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.
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# 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(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))
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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