NumPy Python Tutorial - Part 1 | NumPy and Pandas Tutorial | NumPy Tutorial | NumPy Introduction

NumPy Python Tutorial - Part 1 | NumPy and Pandas Tutorial | NumPy Tutorial | NumPy
Hello and welcome to NumPy python tutorial powered by Acadgild. Let’s start with NumPy basics.
There are basic libraries which are really important for the data manipulation. So, first is ‘NumPy’ that is nothing but numeric python and then there is ‘pandas’ and then there is ‘scipy’.
So, these three are the basic libraries which are very important for you to learn and these two things are very related the NumPy and pandas they are the core structure to handle the data. So, you need to understand NumPy and pandas when you are going to deal with the data.
What is NumPy?
NumPy is nothing but provides all the libraries to deal with the linear algebra.
• NumPy, which stands for Numerical Python
• NumPy is the foundational package for mathematical computing
• Mathematical and logical operations on arrays
• Operations related to linear algebra. NumPy has inbuilt functions for linear algebra and random generation
• ndarray is the core object in NumPy
Basics ndarray
• Multidimensional array
• Homogeneous collection of values
• Fast and efficient
• Support for mathematical functions
• Primary container for data exchange between python algorithms
Important attributes of an ndarray object are:

#numpy, #numpytutorial, #pythontutorial, #numpypandas

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[keshavramaiah]

Is a very good video for data science beginners

[laynepa]

I love this content. Unfortunately, around minute 19 the edges of the screen become whited out. I still gave you a like, because this video is very helpful, but in order to follow along it would be nice to see your whole screen.

[milan]

Good content but consider getting a pop filter for your microphone

[makeoutloud]

provide this whole file in description so that we can study it later also.

[himanshushekhar]

I have one doubt acadglid, Why giving dtype create below difference ?
multiDimArray = [('Him', 26, 1234), ('shek', 27, 4567), ('bruce', 28, 7896)]
mdArray = np.array(multiDimArray, dtype=[('name', '<U11'), ('age', 'int32'), ('salary', '<f4')])

// output = [('Him', 26, 1234.) ('shek', 27, 4567.) ('bruce', 28, 7896.)]
//size: 3 and shape (3, )
mdArray1 = np.array(multiDimArray)
// output = [['Him' '26' '1234']

['shek' '27' '4567']

['bruce' '28' '7896']]

// size: 9 and shape (3, 3)

[falolayusuf]

can we get the a copy of the notebook for the class? Thanks

[AI_CANISTER]

please sir, next time try to improve the quality of the sound

[jessysheen]

Nice video but the audio is so disturbed

[makeoutloud]

screen is shifted not able to see from 20 min

[pisaupisau]

Generally good, but too many uses of the word "things" rather than the proper words. If only matrix multiplication were as simple as multiplying this thing with that thing and that thing with this other thing...