Tutorial 4 - Numpy and Inbuilt Functions Tutorial

[@rajashekarbarapata1764]

Who want to clap for this man👏👏

[@AdvDevraj]

👏🏻👏🏻👏🏻👏🏻

[@priyankapatel6803]

👍👍👏

[@priyankapatel6803]

Thank you very much sir, pl. keep sharing your knowledge, so useful..for everyone..God bless you.

[@swatikashyap717]

Rajashekar Barapata he's the best ! I have improved greatly!

[@ASNPersonal]

I have improved my index concept gratly

[@manojsupyal1912]

Q1-If I pick up 4,5 from 2nd row And 6,8 from third row than In. is Arr[1: , 2:4] Q2-Pick up 3,4,5 from 2nd row than In. is Arr[1:2,1:4] Thank you so much sir.

[@sagarmishra3517]

Hello Krish, I am obliged to take time and express my gratitude towards your efforts and teaching method. I am watching your tutorials since yesterday, and I just so happy to learn and actually understand everything. I am looking forward to follow the playlist, and excited to learn. Thanks man, you deserve our respect and the money as well, I will be joining your membership. I will request all the people who are reading my comment to consider joining the membership to help him grow❣

[@sanjaykothari2597]

What membership ?

[@parththakurdesai809]

Thank you soo much Krish. I am recommending your channel to all my friends. I really like your genuine teaching passion. I learn a lot from all your videos. Thanks for being a mentor.

[@srajat]

Bro! You're helping us all a lot! Proud of you! An Indian teaching everything in depth. Thanks so so much. Keep up the good work. Looking forward to pandas tutorial too. 🤘🏻🤘🏻🤘🏻

[@ShivamSingh-kn3gz]

For the subarray 4, 5, 6, 8 code is: arr[1: , 2: 4] For the subarray 3, 4, 5 code is: arr[1, 1: 4]. I started your session, sir, really your contents are truly valuable. Thanks for making this all happen. I wanna learn as best as possible about the concept of Machine Learning. Really glad that I found your channel at the time when I was in its complete need. Thank you soo much, sir

[@yeshjadhav8082]

For sub array 3,4,5 it can be arr[1:2,1:4]

[@54mu33le]

Absolutely great content being put here by this man. I wish there were more teachers like him across different domains. What a stupendous job he is doing here.

[@farazahmed1668]

I never thought understanding the prerequisite of machine learning is that much easy and Krish sir you make it alot easier.

[@ShubhamKumar-nr1ce]

hello sir what are you doing now means which domain

[@farazahmed1668]

@@ShubhamKumar-nr1ce i am learning FastAPI and the future plan is to learn react and follow panaverse GitHub repository to learn the complete ecosystem of modern python and generative ai.

[@sathiyaraj5704]

I started watching this playlist today after knowing the learning path from your yesterday's video. thanks a lot

[@tintintintin576]

How far you've reached...? Just asking out of curiosity...

[@sathiyaraj5704]

@@tintintintin576 At that time i was unaware of GATE exam and the brand value of doing masters in IIT. It all depends on individual's choice. We all love to work in latest technologies in top notch companies and we even learn everything out of curiosity forgetting the easiest path to reach there is to have CS foundation strong and doing m.tech in IIT.

[@uditarora1215]

Hey @SATHIYA RAJ can u help me pls in learning data science in python as I am complete fresher can u pls get in touch through telegram or discord . Also I am new to his channel I am planning to access all its content and side by side a mentor and a friend 🙏

[@sathiyaraj5704]

@@uditarora1215 i am also a fresher. After gate exam on feb 13, i have started again learning data science full fledged. lets do it together.

[@laksh._.official]

Did you become a data scientist or analyst yet?🧐

[@archanaashok1980]

Hi Krish, Python is made so simple to learn from you. Always had difficulty in understanding and remembering from other tutors. Never felt it so easy and enjoyable to learn. Thank you for your efforts.

[@zahabiyarangwala1808]

Honestly glad to have come across your channel and it brings in humungous value to the folks trying to learn. You are truly the best. You make commendable efforts and as a part of the learning community, I hold enormous respect for your contribution in helping us. (y)

[@BHANU693]

Following are taught in video: -Array definition - Numpy library import - Array Shape and Reshape - Array indexing - Array Range - Array linspace - Array copy and broadcasting - some functions in Array like np.ones, np.random.rand (random distribution), np.random.randn (normal distribution), np.random.randint etc.

[@bishalgupta49]

This is the first video of your channel that i got recommended and man i loved it . Thanks for sharing.

[@xeno_plays2930]

For accessing 4,5,6,8 answer is arr[1: , 2:4] and for accessing 3,4,5 answer will be arr[1:2,1:4]

[@lauraprado5916]

arr[1:3,2:4] = array([[4, 5], [6, 8]]) Thank you Krish! I am following your path to become a Data scientist

[@ravikhandsiya1238]

Thank you Krish Naik for teaching us by this much of patience. You have cleared so many of my doubts.

[@gulabmeetyou]

EAGERLY EXPECTING Scikit learn and PLOTLY tutorials. No one has taught about Plotly... If you make this it would be great....

[@Anupkumar-xv3vd]

print(arr[1:,2:4]) print(arr[1:2,1:4])

[@sharvandas4349]

*Numpy *Array 1.Creating One Dimensional array. 2.Creating Two Dimensional array. 3.Shape, reshape and indexing(slicing) done in two dimensional. 4.In-built function present in numpy- arange, linspace, ones, random.(and more) 5.Concept of copy and Exploratory data analysis Please share the list built-in functions of numpy. Thanks

[@balusister1991]

Hi Krish, great effort. But i request you to improve the audio quality. Audio quality is not so good to follow the recording. thank you.

[@hasibkazi1379]

this is one of the best playlist for learning python for data science, can you please tell me how can I practice without anaconda environment? As my PC does not support the environment.

[@styles4330]

Here are the functions mentioned in the video with examples: * Creating arrays: * `np.array()`: This function is used to create arrays from various data types like lists, tuples, etc. For example, `np.array([1, 2, 3, 4, 5])` creates a one-dimensional array with elements 1, 2, 3, 4, and 5. * `np.zeros()`: This function creates an array filled with zeros. For example, `np.zeros((3, 4))` creates a two-dimensional array with 3 rows and 4 columns, all filled with zeros. * `np.ones()`: This function creates an array filled with ones. For example, `np.ones((2, 2))` creates a two-dimensional array with 2 rows and 2 columns, all filled with ones. * `np.random.rand()`: This function creates an array filled with random floats between 0 and 1. For example, `np.random.rand(2, 3)` creates a two-dimensional array with 2 rows and 3 columns, filled with random floats between 0 and 1. * `np.random.randn()`: This function creates an array filled with random samples from the standard normal distribution. For example, `np.random.randn(3, 3)` creates a two-dimensional array with 3 rows and 3 columns, filled with random samples from the standard normal distribution. * Indexing and slicing: * `[]`: This operator is used to access elements of an array. For example, `arr[0]` accesses the first element of the array `arr`. * `[:, :]`: This is used to access all elements of an array. For example, `arr[:, :]` accesses all elements of the array `arr`. * `[start:stop:step]`: This is used to slice an array. For example, `arr[1:4:2]` selects elements from index 1 to index 4 (excluding index 4) with a step of 2. * Mathematical operations: * `+`, `-`, `*`, `/`: These operators are used to perform basic arithmetic operations on arrays element-wise. For example, `arr1 + arr2` adds the corresponding elements of arrays `arr1` and `arr2`. * `x * arr`: This multiplies each element of the array `arr` by the scalar `x`. * `arr.shape`: This attribute returns the shape of the array as a tuple of integers. For example, `arr.shape` might return `(3, 4)`, indicating that the array has 3 rows and 4 columns. * Reshaping: * `np.reshape()`: This function is used to reshape an array into a new shape. For example, `np.reshape(arr, (2, 6))` reshapes the array `arr` into a two-dimensional array with 2 rows and 6 columns. * Other functions: * `np.dot()`: This function is used to perform dot product or matrix multiplication between arrays. * `np.sum()`: This function is used to calculate the sum of all elements in an array. * `np.mean()`: This function is used to calculate the mean of all elements in an array. These are just a few of the many functions available in NumPy. I hope this helps! -courtesy:GeminiAI

[@farazahmed1668]

His explanation is clear and everything is practical.

[@tahabimuhammad4524]

Thanks for the videos. One change : Here, even if the elements are of not same data type, arrays can be created. So, they need not be of same data type. import numpy as np my_lst1=[1,2,3,'sdfs',5] my_lst2=[2,3,4,5,6] my_lst3=[9,7,'wow',8,9] arr=np.array([my_lst1,my_lst2,my_lst3]) print(arr)

[@krishnaik06]

Yes it can be created..but the array should have common datatypes elements

[@shreyshah7133]

Goat of Python bro, learned 3 months work in 3 lectures.

[@pratappawar8899]

hi, how is this course?

[@shreyshah7133]

@@pratappawar8899 He explains every concept in detail with examples. I also just started watching a few weeks back.

[@pratappawar8899]

@@shreyshah7133 what other courses did u watch, which u recommend?

[@rusteze4710]

Excited to watch more tutorials on deployment

[@kornelies]

Hi..In[105] -( val=2)..in this case we take "val" to do the operations like...arr*val, arr>val,.......correct me if i am wrong..Thank you Krish for your valuable teaching

[@Virus-ke8xj]

Just 3 videos into and you made it really interesting ❤️❤️🙏🙏🙏

[@RajeshMaallah]

How do I query if column 2 is grater than column 1 in three dimensional arry? [(2,3,4),(1,4,6)] check if 3>2 & 4>1

[@RajeshMaallah]

Array[:, 0

[@AInamedMia]

What is the difference between arrays with the following shapes: (x,) and (x,1) Aren't both the same, i.e. an 1D array?

[@AInamedMia]

My bad, should have searched first. Found it: stackoverflow.com/questions/38402227/numpy-why-is-there-a-difference-between-x-1-and-x-dimensionality Concise explanation for those who are interested: (x,) is a 1D array (x,1) is a 2D array (!), the length of it's second element is 1. Also, Numpy does not have vectors or matrices, only n-dimensional arrays. That helps understand this better.

[@jn9281]

First of all thank u so much for amazing tutorials on python. I have a question. When I do this, my_lst=[1,2,3,4] arr=np.array([my_lst]) arr The output comes as array([[1,2,34]]) Is it two dimensional then?

[@wajahatali4828]

Yes you are wrapping the my_list inside another list (using [ ]) in the line np.array. So it will create a 2d array with 1 row and 4 columns.

[@AnkitaHankare]

@@wajahatali4828 But if I do like this arr=np.array(my_lst) then output is [1 2 3 4] that means this is not 2D array?

[@anvayawalgaonkar4119]

great explanation!!! if I cover all these concepts I will be data scientist within couple of months: Absolute best explanation..

[@manavshah2119]

Sir Thank you so much your playlist is very used full and it was very fast unsersting.

[@user-pj8lk9ii6n]

#slice operation to print only [3,4,5] in second row arr[1:2,1:4]

[@arandomwho]

thank you again....i gonna finish your amazing course in a week

[@aditigupta596]

Highly insightful

[@kesshie07]

Hi, for assignment @14:23... 1. arr[1:,2:4] & 2. arr[1,1:4]

[@Cricketpracticevideoarchive]

Hi Krish, I want to enrol in the course but I am not able to open the google form. Could you please help me out. Thanks Priyadarshi

[@avinashtripathi3692]

while creating a dimensional array, why does the shape indicates (5,0) and why not (1,5)?

[@sapnaSingh-gk9nq]

(r,c) where r is rows and c is columns so it'll show you first no of rows and then columns

[@vysakhkailas940]

wow Sir. Love all your videos. Thank you !!

[@farazahmed1668]

I understand this chapter of numpy in 3 days there are lot to learn in 26 minutes.

[@Suraj-mj2jo]

Assignment - array[1:,2:4] array[1:2,1:4]

[@prithvivasanth3114]

correct!

[@SiddheshShankarBtech]

or the second assignement will work with this too: array[1,1:4]

[@SiddheshShankarBtech]

or the second assignement will work with this too: array[1,1:4]

[@ParvathyAjith-y7k]

hi Krish, What's the difference between random.rand and random.random_sample ? btw, these lectures are super helpful!! Thank you so much for this

[@mohitaggarwal7971]

hello sir i am getting an error " module 'numpy' has no attribute 'arrange'". how this is to be resolved??

[@gayatripraharshitaprabhala2447]

should be arange()

[@deepaksarvepalli2344]

Remove one r...... arange

[@manateluguabbaiinuk-mahanu761]

arr[1:2, 1:4] output: array([[3, 4, 5]])

[@striders5473]

I have a request to make : if you could provide a mind map of the things that we are learning in numpy, pandas, matplotlib and other python libraries that we are going to learn that would be really helpful.....getting to know all the things that we have to learn will be better for better understanding and remembering also. looking forward to your reply.

[@sanjaykothari2597]

Have u made one ?

[@omprakashacharya3810]

print(arr[1:,3:]) print("-----Asssiment Tasks 1----") print(arr[1:,2:4]) print("-----Asssiment Tasks 2----") print(arr[1,1:4])

[@poojakukreti8618]

array of 45 68 ----- arr[1:,2:4] array of 345 ----- arr[1,1:4]

[@banimohammad8276]

your explanation is very good

[@ramakant1963]

solution for the excercise - arr[1:,2:4]

[@sandeeppal1083]

Hi Krish, if the first list has 3 elements, 2nd has 4 elements and 3rd has 5 elements then still NumPy can create a multidimensional array?

[@sandipansarkar9211]

Very nice explanation .Thanks

[@sapnaSingh-gk9nq]

Answer to print 1.) 3,4,5 @14:20 arr1[1:2,1:4 ] 2.) 4,5 and 6,8 arr1[1: , 2:4]

[@namanrungta144]

for indexing... arr[1:,2:4] arr[1:2,1:4]

[@learn_with_rudraa]

time: 14:30 assigment asn: array[1:,2:4]

[@_itz_pk]

New threads comes in :5: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray. arr=np.array([lst1,lst2,lst3]) this want work anymore

[@Arceus948]

Sir i have exam tomorrow, r these numpy functions sufficient for my exam???

[@tanmaydigraskar7156]

Hii Krish I am confused in .copy() concept

[@manateluguabbaiinuk-mahanu761]

arr[1:3, 2:4] array([[4, 5], [6, 8]])

[@asprihashrivastava7548]

I have a confusion.. when we execute copy() function and print arr and arr1 then why is the space difference between the two array?

[@Arun-rm5bb]

i havent studied statistics can i complete python playlist then move to statistics or have to compalsary study statistics first ?

[@artifiedai8898]

Hello, How can We select 1st and 3rd row and 2nd and 4th column. Is it possible using numpy?

[@bhushanmali7635]

18.07 when we print "arr" the output array is comma seperated but when we print "arr1" output is space seperated.. why? when we use linspace the array is of shape 10 rows and 5 columns .. why? and why not 25 rows and 2 column or other?

[@pavanvg5141]

Sir can you please do project on mechanical engineering domain??

[@saiphani3999]

arr = [1, 2, 3, 4, 5, 6, 7, 8, 9] arr1 = arr.copy() arr1[3:] = 67 print(arr1) for this code i'm getting errory , i replaced it with [67] the out put is only [1,2,3,67] how can i get all the remaining values as 67

[@swatikashyap717]

Hello sir. Can you please create a video where you can guide us through the index and order on how to watch your videos ? I am facing a lot of problems in this regard. Thanks!👍

[@mominmaqbul6538]

hi mam

[@harish00784]

arr1[1:,2:4] for [4,5,6,8] and arr1[1:2,1:4] for [3,4,5]

[@amitsaxena6530]

Are you also preparing for UPSC at the same time? :)

[@badrinathansathiyamurthy8390]

Why this Question Bhai..

[@amitsaxena6530]

@@badrinathansathiyamurthy8390 haha..you should observe the screen while watching his videos Bhai...:)

[@rishabhgupta9846]

Is there any WhatsApp group or website or something similar where we can ask doubt regarding Machine Learning? Please tell me

[@venkataduri5790]

I am not able select multiple cells using shift+Down arrow or shift+J. Help will be appreciated.

[@venkateswarareddypusapati4310]

Hi,please make a video on pandas,scipy. Thanks

[@simplyanup9658]

But when I was trying to insert different data type into an array , it is accepting

[@NKATRUKUSUMANADH]

hello,sir,,is this concept of numpy enough to go through machine learning

[@shubhamchaudhary7322]

done...heading to video number 8 :)

[@yogoai136]

Krish if [0:2,:] means it needs to retrieve all three rows right? But in this tutorial we are getting only first two rows as output . how? shall you kindly explain?

[@saurabhyadav-nu3mj]

it means start from the 0th row until 2nd row i.e do not include 2nd row

[@sonasingh131]

audio quality is bad sir, could you please fix it for upcoming videos, thank you!

[@gulabmeetyou]

1. arr[1:, 2:4] 2. arr[1, 1:4] Is this answer right for your question?

[@krishnaik06]

Yup

[@SudheerKumar-tp8rz]

1.arr[1:,2:4] 2. arr[1:2,1:4] Is second one is correct or not?

[@ravikhandsiya1238]

@@SudheerKumar-tp8rz I think second one would not be considered as correct of Gul's answer, because the answer should be in 2 dim.

[@SB-fs4vi]

Thanks Krish for these videos👏.I am a beginner in python and from bio science background.I am using pycharm for coding and found differences in syntaxes in pycharm than jupiter notebook.Why it is like that?kindly reply.

[@MrShree370]

the diffrences will always be there, Just get your basics clear about the syntax and how the data should be approached. you can use either of them depending upon your requirements.

[@SB-fs4vi]

@@MrShree370 Many thanks for the advice🙏

[@journeyofengineerjoe7386]

14:25 [1:,2:4] [1:,1:4]

[@venkatratnamratnam2716]

Bro I find your tutorials are so good and useful. I have a question where to start...?. There are lot of video playlists like stats,Ml,python...Please suggest me to learn data science as a beginner ,first i have to go through stats or Machine learning...please suggest bro,

[@krishnaik06]

Start with my complete ML playlist

[@venkatratnamratnam2716]

@@krishnaik06 I started with this bro but here in this video u said to watch Stats ,so i am a bit confused..whats first stats or ML

[@parikshitrajpara5706]

did you find how to start DS?

[@snehithoddula7905]

@@krishnaik06 import sympy as sp import numpy as np l1=[2,3,5,7] a=np.array(l1) print(type(a[1])) print(sp.isprime(i for i in a)) why doesn't this programme giving me correct output? how to check any array has prime NUMBERS using sympy methods?

[@abdulmoizasif3930]

Awesome

[@einstein007able]

Hey we're is the course curriculum details which I saw below one of ur videos. Also experience error in enrolling in ur course.

[@krishnaik06]

Online platform will be created. Dont worry it will be shared

[@ypvaralakshmi4885]

Sir, I want to enroll to this course. Please let me know how I can join this..

[@jimbujaddu9602]

Hey could u explain the diff between : ar[[1,2]] [[3,4]] & ar[[1,2],[1,3]]

[@priya3677]

sir what is the difference between range () and arange()

[@aamnasuhail4468]

Done and Implemented !!

[@HelloWorld40408]

Thank you

[@ROLLNUMBERDS-MY-3067]

can we copy or replace number with srting vaue

[@hv3300]

How can we check i Numpy is installed ? Numpy --version ?

[@someonesomebody716]

To check list of packages installed: pip3 list

[@nagendrababuavula6629]

U can go anakonda prompt in that pip install < package name> now you can get the package make sure u r PC must be connected to internet

[@hv3300]

@@nagendrababuavula6629 Thanks .It worked on Dos prompt as well as on Anaconda prompt.

[@prabhakaranandbikku]

Sir how to access private video

[@lokeshvenkatesan2693]

I have one doubt np.arrange output not showing as 2 Dimensional brackets. Anyone?

[@madhavimishra7943]

sir can u plz help me..mai Pychm use kr rhe hu bt use me numpy import error show kr rha..mai google kiya kuch nhi mila information ki kaise thik kru..bs yahi bol rhe h problem aati h so plz help

[@sanjeevashoka7948]

Thanks a lot Sir ,

[@malladipavankalyan2767]

Hi all , is it easy to go directly to libraries than of inbuilt DS and functions concept , someone ans

[@ArunKumar-sg6jf]

Which type of mathematics is needed for ml

[@shijithsasidharan8436]

print(ar[1:,2:4]) print(ar[1:2,1:4])

[@Raveendr1191]

mylisy=[1,2,3,4,5] arr=np.array(mylisy) arr=np.array(mylisy) -->o/p:-(5,) means 5 columns 0 rows[first column ,second rows] where as myarray1=[1,2,3,4] myarray2=[5,6,7,8] myarray3=[9,8,7,6] arr2=np.array([myarray1,myarray2,myarray3]) arr2.shape -->o/p:-(3, 4) here first rows (3) and then 4 (column) why both time o/p not same ? it should be (row, column )or (column , row )

[@harish00784]

arr4[3:]=500. Copy and broadcasting didn't work. TypeError: can only assign an iterable

[@shalupriya8219]

same error, did you find a way to fix it?

[@ajaxaj8470]

Guys, watch this playlist as well for Numpy revision kzbin.info/www/bejne/hIe3iJ2alLqjsK8

[@manojkumaar8221]

Arr[1:, 2:4] and arr[1,1:4]