Numpy python

NumPy is a Python library used for working with arrays.

It also has functions for working in domain of linear algebra, fourier transform, and matrices.

NumPy was created in 2005 by Travis Oliphant. It is an open source project and you can use it freely.

NumPy stands for Numerical Python.

In this video, join Aryan as we delve into the fascinating world of Python's Numpy! From its powerful array-processing capabilities to its vast range of mathematical functions, we'll explore the ins and outs of this essential library. Whether you're a beginner looking to enhance your Python skills or an experienced programmer seeking to optimize your data manipulation techniques, this video is packed with valuable insights and practical tips. Make sure to hit the like button and share this video with your friends who are eager to level up their Python programming game!

In Python we have lists that serve the purpose of arrays, but they are slow to process.

NumPy aims to provide an array object that is up to 50x faster than traditional Python lists.

The array object in NumPy is called ndarray, it provides a lot of supporting functions that make working with ndarray very easy.

Arrays are very frequently used in data science, where speed and resources are very important.

Data Science: is a branch of computer science where we study how to store, use and analyze data for deriving information from it.

In this video, we dive deep into the differences between Numpy, List, and Array in Python. We'll provide clear examples using A, I, 7, 9, and 5 to help you understand when to use each data structure effectively in your Python projects.

Understanding the distinctions between these key data structures is crucial for boosting your Python programming skills and efficiency. Whether you're a beginner or an intermediate Python developer, this breakdowns will help you make informed decisions in your code.

Don't miss out on this insightful comparison! Watch the video, like it if you find it helpful, and share it with your fellow Python enthusiasts to spread the knowledge. Let's level up our Python programming together! 🐍💻 #PythonProgramming #NumpyVSListVSArray #PythonDataStructures

OUTLINE:

00:00:00 Introduction to Python Data Structures

00:00:20 Understanding Lists in Python

00:00:41 Introduction to Arrays

00:01:04 Unpacking Numpy

00:01:25 Comparing Numpy, List, and Array

00:01:56 Conclusion

Quiz || Poll

What is a correct syntax to create a NumPy array?

• 0%np.array([1, 2, 3, 4, 5])
• 0%np.createArray([1, 2, 3, 4, 5])
• 0%np.object([1, 2, 3, 4, 5])

Which of the following arrays is a two dimensional (2-D) array?

• 0%[[1, 2, 3], [4, 5, 6]]
• 0%[1, 2, 3, 4, 5]
• 0%[A,79]

What is a correct syntax to check the number of dimensions in an array?

• 0%arr.ndim()
• 0%arr.dim
• 0%arr.dim()
• 0%arr.ndim

What is a correct syntax to print the first item of an array?

• 0%print(myArr[0])
• 0%print(myArr,1)
• 0%print(myArr[1])

What is a correct syntax to print the number 8 from the array below: arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])

• 0%print(arr[1, 2])
• 0%print(arr[3, 0])
• 0%print(arr[7, 2])