. a method, rather than np.reshape((2,3),a), i.e. a function. Since a.reshape() isn't modifying in place (it's not changing a), why not just have it as a function.

[@harshmalviya5967]

please create pandas tutorial too

[@PandaVlademirBerlin]

handsome boy

[@gamingkakshaa]

Bro want to collaborate with me for one video 👍 from India

[@ahmadbodayr7203]

great bro , Read About Islam if you are not muslim ❤

[@tangrechristopherkolbil1853]

Great