numpy tutorial: iterate numpy array using nditer | numpy nditer

[@codebasics]

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[@ramanak6961]

Your tutorials are Huge asset for the beginners and we are looking forward for more......and your style of mentoring is awesome. Great Job.

[@codebasics]

Ramana I am glad 😊

[@ahmedhelal920]

for the first example , we can use for row in a.flat: print(row) 0 1 2 3 4 5 6 7 8 9 10 11 learned from you on last tutorial 🥰

[@deepthapa5957]

Cant thank you enough sir, really you are doing great job help others for free ,thats very rare nowadays, glad to see persons like you ,it make me to believe that humanity still exists.

[@codebasics]

👍😊

[@notanengineer69]

finally finished the python tutorial, thanks for the easy explanations. im looking forward to the data structures and algorithms tutorial now

[@AbhijeetKumar-qu4lm]

Amazing way of teaching 😍😍 Thanku so much for this all

[@shrutijain1628]

Best numpy tutorial 💯

[@tanoychowdhury6375]

Make more videos on numpy to cover all functions....... your tutorials are really helpful for a beginner.❤

[@DiverseDestinationsDiaries]

Really , it's amazing . the way you're explaining every concept from fundamentals for beginners.

[@codebasics]

Glad to hear that

[@purplecrayon7281]

I understand how using numpy is superior than using lists, but the weakness of numpy seems to be that the shapes of arrays are so important. I would need to make sure that the data need to be made "rectangular/squarish" first by using a calculator (Yes, I'm aware you can make the calculations first using Python).

[@victorlourenco_]

you are amazing, love the effort you put into your videos

[@SulemanTheTraveller]

it's really interesting, just done it with practice

[@dineshkumar-dg9ml]

Completed your Numpy playlist. Wonderful. Easy understandable. Please advise if this is enough. Please post more videos eagerly waiting

[@kenoalbatros]

This tutorial was very well explained, thank you!

[@InformativeVideos423]

Excellent teaching. Superb!!!! Please also do videos on Tensorflow machine learning. I want to save a trained Tensorflow model and then later use it in some another program. How can I do it? help me please

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Sir can you please provide information on django framework

[@ManishSharma-wy2py]

You are great sir , your videos are amazing and awesome way of teaching .

[@codebasics]

😊👍🤓

[@narayanamt9534]

well covered. very helpful. Thank you very much

[@jinkaleo]

straight to the basics....

[@OmkarShelke-w2j]

this tutorial is amazing

[@Muhammad.Kashif31]

Great effort Sir

[@s.baskaravishnu22]

Many thanks for giving code

[@agenesis6761]

I have a specific question about Data frame (i went through your GitHub) library and could not find answer. How to reach you for some more clues on problem around iterating through dataframes and calculating values in 3 dimensional dataframe?

[@surewin3006]

Good tutorials and very helpful. I just completed this whole Python3 programming for beginners. What is your recommendation that i should take next?

[@nikhiljain8411]

Could you please create a video for scikit-learn as well

[@codebasics]

Nikhil I have an entire series on machine leart using scikit-learn. Plz check that playlist on my channel

[@johnjohn-nv9wb]

Good day codebasics,i wanted to ask you,if this video is the complete course for professionals on python or just for beginners course only? if not can you send me the link to a more advanced course on python, please?

[@hichemhadji348]

Hi, please I have a question, you said that the iteration through 2 arrays simultaneously is possible if the arrays have the same shape or if one of the dimentions in one of the arrays is 1 . but it turns out that you have changed the dimentions of the array b of your example from (3,1) to a (4,1) but you had an error although we still have one as dimention greetings from France, your videos are awesome

[@hichemhadji348]

I think that the best answer would be ( if the shapes are equal) or if at least one of the 2 dimentions are equal in both arrays while the other dimention of one of the 2 arrays is equal to 1. please let me know

[@mohammadal-antary9321]

@@hichemhadji348 I do agree with you

[@bhupendrasai4640]

Tq @@hichemhadji348

[@goodester6924]

thanks for the tutorials!

[@inspirational_talkings2099]

Sir can you upload Scipy tutorial videos ??? It would be very much helpful for me....plz sir...... expect a kind reply from you.....

[@inspirational_talkings2099]

Okkk sir.... thank you sir....!!!

[@rhard007]

Hi could you upload a video that explains how the numpy class as_strided works ? I have been stuck on this and haven't been able to find a good descriptions anywhere. Thanks.

[@tejaschaudhari3259]

sir can you please provide links for all quries you teach in lectures. i mean each and every. please

[@ravibatta8921]

nice one

[@mariolinovalencia7776]

Your videos are great

[@roninababan1239]

use zip() function for x,y in zip(a,b): print(x,y)

[@shankarsalesforceseries5196]

Thank you. Good tutorial.

[@mwahmed9519]

Can you make a/some video on AWS ..

[@birendrakumar-gl5gq]

Where to go from here?

[@Imran20091990]

Excellent

[@its_kumar]

Great video 👍

[@codebasics]

Glad you enjoyed it

[@rahuljacob4694]

Sir , should i do Data Structures and algorithms or Data Science with Pandas first?

[@codebasics]

depends on your goal. if you want to become python software engineer than go for data structures etc. if you target data scientist field then do data science with pandas

[@rahuljacob4694]

@@codebasics Ok Sir Thank you

[@ravisonawane6381]

Thank You sir...

[@mehandiyanaaditya]

thank you sir

[@cantanzim6215]

grate videos..... thanks

[@codebasics]

Can Tanzim, I am happy this was helpful to you

[@tsietsimatjele5459]

Awesome......

[@ParthivDesaii]

It would be great if you show how to do iteration (for loop ) without using modules and built-it python functions, instead by applying logical and arithmetic ways.

[@chiliverupavankalyan5051]

Thankyou

[@okenlaqahhar4879]

I mean you just transpose the array and then square each value in the array via vectorized operations. The nditer seems to be extra.

[@maidishahoon]

is this enough ???

[@ankitkumarsingh3717]

Can you provide link to website where i can practice numpy?

[@lakshsinghania]

made with ML lol im replying 4 yrs late

[@selvakd7103]

Hi I saw your tutorial videos its really useful for me . while I am working on numpy i have stuck with one point. i.e., jagged array concept. Is it possible to bring jagged array in numpy ?

[@luiscarlospinheiromarques9258]

great !! very helpfull video!!

[@sabariedits]

Is this enough because you don't teach random in numpy?

[@khanduom9341]

sir, the videos are really help. I have a query regarding reshaping of arrays. For example, if we have input shape of (144,1), we can easily reshape the array by assuming (12x 12 =144 matrix) and then reshape it as x = np.arange (144).reshape (1,12,12). Now my question is : how do we reshape the array if we have input shape of (1048572,1). Please help. ..Thanks

[@bhupendrasai4640]

I think 1024*1024

[@instantlearning3003]

sir I just want to ask that this tutorial is enough for data science.?

[@parveznadvi007]

Hi Deepak, I would say that the information provided in this series is sufficient to start your projects using numpy. While you are working on your project, based on the application, you will come up with algorithms in which you will use multiple numpy functions to work with. At that time you will know that the numpy docs and stack over flow will be your best friends to know more about the functionalities and how you can utilize them to complete your project. Hope this answers your question.

[@hunting5.gammers417]

@@parveznadvi007 she did not ask you..

[@hunting5.gammers417]

mind your own business....

[@hunting5.gammers417]

rascle

[@sauryadeeppal8873]

If i have an array a = np.arange(9).reshape(3, 3) and I define a function such that: def iter_by_row(array): for x in np.nditer(array, order='F'): print(x) But when I do this: print(iter_by_row(a)) My output is: 0 3 6 1 4 7 2 5 8 None Why is the None being printed? Is this normal?

[@gajulanagamani8312]

array=np.arange(9).reshape(3,3) def iter_by_row(array): for x in np.nditer(array, order='F'): print(x) iter_by_row(array) try this one you cannot get none .function already print values but again you call print function for call the iter_by_row(array)

[@al-amin5542]

thank you

[@karthickkumar4941]

thank u so much

[@vamsisaggurthi5528]

Good

[@jeanrodrigues6249]

Ramana

[@gangulreddy7918]

Helpful a lot, thanks much

[@codebasics]

😊😊😊🙏👍

[@thirumala_reddy]

Thank u....