Python Data Visualization Cookbook

Python Data Visualization Cookbook - Over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries

Overview

• Learn how to set up an optimal Python environment for data visualization
• Understand the topics such as importing data for visualization and formatting data for visualization
• Understand the underlying data and how to use the right visualizations

In Detail

Today, data visualization is a hot topic as a direct result of the vast amount of data created every second. Transforming that data into information is a complex task for data visualization professionals, who, at the same time, try to understand the data and objectively transfer that understanding to others. This book is a set of practical recipes that strive to help the reader get a firm grasp of the area of data visualization using Python and its popular visualization and data libraries.

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts.

Python Data Visualization Cookbook starts by showing you how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. During the book, we go from simple plots and charts to more advanced ones, thoroughly explaining why we used them and how not to use them. As we go through the book, we will also discuss 3D diagrams. We will peep into animations just to show you what it takes to go into that area. Maps are irreplaceable for displaying geo-spatial data, so we also show you how to build them. In the last chapter, we show you how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.

This book will help those who already know how to program in Python to explore a new field – one of data visualization. As this book is all about recipes that explain how to do something, code samples are abundant, and they are followed by visual diagrams and charts to help you understand the logic and compare your own results with what is explained in the book.

What you will learn from this book

• Install and use iPython
• Use Python's virtual environments
• Install and customize NumPy and matplotlib
• Draw common and advanced plots
• Visualize data using maps
• Create 3D animated data visualizations
• Import data from various formats
• Export data from various formats

Approach

This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.

Print list of int, and String

This example print list of int, and String:

Print list of int, and String

#generate random 5 number
import random

list=[]     #init a empty list

for x in range(0, 5):
    random_number = random.randint(0, 10)
    print(random_number)
    list.append(random_number)  #append random number to list
    
#print all elements
print('[%s]' % ', '.join(map(str, list)))

strList = ['abc', 'def', 'ghi', 'jkl']
#join strings in list, with ', ' in between each element.
print(', '.join(strList));

Generate random number in Python

To generate random number in Python Shell:

>>> import random
>>> random.randint(0, 10)

Generate random number in Python Shell

Code example:

#generate random 5 number
import random
for x in range(0, 5):
    random_number = random.randint(0, 10)
    print(random_number)

Python code to generate random number

Output