Mastering matplotlib : a practical guide that takes you beyond the basics of matplotlib and gives solutions to plot complex data / Duncan M. McGreggor.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- text
- computer
- online resource
- 1783987553
- 9781783987559
- 005.133
- QA76.73.P98
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OPJGU Sonepat- Campus | E-Books EBSCO | Available |
Print version record.
Matplotlib is a Python plotting library that provides a large feature set for a multitude of platforms. Given the depth of the library's legacy and the variety of related open source projects, gaining expert knowledge can be a time-consuming and often confusing process. You'll begin your exciting journey learning about the skills that are necessary in leading technical teams for a visualization project or to become a matplotlib contributor. Supported by highly-detailed IPython Notebooks, this book takes you through the conceptual components underlying the library and then provides a detailed overview of its APIs. From there, you will learn about event handling and how to code for interactive plots. Next you will move on to customization techniques, local configuration of matplotib, and then deployments in Cloud environments. The adventure culminates in an exploration of big data visualization and matplotlib clustering.
Online resource; title from PDF title page (EBSCO, viewed September, 06, 2017).
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Up to Speed; A brief historical overview of matplotlib; What's new in matplotlib 1.4; The intermediate matplotlib user; Prerequisites for this book; Python 3; Coding style; Installing matplotlib; Using IPython Notebooks with matplotlib; Advanced plots -- a preview; Setting up the interactive backend; Joint plots with Seaborn; Scatter plot matrix graphs with Pandas; Summary; Chapter 2: The matplotlib Architecture; The original design goals
The current matplotlib architectureThe backend layer; FigureCanvasBase; RendererBase; Event; Visualizing the backend layer; The artist layer; Primitives; Containers; Collections; A view of the artist layer; The scripting layer; The supporting components of the matplotlib stack; matplotlib modules; Exploring the filesystem; Exploring imports visually; ModuleFinder; ModGrapher; The execution flow; An overview of the script; An interactive session; The matplotlib architecture as it relates to this book; Summary; Chapter 3: matplotlib APIs and Integrations; The procedural pylab API
The pyplot scripting APIThe matplotlib object-oriented API; Equations; Helper classes; The Plotter class; Running the jobs; matplotlib in other frameworks; An important note on IPython; Summary; Chapter 4: Event Handling and Interactive Plots; Event loops in matplotlib; Event-based systems; The event loop; GUI toolkit main loops; IPython Notebook event loops; matplotlib event loops; Event handling; Mouse events; Keyboard events; Axes and figure events; Object picking; Compound event handling; The navigation toolbar; Specialized events; Interactive panning and zooming; Summary
File and directory locationsUsing the matplotlibrc file; Updating the settings dynamically; Options in IPython; Summary; Chapter 7: Deploying matplotlib in Cloud Environments; Making a use case for matplotlib in the Cloud; The data source; Defining a workflow; Choosing technologies; Configuration management; The types of deployment; An example -- AWS and Docker; Getting set up locally; Requirements; Dockerfiles and the Docker images; Extending a Docker image; Building a new image; Preparing for deployment; Getting setup on AWS; Pushing the source data to S3; Creating a host server on EC2
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