Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

Overview of this book

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 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.
Table of Contents (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Importing image data into NumPy arrays


We are going to demonstrate how to do image processing using Python's libraries such as NumPy and SciPy.

In scientific computing, images are usually seen as n-dimensional arrays. They are usually two-dimensional arrays; in our examples, they are represented as a NumPy array data structure. Therefore, functions and operations performed on those structures are seen as matrix operations.

Images in this sense are not always two-dimensional. For medical or bio-sciences, images are data structures of higher dimensions such as 3D (having the z axis as depth or as the time axis) or 4D (having three spatial dimensions and a temporal one as the fourth dimension). We will not be using those in this recipe.

We can import images using various techniques; they all depend on what you want to do with image. Also, it depends on the larger ecosystem of tools you are using and the platform you are running your project on.

In this recipe, we will demonstrate several ways to...