Python NumPy Tutorial for Beginners
ฝัง
- เผยแพร่เมื่อ 6 ส.ค. 2019
- Learn the basics of the NumPy library in this tutorial for beginners. It provides background information on how NumPy works and how it compares to Python's Built-in lists. This video goes through how to write code with NumPy. It starts with the basics of creating arrays and then gets into more advanced stuff. The video covers creating arrays, indexing, math, statistics, reshaping, and more.
💻 Code: github.com/KeithGalli/NumPy
🎥 Tutorial from Keith Galli. Check out his TH-cam channel: / @keithgalli
⭐️ Course Contents ⭐️
⌨️ (01:15) What is NumPy
⌨️ (01:35) NumPy vs Lists (speed, functionality)
⌨️ (09:17) Applications of NumPy
⌨️ (11:08) The Basics (creating arrays, shape, size, data type)
⌨️ (16:08) Accessing/Changing Specific Elements, Rows, Columns, etc (slicing)
⌨️ (23:14) Initializing Different Arrays (1s, 0s, full, random, etc...)
⌨️ (31:34) Problem #1 (How do you initialize this array?)
⌨️ (33:42) Be careful when copying variables!
⌨️ (35:45) Basic Mathematics (arithmetic, trigonometry, etc.)
⌨️ (38:20) Linear Algebra
⌨️ (42:19) Statistics
⌨️ (43:57) Reorganizing Arrays (reshape, vstack, hstack)
⌨️ (47:29) Load data in from a file
⌨️ (50:20) Advanced Indexing and Boolean Masking
⌨️ (55:59) Problem #2 (How do you index these values?)
⭐️ Links with more info ⭐️
🔗 NumPy vs Lists: / channel
🔗 Indexing: docs.scipy.org/doc/numpy-1.13...
🔗 Array Creation Routines: docs.scipy.org/doc/numpy/refe...
🔗 Math Routines Docs: docs.scipy.org/doc/numpy/refe...
🔗 Linear Algebra Docs: docs.scipy.org/doc/numpy/refe...
--
Learn to code for free and get a developer job: www.freecodecamp.org
Read hundreds of articles on programming: www.freecodecamp.org/news
![[Full Episode] MasterChef Junior Thailand มาสเตอร์เชฟ จูเนียร์ ประเทศไทย Season 3 Episode 1](http://i.ytimg.com/vi/Qs5zdBqLn_8/mqdefault.jpg)
Keith, I've taken a heavy interest in data science lately and your courses absolutely rock !!!
Many thanks to you for teaching me these fundamentals in such an informative, easy-to-understand manner.
how is the progress?
Seriously, side-by-side comparisons are the BEST !! As visual as it can get ! 🙏
You Sir are an amazing teacher!! There are many software gurus in the world, but sadly few who can impart their knowledge as you do...
finally, done with the entire video, tbh, it took me 6 hours to get myself acquainted with the working of the NumPy library and the Jupyter notebook. Thank you for this awesome tutorial
Well done. Quick ,short & straight to the point!
This was a phenomenal overview of numpy. I feel confident that I can tackle more advanced topics now!
1.25 speed is perfect, thanks for the video
thanks for tips
I'm on 2.5
Thx bro
Yup
2x speed is better. Saves alot of time.
One of the finest Numpy tutorials. Keep up the great work guys!
This is the first tutorial that I actually finished. Thank you, Keith!
Absolute clarity and upto speed. Very comprehensive coverage.
Thats the most english I have heard all day
@@63khushalsolanki9 lol
⭐️ Course Contents ⭐️
⌨️ (01:15) What is NumPy
⌨️ (01:35) NumPy vs Lists (speed, functionality)
⌨️ (09:17) Applications of NumPy
⌨️ (11:08) The Basics (creating arrays, shape, size, data type)
⌨️ (16:08) Accessing/Changing Specific Elements, Rows, Columns, etc (slicing)
⌨️ (23:14) Initializing Different Arrays (1s, 0s, full, random, etc...)
⌨️ (31:34) Problem #1 (How do you initialize this array?)
⌨️ (33:42) Be careful when copying variables!
⌨️ (35:45) Basic Mathematics (arithmetic, trigonometry, etc.)
⌨️ (38:20) Linear Algebra
⌨️ (42:19) Statistics
⌨️ (43:57) Reorganizing Arrays (reshape, vstack, hstack)
⌨️ (47:29) Load data in from a file
⌨️ (50:20) Advanced Indexing and Boolean Masking
⌨️ (55:59) Problem #2 (How do you index these values?)
Why?
thanks bhai
+
@@yahyafati u were dumb or something'
@gokul8747 is the hero of this comment section
This is absolutely great content! Thank you so much for doing this!
Thank you for great video, Keith Galli. I had some problem of understanding Numpy before. Thanks to your help, I have strong basic knowledge of Numpy :)
This guy is smart and he makes this stuff really interesting !!! I like it !!!
Just finished it. It was really awesome! I like how you would look at your notes, so that we don't see you 😂. Thanks a lot for this tutorial Keith Galli. Not following any other tutorial on Numpy. Take love!
Much better than courses that I've paid good money for - Top Man Galli
Really well put together, thanks! :)
Amazing! Thank you for the explanation dude. It is really helping me with a certification course that I’m taking now
great vid, thanks for leaving the little mistakes in there, helps me remember that I dont have to be perfect at this and remember every little thing
Thanks for the free class! I'm just learning programming :) I felt very motivated after I could make the array on Problem #1
learning as well, would u like a study budy?
Nice mate! What a wonderful review from all the possible uses of Numpy. Thanks a lot!
excellent tutorial. feeling comfortable with numpy now thanks to you :)
Thanks you Keith , great video (also subscribed to your channel). Also thanks to FCC , love you for your service!
Thank you very much sir... the course is crystal clear... thank you
Thanks so much Keith, for the very educating tutorial. Quite explanatory
This video improved my numpy information. So thanks everybody who contributed.
for the part at 31:50
a = np.zeros((5,5), dtype='int8')
a[:,0:5:4], a[0:5:4,:], a[2,2] = 1, 1, 9
imp points:
5:38 contiguous memory
8:28 how are lists diff than Numpy
9:42 applications of numpy
26:17 full and full like
Super helpful tutorial.
When you went back and used -1 indexes instead of exclusive 4's at 33:36 my world stopped imploding. Thank you.
Why tho?
Thanks for your effort and the good stuff. Effective introductory! Thanks
love the content ! i have just started to learn numpy for my course and this certainly helped !! cheers , would be looking forward to your content!
Thank you! The only thing was a little bit complicated to me is working with axis. None the less, great tutorial!
رحؤنشضهكبءخؤذمء ء يددحمس
Excellent pace and explanations -- thank you!
This is a great tutorial, thanks!!
Thank you bro! This was an amazing tutorial!
Even OpenCV a top choice among computer vision professionals uses numpy array to store the image data....
Basically if you know how to manipulate numpy array you can do fine / pixel level operations...
really appreciate your video.
Awesome Tutorial. Thank you very much, Keith !
Thank you dude ! That was great !
Watching this at 2x speed so I can learn Numpy in 29 minutes instead of 58 minutes.
i have installed video controller extension, i am watching at 2.5x
@@krrishkataria560Just don't watch the video and read the specific documentation. It will be even faster if you have skill.
Best crash course on Numpy ! Thank you for your interesting videos
Really amazing introduction to numpy, it helps a lot
Thank you man!
Thank You for clearing my concepts on NumPy library.
Thank you so much for this amazing video!
one of the best numpy tutorial ever
The second exercise from last part we can do this as well: a[range(0,4),range(1,5)]
shouldn't the two range functions be in square brackets so as to make them a list
@@bhavpreetsingh1842 Hello Bhavpreet. I think that is a good practice to use square brackets to read the function, but it`s not necessary. You can test and see that works :)
Even i did the same way ✌️🤟
Mine: np.hstack(a[0:4, 1:5])[0:19:5]
a = Np.arrane([0, 4] [1,5]) is more efficient
Good job, way to go. Salute from Brazil.
Thank you Keith for this awesome tutorial!
ur tutorial IS AWESOME, plz do more man i also watched ur pandas too and it was as expectedly AWESOME tnx for the help man i appreciate it
Thanks a lot for this video!! much appreciated really !
Great video and awesome examples
Great tutorial completed full. Love from heart
Excellent sir, very well explained !! Many thanks for uploading. 5 stars. ⭐⭐⭐⭐⭐
Great Tutorial .. can u upload the pandas, scikit learn also.. So we will get the complete basic ml package
Also matplotlib
Thank you very much for sharing the video. It was very helpful.
Thank you for uploading this.
Great video . God bless you and you keep making such great videos
Just completed this tutorial. Thanks a lot for the content. Peace Out!!
Very good job, it was very helpful to me, thank you!
Here's how you watch these videos:
Hover over your right arrow key and hit it when he's initializing or doing some boring stuff,
and when something interesting happens, something you might wanna know, you stop, pay attention, maybe type something similar in your own jupyter notebook; continue.
Don't watch it at 2x speed. It doesn't work...
Reading docs is hard! So this video is really cool.
Fantastic Tutorial !!!!
Loved It !!!
Thanks bro you I have learnt a TON of stuff from your tutorials
Love. this. Truly great content and it was even nice to see the little faux pas because everyone has those!
thanks for making this video ! It's helpful !
Thanks for this amazing course!!
Great video.
Thanks!
Thanks a lot, man. You are amazing.
Awesome Keith, thank you for this great video
Thank You! 😊
Thank you for the useful content. The very quick start with numpy.
Great video. LOVED IT!
Excellent video. Thank you so much.
At the end, I indexed [2, 8, 14, 20] as np.delete(a[a%6 == 2], -1) to make use of the cool stair pattern
Great Tutorial!!
Fantastic tutorial, thank you
completed. thanks man! u r amazing
What happened to the live stream, I can't focus anymore!!!
very very helpful. thank you!
Thank you so much for this video :) :)
Thanks for the awesome video!
Thank You Very Much for teaching us this nicely
Thank you so much for this video. It helped a lot.
very good video for learning numpy every topic is covered very well.....
Thank you. Very helpful.
Thanks for the tutorial! 👍
thank you very much for your efforts,could you talk about pygame with pymunk on details?
That was PRETTY amazing. Thankyou. But the most interesting thing was that I was the exact 3k'th like because I liked and unliked the video several times to confirm it.
Thnx for these great lessons
.😇
Thank you for the video, its help me a lot to understand the concept and the function
welcome to check my playlists also. I made most of the videos for Python and R. easy to follow.
I pressed the thumb up twice as you wanted
Great video! Just got confused on min 43:55, output 143 should be a sum, but rather we got an array.
Awesome work dude.
love from India
Thanks you for this amazing video , great explaination
I did the matrix exercise a bit differently:
arr = np.ones((5, 5))
arr[1:-1, 1:-1] = np.zeros((3, 3))
arr[2, 2] = 9
Nice. I noticed, you can also just use 0 instead of np.zeros((3, 3))
Thanks for everything big man
Very well done!!!
Very good! Thanks a lot :)
The first 11 minutes of the video have really useful info
We can also solve the exercise at 33' using
output = np.ones((5,5))
print(output)
output[1:4,1:4]=0
print(output)
output[2,2]=9
print(output)
I solved it in the same way as you :)
Thanks man. Great content. Cheers
Thank you for the lesson