Numpy Tutorial in Hindi
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- Опубликовано: 9 фев 2025
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Like karna mat bhoolna :)
Pandas In one video is coming soon.. Subscribe and hit the bell icon to stay tuned!
QNA
@@safety1610 Bro You are right.
QnA
I can't say how much I am grateful to you after this video. Thanks a lot, bro! 😊 Please cover other important libraries like pandas,matplotlib,scikit-learn,scipy etc.
After this I would request you to deep dive into statistics part pls, else the knowledge gained through data science would be incomplete.
Looking forward to your upcoming videos 👍.☺️
Bhai please make complete tutorial of matplotlib including seaborn please.....
"hum ko sirf numpy hi nahi padhna hai , besically hum ko data science karna hai " ------love this line
waah hero ho boss, itne easy way se samjha diya jisko main 3 din se padh k nahi samajh paya....society needs more heroes like you. Appreciate bhai the efforts you have given. Thanks a lot. :)
cuz he does not touch complex things in any video
@@sunilmaurya6594 bhai to actual numpy bahut details mai hai kya?? please guide karo hum kaha se seeke???
44:56
Function: myar.argsort(axis = 1)
Display: array
([[0, 1, 2],
[0, 1, 2],
[2, 1, 0]], dtype=int64)
Functionality: it will display the indexes of the values from the original array and sort the values
07:03 Numpy gives efficient storage and ready-made functions for data analysis.
14:06 Using Jupyter Notebook and Numpy
21:09 Learned about creating numpy arrays using python objects
28:12 Creating numpy arrays from Python structures and using intrinsic numpy array creation objects
35:15 Numpy array creation methods and reshaping
42:18 Understanding numpy arrays and axis
49:21 Using arg sort and axis to sort 2D arrays
56:18 NumPy arrays take less space compared to Python arrays.
Thanks, bro this is what I was looking for.
Is this video still worth it ? If I started now in 2024
@@ankitmondal1236 for data science its basic introduction not full
saviour bro thanks
44:42 --> 'argsort()' may be used to find the index of all the elements of a sorted array of any dimension. for a 2d array, we have to specify the axis whose elements we want to sort
no it's not necessary to specify axis for a 2d array when using argsoft()
44:58, I feel that the argsort(axis=0) when applied to the 2D array, shows the indices sorted with respect to the vertical directions and the axis=1 shows induced sorted wrt the horizontal direction :)
sahi hai, vo harry bhaiya kabhi kabhi galti se bol dete hai shayad. Mai bhi output dekh kar hi samjha
nahi vo sah =i bol rha hai, phir se check karo, axis =0 along the rows and across the columns
Please make a series on chatbot with AI and Deep learning
Hmm
Yes
hmmmmm...plzzz
plz sir from first to last
code with harry can we do visiluation in numpy
44:54
We want an argsort of axis 1, so as we all know that axis one goes from left to right hence when the first whole column will be an axis of when axis 1 is concerned, hence if we try to sort it we will come to know that all the elements are already sorted, so it will yield and answer as [0,1,2].
Wow, I can't believe I understood numpy so easily in 1 day. Your teaching style is so amazing, Harry sir. Hats off to you. Going to learn pandas next.
Keep up the good work you're doing, you don't know how many students you actually help everyday.
dont forget to practice
@@hum4424 from where to do ? do u have resources ?if yes pls do share it here
Which designation you are going for ?
Like I like AI and my bhaiya told me to do learn NumPy, Pandas, Matllotlib, Sci...
Will you Plz tell me that in which order should I learn the above libraries???
45:13 arg.sort() it works by default rows wise and if we give it axis =0 . then it work vertically every column and if we give axis = 0 then it work horizantally
44:58 in axis = 0 it tells us where the required elements are w.r.t vertical axis for them to be sorted in ascending order vertically
In axis = 1 it is considered horizontally
Thankyou so much Harry Bhaiya, ye video mere liye kaffi helpful thi😍😍😍😍
There are 6 general mechanisms for creating arrays:
-Conversion from other Python structures (i.e. lists and tuples)
-Intrinsic NumPy array creation functions (e.g. arange, ones, zeros, etc.)
-Replicating, joining, or mutating existing arrays
-Reading arrays from disk, either from standard or custom formats
-Creating arrays from raw bytes through the use of strings or buffers
-Use of special library functions (e.g., random)
there are only 5
Based on latest info it is 6 @@utkarshbharti7274
Sir please Do QNA 🙏🙏🙏
44:30
As you have given (axis=1) as argument for argsort it will sort elements with respect to in horizontal axis.
I was not knowing that its so easy to handle NumPy and pandas...Kudos to COde Master Mr.Harry.....I know that you but still I wanna tell, you are providing occupation to a family.....which is so kind....HATTSSS OFFF to this master....We all love you....😍
Do we have notes of pandas and numpy?
good teacher
ar.argsort(axis=1) gives the given 2D array in ascending order for all rows. [ [1,2,3] , [4,5,6] , [0,1,7] ]
Harry Brother kesay shukriya kaho aap ko ....
Auesome Understanding of Numpy in just one hour......
Hats off.... Love from Pakistan❤❤❤
Anyone in 2025
Extremely good work. Cut to cut & point to point tutorial. We liked it. Please make some videos on Panada and Scipy. Keep it up :-)
Pandas is already uploaded and scipy is coming soon. Thanks for your love and support!
right
@@ruchiagarwal4943hi
I am here now after 100 days of python course and now i move further to machine learning
🍑🍑💦
thank you harry bhai mene aapke python ke pure 123 video dheke and numpy bhi appne bahut achi and simple tareke se sikayeye hai. your way of teaching, so laveable :)
dear sir, this is only one video I proper clear numpy thanks sir for your videos and you are the best teacher on youtube.
thank u so much harry bhai...
it means a lot...
Please make video on tensorflow, keras, matplotlib, pandas, scipy modules.
bro jupiter ki jagah vs code use kar sakte hai
@@sumitrawat6493 Haa bhai kar sakte hain 👍
What is the difference between methods and attributes?
Also SymPy
@@amanshukla270 methods are functions and attributes are variables (in classes ) . You can think like that
For 44:50 , ar.argsort(axis=1) will give us the indices by which we can sort our numpy 2d array elements column-wise
Rowise
wha bhaia maza aa gaya numpy sekh ke apke sath....
Such a great Explanation of Numpy, I have understood alots of things through this video.
So thanks alot♥️.
Thank you गुरु जी❤
Such a great introduction tutorial on numpy. Got a clarity finally. Keep up the hardwork harry❤
Argsort(axis=0)..per pehle ek column ko sbse choti value ke index ko pehle fir usse bdi value ke index ....isi tarah ek column ko poora krta h ..fir doore column me same process...
Argsort(axis=1)per pehle wale row ke sbse choti value ke index ko pehle use baad usse bdi wali value ke index ko ...aur fir last me sbse bdi wali value ke index ko btaya h ...aur isi tarike jitne bhi matrix me row honge unko sort krega .😊
Wow, numpy in 50 mins! Will look forward for pandas video.
GREAT WORK
ar.argsort(axis=1) - gives the element position to sort the array for column, horizontally in asc
ar.argsort(axis=0) - gives the element position to sort the array for rows, vertically in asc
I know its confusing since axis=0 is row and axis=1 is column
44:42 -> what argsort() does is it returns the indices of the array's elements in the ascending order depending upon the axis that has been assigned to it.
Hey, thank you, Harry, I am started following your videos from the last 3-4 months What a content you created for free of cost you deserve a big Applause 👏 👏
💦💦💦
@44:58 about ar.argsort(axis=0)
we know that argsort method sorts the elements in a way that we can make out which element is lower or greater in the manner of 0 1 2 indexes, so when we execute it for every 0 axis we will be getting columns sorted out, so eventually the output will be
([[0, 2, 2],
[1, 0, 0],
[2, 1, 1]]
array([[1, 2, 3],
[4, 5, 6],
[7, 1, 0]])
argsort(axis=0) shouldn't be like array([[0, 1, 1],
[1, 2, 2],
[2, 0, 0]])
because for the 2nd and 3 rd column the largest number are present at index 1 [2, 3],
[5, 6],
[ 1, 0]
Argsort arranges the indices of elements in increasing order of element value. Depending on the axis, it works like...for axis 0 it sorts every column individually and for axis 1 it sorts the rows individually.
This is the best 56 minutes ever invested. Great vid awesome tutorial. 56:01
You are just Amazing Harry........Thanks aton for teaching Numpy in simplest way possible......Learned a lot on Numpy.......Thanks bro
Great video. For ppl who know how to install jupyter and basics of it can skip the video to 15:00
ar.argsort(axis = 1)
array ([0,1,2]
[0,1,2]
[2,1,0])
2 = 3
2 = 6
0 = 7
it represents ascending value in every row (horizontally)...
Hi, your vedio's are leaner friendly, but if you could prounce numerical numbers in English,then its more convenient for Non-hindi students,great going!
Thank you very much for this course!!!
Your teaching style is too good thus all beginner type stude prefer you ❤
Love from Satyam Rocker
ar.argsort(axis=0)
This will give us the index to sort the array column-wise, vertically.
Harry Bhai thanks alot. Ur videos helped me alot, Dil se sukriya❤️
Thank u 😘 so much 💕 sir 🙏
Brother you're great. You're helping many who can't learn these concept easily. I watched your both videos on numpy and pandas, again thanks a ton. Harry 😊
Me toooo bhai
Your tutorials are just awesome it really helps us a lot
very well explained bhaia😄
thank u so much for teaching in a layman language
Thank you Harry Bhai 😊😊🤍🤍🤍🤍
You are the best for me.✨✨✨
you have cleared all my doubts regarding numpy. thankyou!
For 48:48 in np.where(ar>5)
(array ([1,2]), array([2,0])
As I understood you mean there are 2 tuples (1,2) and (2,0) which shows the index of items greater that 5.
But I think this two tuples are not for 2 index of 2 elements rather it is index of X and Y axis of all the elements greater than 5.
Pls correct me if I am wrong.
you are right bro . i was very confused but your comment gave me relief . thanks a lot
Argsort(axis=0)..this provide the sorted position of the value of axis 0...like if axis 0 has some numbers like 4,2,7..then argsort will provide the following position 1,0,2..
aapke sabhi vdeos full of content h.all video are liberary of knowledge.
This Video is helpful for me and i am an Aspiring for data scientist
i understand 75% percentage of this lecture and i also make notes of this
your video are amazing Thank you bhaiya
Hey I also want to learn data science , Can you pls tell me which is the best source to learn data science
@gourav7921 yeah sure
bohor barhiya re Harry bhai, bohot barhiya samjaya aapne
Easy to understand for IT Or Non- IT people's. 😊
argsort(); Basically Sort the array according to indexes ... if you put (axis=0) then it will give you that indexes which are sort for top to bottom and if you put (axis=1) then it will give you that indexes which are sort for right to left respectively.
Harry bhai dil se THANK YOU!!!
Superb introduction to NumPy topic... Thanks for the tutorial..! :)
Kya baat hein , Your basics are so clear . I always will refer to your videos in future for Python
its very helpful for me for my NumPy Quiz test
thanks bro
Bhai mza aa gya, itna acha sa samaj aa gya, kal viva ha 😭🙏
I have completed Numpy Tutorial
Thanks Harry!!
Thankyou Harry bhai. Helped me a lot
Learned alot of basics from this short video
ar.argsort(axis=1) will return a matrix of same order with sorter indices on axis one. This will tell us the indices of min to max element of the row
for example;
[
[4,5,6],
[8,22,1],
[100,23,1]
]
will result in
[[0,1,2],
[1,2,0],
[2,1,0]]
Wonderful Explanation 🔥👏💖
Thanks alot brother.. god bless you
very easy explanation! Really apprectiate this
You are the badshah of coding... resemblance to The rapper
I learn Python, JavaScript, C# and am learning more from your channel.
Thank you yar harry bhai aap bahut achchha padhate ho❤️
Your teaching is very amazing
Harry Bhai Jindaabaad 😍😍😍 always Follow you
Thank you soo much harry!!!
Big hug!🤗❤️
Thank you so much sir for your efforts and nice video😍😄
You are great. Bestcoder in you tube
Argsort is used to arrange elements from ascending to descending order in 2D array and when axis = 0 , it is according to vertical direction and when axis = 1,it is according to horizontal direction.
Sir Thankyou very much your videos
helps so much to learn python.Numpy library aache se understand
ho gayi he.
Him 4 yrs back >>> new creators ❤🔥
ar.argsort(axis=1)
# for axis =1 it will sort the array by the column
ar.argsort(axis=0)
# for axis = 0 it will give the index of the maximum element in each row
treko boht pta h
argsort simply arrange the element indices in ascending order.
like argsort(axis =0) means it will simply arrange element indices in ascending order column wise.
argsort(axis = 1) works as row wise.
at 45:30 in axis = 0 it gives matrix of indicies to sort the given matrix wrt to rows..... and vice versa for axis = 1
The argsort(axis=0) works on columns if we look at the column no1 then the smallest is at index 0, the middlest as at index 1 and the largest is at index 2 so it become 0,1,2 and in column 2 : the smallest is at index 2, the middlest is at index 0 and the largest is at index 1 so it become 2,0,1..so like this we have to write the index of the smallest number to largest in a column (from smallest to largest )
Thank you Harry bhai. ❤️
Thanks for your lucid explanation...
Thank you harry bro, for such a explanatory tutorial, please publish more content on Data science for self learning
.argsort() function gives the order in which a given array must be arranged for ascending order, it returns the index number of elements present in an array.
bro jupiter ki jagah vs code use kar sakte hai
Bhai Thank You Thank You
.
Please make a series on chatbot with AI and Deep learning.............
Thankyou, Harry Bhai
Tkinter ✔️
Numpy ✔️
Dil maange more....
argsort(axis=0)
It tells the indexes of 2D array in sorted order for vertical matrices. But argsort(axis=1) tells the sorted indexes of arrays in horizontal matrices of an array.
Harry bhai you are the best❤️
Nyc teaching technique bro....
Loved it!! thanks :)
U r phenomenol bhaia thank you so much for doing such a hard work for us. Hit the like if like the video yaha nhi kroge to chalega pr upr jarur like👍 krna
yes right