Python Data Visualization Cookbook (Second Edition)
Visualize data using Python's most popular libraries
Published on 13. January 2025
302 pages
978-1-78439-494-3 (ISBN)
Description
Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization.
Key Features
[*] Learn how to set up an optimal Python environment for data visualization
[*] Understand how to import, clean and organize your data
[*] Determine different approaches to data visualization and how to choose the most appropriate for your needs
Book DescriptionPython 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 will 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 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. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.What you will learn
[*] Introduce yourself to the essential tooling to set up your working environment.
[*] Explore your data using the capabilities of standard Python Data Library and Panda Library
[*] Draw your first chart and customize it
[*] Use the most popular data visualization Python libraries
[*] Make 3D visualizations mainly using mplot3d
[*] Create charts with images and maps
[*] Understand the most appropriate charts to describe your data
[*] Know the matplotlib hidden gems
[*] Use plot.ly to share your visualization online
Who this book is forIf you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you.
Key Features
[*] Learn how to set up an optimal Python environment for data visualization
[*] Understand how to import, clean and organize your data
[*] Determine different approaches to data visualization and how to choose the most appropriate for your needs
Book DescriptionPython 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 will 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 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. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.What you will learn
[*] Introduce yourself to the essential tooling to set up your working environment.
[*] Explore your data using the capabilities of standard Python Data Library and Panda Library
[*] Draw your first chart and customize it
[*] Use the most popular data visualization Python libraries
[*] Make 3D visualizations mainly using mplot3d
[*] Create charts with images and maps
[*] Understand the most appropriate charts to describe your data
[*] Know the matplotlib hidden gems
[*] Use plot.ly to share your visualization online
Who this book is forIf you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you.
All prices
More details
Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
US School Grade: College Graduate Student
Edition type
Digital original
File size
9,02 MB
ISBN-13
978-1-78439-494-3 (9781784394943)
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.
Schweitzer Classification
Other editions
Additional editions
Igor Milovanovi¿ | Dimitry Fourés | Giuseppe Vettigli
Python Data Visualization Cookbook Second Edition
Book
11/2015
Packt Publishing
€56.00
Shipment within 3-4 weeks
Previous edition
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
Persons
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. Dimitry is a data scientist with a background in applied mathematics and theoretical physics. After completing his physics undergraduate studies in ENS Lyon (France), he studied fluid mechanics at cole Polytechnique in Paris where he obtained first Class class Masters degree. He holds a PhD in applied mathematics from the University of Cambridge. He currently works as a data-scientist for a smart-energy start-up in Cambridge, in close collaboration with the university. Giuseppe Vettigli is a data scientist who has worked in the research industry and academia for many years. His work is focused on the development of machine learning models and applications to use information from structured and unstructured data. He also writes about scientific computing and data visualisation in Python on his blog at http://glowingpython.blogspot.com.
Content
Table of Contents
Preparing Your Working Environment
Knowing Your Data
Drawing Your First Plots and Customizing Theme
More Plots and Customizations
Making 3D Visualizations
Plotting Charts with Images and Maps
Using Right Plots to Understand Data
More on matplotlib Gems
Visualisations on the clouds with Plot.ly
Preparing Your Working Environment
Knowing Your Data
Drawing Your First Plots and Customizing Theme
More Plots and Customizations
Making 3D Visualizations
Plotting Charts with Images and Maps
Using Right Plots to Understand Data
More on matplotlib Gems
Visualisations on the clouds with Plot.ly
