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Table of contents
 Highlights
 Introduction
 Here’s how we’ll learn NumPy:
 What is the NumPy library in Python?
 Python Lists vs NumPy Arrays – What’s the Difference?
 Creating a NumPy Array
 The Shape and Reshaping of NumPy Arrays
 Expanding and Squeezing a NumPy array
 Indexing and Slicing of NumPy array
 Stacking and Concatenating NumPy arrays
 Broadcasting in NumPy arrays – A class apart!
 NumPy Ufuncs – The secret of its success!
 Maths with NumPy arrays
 Sorting in NumPy arrays
 NumPy arrays and Images
 End Notes
INTRODUCTION
NumPy is one of the most fundamental libraries in Python and perhaps the
most useful of them all. NumPy handles large datasets effectively and
efficiently.
NumPy stands for Numerical Python and is one of the most useful scientific
libraries in Python programming. It provides support for large
multidimensional array objects and various tools to work with them. NumPy
arrays are called ndarray or N-dimensional arrays and they store
elements of the same type and size
Numpy installation
pip install numpy
import numpy as np

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Numpy

  • 1. Table of contents  Highlights  Introduction  Here’s how we’ll learn NumPy:  What is the NumPy library in Python?  Python Lists vs NumPy Arrays – What’s the Difference?  Creating a NumPy Array  The Shape and Reshaping of NumPy Arrays  Expanding and Squeezing a NumPy array  Indexing and Slicing of NumPy array  Stacking and Concatenating NumPy arrays  Broadcasting in NumPy arrays – A class apart!  NumPy Ufuncs – The secret of its success!  Maths with NumPy arrays  Sorting in NumPy arrays  NumPy arrays and Images  End Notes INTRODUCTION NumPy is one of the most fundamental libraries in Python and perhaps the most useful of them all. NumPy handles large datasets effectively and efficiently. NumPy stands for Numerical Python and is one of the most useful scientific libraries in Python programming. It provides support for large multidimensional array objects and various tools to work with them. NumPy arrays are called ndarray or N-dimensional arrays and they store elements of the same type and size Numpy installation pip install numpy import numpy as np