**The fundamental package for scientific computing with Python**

**NumPy Official Website: https://numpy.org/**

**Downloads: https://numpy.org/install/**

**Source code: https://github.com/numpy/numpy**

## Descriptions for NumPy

- Creator: Travis Oliphant(2005)
- License: Open source
- Expansion: Numerical Python
- Purpose: Array Manipulator
- Domains:Linear algebra, Fourier transform, Matrices

**NumPy or Lists ?**

- NumPy arrays are stored at one continuous place in memory
- NumPy is faster than lists and also it is optimized to work with latest CPU architectures
**.**

**---------------------------------------------------------------------------------------------------------------------------------------**

**# Checking NumPy Version**

print(np.__version__)

**# Sample Array Creation**

import numpy

a = numpy.array([111, 222, 333, 444, 555])

print(a)

**# Python alias are an alternate name (np)**

import numpy
as np

a = np.array([111, 222, 333, 444, 555])

print(a)

a = np.array([111, 222, 333, 444, 555])

print(a)

**# 1-Dimesion to n-Dimension Array**

a1 = np.array(42) #0-D Arrays

a2 = np.array([1, 2, 3, 4, 5,6,7,8,9]) #1-D Arrays

a3 = np.array([[1, 2, 3], [4, 5, 6]]) #2-D Arrays

a4 = np.array([ [[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]] ]) #3-D Arrays

a5 = np.array([1, 2, 3, 4], ndmin=5) #n-D Arrays

print(a1,a2,a3,a4,a5)

a2 = np.array([1, 2, 3, 4, 5,6,7,8,9]) #1-D Arrays

a3 = np.array([[1, 2, 3], [4, 5, 6]]) #2-D Arrays

a4 = np.array([ [[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]] ]) #3-D Arrays

a5 = np.array([1, 2, 3, 4], ndmin=5) #n-D Arrays

print(a1,a2,a3,a4,a5)

**# Access Elements or Indexing**

print(a1)

print(a2[3])

print (a3[1,1])

print(a4[0, 2, 0])

**# Negative Indexing**

print(a3[0, -1])

**# Shape of an Array**

print(a1.shape,a2.shape,a3.shape,a4.shape,a5.shape)

**# Reshape From 1-D to 2-D**

na2 = a2.reshape(4, 3)

print(na2)

print(na2)

**# Reshape From 1-D to 3-D**

nna2 = a2.reshape(2, 3, 2)

print(nna2)

print(nna2)

**# Shuffling Arrays**

random.shuffle(a2)

print(a2)

print(a2)

**# Generating Permutation of Arrays**

print(random.permutation(a2))

------------------------------------------------------------------------------------------------

More Examples for Numpy

__Python
programto find Sine and Cosine Values plot using Matplotlib____
__

__Solving
linear mathematical equations with two variable____
__

__Operations
on Matrices using Python program____
__

__Mathematical
operators on Numpy Array and List____
__

__Statistical
and Extrema operations on Numpy Array____
__

__Elementwise
sum of two array elemets__

__
__

__2D-array representation using with & without numpy implementation__