NUMPY Programming, For Beginners, Quick Start Guide: Numpy Language Crash Course Tutorial & Exercises

About This Book (Book Length: Around 128 Pages)

Absolutely for Beginners
“Numpy Programming & Exercises” covers all essential Numpy knowledge. You can learn complete primary skills of Numpy fast and easily. The book includes many practical examples for beginners and includes questions and answers for the college exam, the engineer certification exam, and the job interview exam.

Prerequisite to learn Numpy
Before learning the Numpy, you should have basic knowledge of Python and the array, because Numpy works with Python and arrays.

Table of Contents

Hour 1
What is NumPy?
What is NumPy for?
Install NumPy
Set Up Python Editor
Import NumPy Library
Alias of NumPy Library
NumPy Array
Zero-Dimensional Array
One-Dimensional Array
Two-Dimensional Array
Three-Dimensional Array
Hour 2
High Dimension Array
The Number of Dimension
Access the Array Element
Calculate the Element Values
Access Two-Dimensional Array
Last Index
NumPy Slicing
Slicing by Default
Negative Slicing
2-D Array Slicing (1)
2-D Array Slicing (2)
2-D Array Slicing (3)
Hour 3
NumPy Data Type
Type Code
Check Data Type
Set String Array
Set Int Array
Convert Integer Type
Convert Bool Type
Copy an Array
The View of Array
Check Correlation
Array Shape (1)
Array Shape (2)
Hour 4
Reshape From 1D to 2D
Reshape From 2D to 3D
Reshape Requirement
Unknown Dimension
Flattening Array
Iterating 1-d Array
Iterating 2-d Array
Iterating 3-d Array
nditer()
Iterating with Step Length
Enumerating the Array
Hour 5
Concatenating Arrays
Axis, a Big Issue
Concatenate Arrays (axis=0)
Concatenate Arrays (axis=1)
Stack Arrays (axis=0)
Stack Arrays (axis=1)
Join Arrays Vertically
Join Arrays Horizontally
Join 1d Arrays to be 3d Array
Join 2d Arrays to be 3d Array
Sorting Number Array
Sort String Array
Hour 6
Split an Array
Split Less Elements
Access Split Array
Split 2-D Arrays
Split Vertically
Split Horizontally
Find Array Index
Where is Even/Odd Number?
Search Index in a Location
Search More Indexes
Filter Array by Boolean
Filter Array by Condition
Hour 7
NumPy ufuncs
Check NumPy ufunc
Create My Own ufunc
Arithmetic ufunc
power(), mod(), remainder()
trunc() & fix()
around(), ceil(), floor()
log2(), log10(), log()
Log in Any Base
Sum of Arrays
Sum & Axis=0
Sum & Axis=1
Hour 8
Cumulative Sum
Difference of Array
Once More Difference
Product of an Array
Product of Arrays
Product & Axis=0
Product & Axis=1
Cumulative Product
Quotient of Array
Lowest Common Multiple
Greatest Common Divisor
Rearrange the Array

Numpy Questions & Answers
Questions
Answers