Python NumPy Tutorial for Beginners

///Python NumPy Tutorial for Beginners

Python NumPy Tutorial for Beginners

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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:

🎥 Tutorial from Keith Galli. Check out his YouTube channel:

⭐️ 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:
🔗 Indexing:
🔗 Array Creation Routines:
🔗 Math Routines Docs:
🔗 Linear Algebra Docs:

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By |2021-07-17T15:10:14+00:00July 17th, 2021|Python Video Tutorials|33 Comments

33 Comments

  1. Keith Galli July 17, 2021 at 3:10 pm - Reply

    Hope you all enjoyed! And thanks for sharing FreeCodeCamp! Check out my channel for more Python & Data Science videos 🙂

    Also I mention that a full video timeline is in the comments, that can actually be found under the video description.

  2. q zorn July 17, 2021 at 3:10 pm - Reply

    last time i smashed the button i had to get a new keyboard! Mmmm…:/ thanks a lot and great video…:)

  3. lou Naguez July 17, 2021 at 3:10 pm - Reply

    this was my solution
    one=np.ones(5)
    x=np.asmatrix(one)
    matrix=np.repeat(x,5,axis=0)
    matrix[1:-1,1:-1]=0
    matrix[2,2]=9

  4. achintha isuru July 17, 2021 at 3:10 pm - Reply

    For the part in 35:10,

    It is happening because Lists / Arrays are
    mutable by nature. This means once you created them you cannot change it.
    Do a google search about this, you will find more details.

  5. Epsilonator July 17, 2021 at 3:10 pm - Reply

    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

  6. meher shrishti nigam July 17, 2021 at 3:10 pm - Reply

    a = np.array([[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15],[16,17,18,19,20],[21,22,23,24,25],[26,27,28,29,30]])
    b = np.array([])

    for i in range(4):

    b = np.append(b,a[i,i+1])

    print(b)

    This also worked for the second problem at the end, but the numbers were floats

    [ 2. 8. 14. 20.]

  7. meher shrishti nigam July 17, 2021 at 3:10 pm - Reply

    filedata = np.genfromtxt('data.txt', delimiter=',') is showing "IOError ("%s not found." % path)

    OSError: data.txt not found" for me, I have created a data.txt file in the same folder in which I'm running my python script (using vscode). What am I doing wrong?

  8. meher shrishti nigam July 17, 2021 at 3:10 pm - Reply

    224 bits to store a 5 in a list!?☻

  9. Sneha July 17, 2021 at 3:10 pm - Reply

    Wonderful tutorial! I've shared it to friends

  10. Salman Alsaffar July 17, 2021 at 3:10 pm - Reply

    I am learning numpy but still dont know whats the point with it

  11. Kal July 17, 2021 at 3:10 pm - Reply

    I am gonna burp u like a bby

  12. Vincent Blaze July 17, 2021 at 3:10 pm - Reply

    You could at least try to show some interest. Felt like watching a zombie speak

  13. Announcer July 17, 2021 at 3:10 pm - Reply

    Thanks for everything big man

  14. Mohammed umar Farhan July 17, 2021 at 3:10 pm - Reply

    May God bless you mate

  15. Majid Howsawi July 17, 2021 at 3:10 pm - Reply

    just amazing

  16. suraj gupta July 17, 2021 at 3:10 pm - Reply

    20.50, I, think something is wrong in it.
    [:, 2] = 5 doesn't changed in every row

  17. Bruno Araújo July 17, 2021 at 3:10 pm - Reply

    AWESOME video!!!

  18. Rohan Kandra July 17, 2021 at 3:10 pm - Reply

    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)

  19. Mohan PAKALAPATI July 17, 2021 at 3:10 pm - Reply

    Could you please clarify below points?

    Why NumPy is not having Objective value, I think everything in python is an object?
    Why NumPy doesn't have object type?
    Why NumPy doesn't have references count?
    I think size of NumPy is homogeneous data, it can be int8….

  20. Neethin Nandakumar July 17, 2021 at 3:10 pm - Reply

    The cooking sounds making me hungry :). Great video

  21. Ayush Agrawal July 17, 2021 at 3:10 pm - Reply

    31:50

    q = np.ones((5,5),dtype='int8')

    q[1:4, 1:-1:1],q[2,2] = 0,9

  22. Robert Alvarado Lugo July 17, 2021 at 3:10 pm - Reply

    Thanks sir

  23. S K July 17, 2021 at 3:10 pm - Reply

    Absolute clarity and upto speed. Very comprehensive coverage.

  24. The Soulful Reincarnation July 17, 2021 at 3:10 pm - Reply

    Thank you for the lesson

  25. Александр July 17, 2021 at 3:10 pm - Reply

    Thank you! The only thing was a little bit complicated to me is working with axis. None the less, great tutorial!

  26. YASH LEGEND July 17, 2021 at 3:10 pm - Reply
  27. Cyber Pirate July 17, 2021 at 3:10 pm - Reply

    Watched it in 1.5x Speed lol

  28. Santosh Shriyan July 17, 2021 at 3:10 pm - Reply

    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.

  29. Tony Stark July 17, 2021 at 3:10 pm - Reply

    i figured that this video seems better at speed 1.5x

  30. Vincent Valdinata July 17, 2021 at 3:10 pm - Reply

    THANK YOU SO MUCH

  31. Vaibhavi krishna siva July 17, 2021 at 3:10 pm - Reply

    God own child

  32. Emambucus Sohail July 17, 2021 at 3:10 pm - Reply
  33. AASHI JAIN July 17, 2021 at 3:10 pm - Reply

    Arr=numpy.arr["array",5,5.6]
    What is the dtype of this arr and why??

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