
Python Data Visualization Cookbook
As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.
Igor Milovanovic(Author)
Packt Publishing
Published on 25. November 2013
Book
Paperback/Softback
280 pages
978-1-78216-336-7 (ISBN)
Description
As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.
Key Features
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
Book DescriptionToday, 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 'AEi 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
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
Who this book is forPython Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.
You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.
Key Features
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
Book DescriptionToday, 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 'AEi 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
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
Who this book is forPython Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.
You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Target group
US School Grade: College Graduate Student
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 16 mm
Weight
528 gr
ISBN-13
978-1-78216-336-7 (9781782163367)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Igor Milovanovic
Python Data Visualization Cookbook
As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.
E-Book
01/2025
Packt Publishing
from
€31.19
Available for download
Person
Igor Milovanovic is an experienced developer, with strong background in Linux system knowledge and software engineering education. He is skilled in building scalable data-driven distributed software rich systems. An evangelist for high-quality systems design, he has a strong interest in software architecture and development methodologies. Igor is always committed to advocating methodologies that promote high-quality software, such as test-driven development, one-step builds, and continuous integration. He also possesses solid knowledge of product development. With field experience and official training, he is capable of transferring knowledge and communication flow from business to developers and vice versa. Igor is most grateful to his girlfriend for letting him spend hours on work instead with her and being an avid listener to his endless book monologues. He thanks his brother for being the strongest supporter. He is also thankful to his parents for letting him develop in various ways to become a person he is today.
Content
Table of Contents