Numpy

  Numpy Library Introduction      NumPy is a Python library that is used for scientific computing. It is an abbreviation for Numerical Python. NumPy provides support for arrays and matrices, as well as a number of mathematical functions to work with these arrays. In this blog, we will explore the various features and functions of NumPy library and how it can be useful for scientific computing. Arrays in NumPy      One of the primary features of NumPy is the array object. NumPy arrays are similar to Python lists, but with added advantages. They are more efficient, take up less memory, and allow for faster computations. Arrays in NumPy can be multidimensional, making it easy to work with matrices.      To create an array in NumPy, we use the np.array() function. We can create a one-dimensional array as follows: python import numpy as np a = np.array([ 1 , 2 , 3 ]) print (a) Output: [ 1 2 3 ]      We can also create a two...