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    Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python
    Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python
    Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python
    Ebook1,270 pages5 hours

    Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python

    By Srinivasa Rao Poladi

    ()

    Read preview

    About this ebook

    Build attractive, insightful, and powerful visualizations to gain quality insights from your data




    Key Features



    • Master Matplotlib for data visualization


    • Customize basic plots to make and deploy figures in cloud environments


    • Explore recipes to design various data visualizations from simple bar charts to advanced 3D plots





    Book Description



    Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Matplotlib 3.0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3.7.







    With the help of this cookbook, you'll be able to tackle any problem you might come across while designing attractive, insightful data visualizations. With the help of over 150 recipes, you'll learn how to develop plots related to business intelligence, data science, and engineering disciplines with highly detailed visualizations. Once you've familiarized yourself with the fundamentals, you'll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You'll annotate and add rich text to the plots, enabling the creation of a business storyline. In addition to this, you'll learn how to save figures and animations in various formats for downstream deployment, followed by extending the functionality offered by various internal and third-party toolkits, such as axisartist, axes_grid, Cartopy, and Seaborn.







    By the end of this book, you'll be able to create high-quality customized plots and deploy them on the web and on supported GUI applications such as Tkinter, Qt 5, and wxPython by implementing real-world use cases and examples.




    What you will learn



    • Develop simple to advanced data visualizations in Matplotlib


    • Use the pyplot API to quickly develop and deploy different plots


    • Use object-oriented APIs for maximum flexibility with the customization of figures


    • Develop interactive plots with animation and widgets


    • Use maps for geographical plotting


    • Enrich your visualizations using embedded texts and mathematical expressions


    • Embed Matplotlib plots into other GUIs used for developing applications


    • Use toolkits such as axisartist, axes_grid1, and cartopy to extend the base functionality of Matplotlib



    Who this book is for



    The Matplotlib 3.0 Cookbook is for you if you are a data analyst, data scientist, or Python developer looking for quick recipes for a multitude of visualizations. This book is also for those who want to build variations of interactive visualizations.

    LanguageEnglish
    PublisherPackt Publishing
    Release dateOct 23, 2018
    ISBN9781789138665
    Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python

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      Book preview

      Matplotlib 3.0 Cookbook - Srinivasa Rao Poladi

      Matplotlib 2.x Cookbook

      Matplotlib 3.0 Cookbook

      Over 150 recipes to create highly detailed interactive visualizations using Python

      Srinivasa Rao Poladi

      BIRMINGHAM - MUMBAI

      Matplotlib 3.0 Cookbook

      Copyright © 2018 Packt Publishing

      All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

      Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

      Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

      Commissioning Editor: Sunith Shetty

      Acquisition Editor: Namrata Patil

      Content Development Editor: Unnati Guha

      Technical Editor: Sayli Nikalje

      Copy Editor: Safis Editing

      Project Coordinator: Manthan Patel

      Proofreader: Safis Editing

      Indexer: Rekha Nair

      Graphics: Jisha Chirayil

      Production Coordinator: Arvindkumar Gupta

      First published: October 2018

      Production reference: 1191018

      Published by Packt Publishing Ltd.

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      B3 2PB, UK.

      ISBN 978-1-78913-571-8

      www.packtpub.com

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      Contributors

      About the author

      Srinivasa Rao Poladi has been in the IT services industry for over two decades, providing consulting and implementation services in data warehousing, business intelligence, and machine learning areas for global customers.

      He has worked with Wipro Technologies for two decades and played key leadership roles in building large technology practices and growing them to multi-million $ business.

      He spoke at international conferences, published many blogs and white papers in the areas of big data, business intelligence, and analytics.

      He is a co-founder of krtrimaIQ a consulting firm that provides cognitive solutions to create tomorrow's Intelligent Enterprises powered by automation, big data, machine learning, and deep learning.

      About the reviewer

      Nikhil Borkar holds a CQF designation and a post-graduate degree in quantitative finance. He also holds the Certified Financial Crime Examiner and Certified Anti-Money Laundering Professional qualifications. He is a registered research analyst with the Securities and Exchange Board of India (SEBI) and has a keen grasp of the Indian regulatory landscape pertaining to securities and investments. He is currently working as an independent FinTech and legal consultant. Prior to this, he worked with Morgan Stanley Capital International (MSCI) as a Global RFP Project Manager.

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      Table of Contents

      Title Page

      Copyright and Credits

      Matplotlib 3.0 Cookbook

      Packt Upsell

      Why subscribe?

      Packt.com

      Contributors

      About the author

      About the reviewer

      Packt is searching for authors like you

      Preface

      Who this book is for

      What this book covers

      To get the most out of this book

      Download the example code files

      Download the color images

      Conventions used

      Sections

      Getting ready

      How to do it…

      How it works…

      There's more…

      See also

      Get in touch

      Reviews

      Anatomy of Matplotlib

      Introduction

      Architecture of Matplotlib

      Backend layer

      Artist layer

      Scripting layer

      Elements of a figure

      Figure

      Axes

      Axis

      Label

      Legend

      Title

      Ticklabels

      Spines

      Grid

      Working in interactive mode

      Getting ready

      How to do it...

      How it works...

      There's more...

      Working in non-interactive mode

      How to do it...

      How it works...

      Reading from external files and plotting

      Getting ready

      How to do it...

      Reading from a .txt file

      Reading from a .csv file

      Reading from an .xlsx file

      Plotting the graph

      How it works...

      Changing and resetting default environment variables 

      Getting ready

      How to do it...

      How it works...

      There's more...

      Getting Started with Basic Plots

      Introduction

      Line plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Bar plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Scatter plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Bubble plot

      Getting ready

      How to do it...

      How it works...

      Stacked plot

      Getting ready

      How to do it...

      How it works...

      Pie plot

      Getting ready

      How to do it...

      How it works...

      Table chart

      Getting ready

      How to do it...

      How it works...

      Polar plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Histogram

      Getting ready

      How to do it...

      How it works...

      There's more...

      Box plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Violin plot

      Getting ready

      How to do it...

      How it works...

      Reading and displaying images

      Getting ready

      How to do it...

      How it works...

      Heatmap

      Getting ready

      How to do it...

      How it works...

      Hinton diagram

      Getting ready

      How to do it...

      How it works...

      Contour plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Triangulations

      Getting ready

      How to do it...

      How it works...

      There's more...

      Stream plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Path

      Getting ready

      How to do it...

      How it works...

      Plotting Multiple Charts, Subplots, and Figures

      Introduction

      Plotting multiple graphs on the same axes

      Getting ready

      How to do it...

      How it works...

      Plotting subplots on the same figure

      Getting ready

      How to do it...

      How it works...

      There's more...

      Plotting multiple figures in a session

      Getting ready

      How to do it...

      How it works...

      There's more...

      Logarithmic scale

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using units of measurement

      Getting ready

      How to do it...

      How it works...

      There's more...

      Developing Visualizations for Publishing Quality

      Introduction

      Color, line style, and marker customization

      Getting ready

      How to do it...

      How it works...

      Working with standard colormaps

      Getting ready

      How to do it...

      How it works...

      There's more...

      User-defined colors and colormaps

      Getting ready

      How to do it...

      How it works...

      There's more...

      Working with legend

      Getting ready

      How to do it...

      How it works...

      There's more...

      Customizing labels and titles

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using autoscale and axis limits

      Getting ready

      How to do it...

      How it works...

      Customizing ticks and ticklabels

      Getting ready

      How to do it...

      How it works...

      There's more...

      Customizing spines

      Getting ready

      How to do it...

      How it works...

      Twin axes

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using hatch

      Getting ready

      How to do it...

      How it works...

      Using annotation

      Getting ready

      How to do it...

      How it works...

      Using style sheets

      Getting ready

      How to do it...

      How it works...

      There's more...

      Plotting with Object-Oriented API

      Introduction

      Plotting a correlation matrix using pyplot and object-oriented APIs

      Getting ready

      How to do it...

      How it works...

      Plotting patches using object-oriented API

      Getting ready

      How to do it...

      How it works...

      Plotting collections using object-oriented API

      Getting ready

      How to do it...

      How it works...

      Plotting with Advanced Features

      Using property cycler

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using Path effects

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using transforms

      Transforming data co-ordinates to display co-ordinates

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using axes and blended co-ordinate system transforms

      Getting ready

      How to do it...

      How it works...

      Taking control of axes positions

      Getting ready

      How to do it...

      How it works...

      GridSpec for figure layout

      Using GridSpec

      Getting ready

      How to do it...

      How it works...

      There's more...

      GridSpec alignment

      Getting ready

      How to do it...

      How it works ...

      Constrained layout

      Getting ready

      How to do it...

      How it works...

      Using GridSpecFromSubplotSpec

      Getting ready

      How to do it...

      How it works...

      Using origin and extent for image orientation

      Getting ready

      How to do it...

      How it works...

      Geographical plotting using geopandas

      Getting ready

      How to do it...

      How it works...

      Embedding Text and Expressions

      Introduction

      Using mathematical expressions with a font dictionary

      Getting ready

      How to do it...

      How it works...

      Annotating a point on a polar plot

      Getting ready

      How to do it...

      How it works...

      Using ConnectionPatch

      Getting ready

      How to do it...

      How it works...

      Using a text box

      Getting ready

      How to do it...

      How it works...

      There's more...

      Plotting area under an integral curve

      Getting ready

      How to do it...

      How it works...

      Defining custom markers

      Getting ready

      How to do it...

      How it works...

      Fractions, regular mathematical expressions, and symbols

      Getting ready

      How to do it...

      How it works...

      There's more...

      Word embeddings in two dimensions

      Getting ready

      How to do it...

      How it works...

      Saving the Figure in Different Formats

      Introduction

      Saving the figure in various formats

      Getting ready

      How to do it...

      How it works...

      There's more...

      Avoiding truncation while saving the figure

      Getting ready

      How to do it...

      How it works...

      Saving partial figures

      Getting ready

      How to do it...

      How it works...

      Managing image resolution

      Getting ready

      How to do it...

      How it works...

      Managing transparency for web applications

      Getting ready

      How to do it...

      How it works...

      Creating multi-page PDF reports

      Getting ready

      How to do it...

      How it works...

      Developing Interactive Plots

      Introduction

      Events and callbacks

      Exception handling

      Getting ready

      How to do it...

      How it works...

      There's more...

      Key press and release events

      Getting ready

      How to do it...

      How it works...

      Mouse button press event

      Getting ready

      How to do it...

      How it works...

      Motion notify and mouse button press events

      Getting ready

      How to do it...

      How it works...

      Pick event

      Getting ready

      How to do it...

      How it works...

      Figure and axes, enter and leave events

      Getting ready

      How to do it...

      How it works...

      Using twin axes for plotting four temperature scales

      Getting ready

      How to do it...

      How it works...

      Widgets

      Cursor

      Getting ready

      How to do it...

      How it works...

      Buttons

      Getting ready

      How to do it...

      How it works...

      Check buttons

      Getting ready

      How to do it...

      How it works...

      Radio buttons

      Getting ready

      How to do it...

      How it works...

      Textbox

      Getting ready

      How to do it...

      How it works...

      Animation

      Animated sigmoid curve

      Getting ready

      How to do it...

      How it works...

      Saving the animation to an mp4 file

      Getting ready

      How to do it...

      How it works...

      Exponentially decaying tan function

      Getting ready

      How to do it...

      How it works...

      Animated bubble plot 

      Getting ready

      How to do it...

      How it works...

      Animating multiple line plots

      Getting ready

      How to do it...

      How it works...

      Animation of images

      Getting ready

      How to do it...

      How it works...

      Embedding Plots in a Graphical User Interface

      Introduction

      Interface between the Matplotlib and GUI applications

      Using the Slider and Button Widgets of Matplotlib

      Getting ready

      How to do it...

      How it works...

      Using the Slider and Button widgets of Tkinter GUI 

      Getting ready

      How to do it...

      How it works...

      Embedding Matplotlib in a Tkinter GUI application

      Getting ready

      How to do it...

      How it works...

      Using the Slider and Button widgets of WxPython GUI

      Getting ready

      How to do it...

      How it works...

      Embedding Matplotlib in to a wxPython GUI application

      Getting ready

      How to do it...

      How it works...

      Using the Slider and Button widgets of Qt's GUI

      Getting ready

      How to do it...

      How it works...

      Embedding Matplotlib in to a Qt GUI application

      Getting ready

      How to do it...

      How it works...

      Plotting 3D Graphs Using the mplot3d Toolkit

      Introduction

      Line plot

      Getting ready

      How to do it...

      How it works...

      Scatter plot

      Getting ready

      How to do it...

      How it works...

      Bar plot

      Getting ready

      How to do it...

      How it works...

      Polygon plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Contour plot

      Getting ready

      How to do it...

      How it works...

      There's more...

      Surface plot

      Getting ready

      How to do it...

      How it works...

      Wireframe plot

      Getting ready

      How to do it...

      How it works...

      Triangular surface plot

      Getting ready

      How to do it...

      How it works...

      Plotting 2D data in 3D

      Getting ready

      How to do it...

      How it works...

      3D visualization of linearly non-separable data in 2D

      Getting ready

      How to do it...

      How it works...

      Word embeddings

      Getting ready

      How to do it...

      How it works...

      Using the axisartist Toolkit

      Introduction

      Understanding attributes in axisartist

      Getting ready

      How to do it...

      How it works...

      Defining curvilinear grids in rectangular boxes

      Getting ready

      How to do it...

      How it works...

      Defining polar axes in rectangular boxes

      Getting ready

      How to do it...

      How it works...

      Using floating axes for a rectangular plot

      Getting ready

      How to do it...

      How it works...

      Creating polar axes using floating axes

      Getting ready

      How to do it...

      How it works...

      Plotting planetary system data on floating polar axes

      Getting ready

      How to do it...

      How it works...

      Using the axes_grid1 Toolkit

      Introduction

      Plotting twin axes using the axisartist and axesgrid1 toolkits

      Getting ready

      How to do it...

      How it works...

      There's more...

      Using AxesDivider to plot a scatter plot and associated histograms

      Getting ready

      How to do it...

      How it works...

      Using AxesDivider to plot a colorbar

      Getting ready

      How to do it...

      How it works...

      Using ImageGrid to plot images with a colorbar in a grid

      Getting ready

      How to do it...

      How it works...

      Using inset_locator to zoom in on an image

      Getting ready

      How to do it...

      How it works...

      Using inset_locator to plot inset axes

      Getting ready

      How to do it...

      How it works...

      Plotting Geographical Maps Using Cartopy Toolkit

      Introduction

      Plotting basic map features

      Getting ready

      How to do it...

      How it works...

      Plotting projections

      Getting ready

      How to do it...

      How it works...

      Using grid lines and labels

      Getting ready

      How to do it...

      How it works...

      Plotting locations on the map

      Getting ready

      How to do it...

      How it works...

      Plotting country maps with political boundaries

      Getting ready

      How to do it...

      How it works...

      Plotting country maps using GeoPandas and cartopy

      Getting ready

      How to do it...

      How it works...

      Plotting populated places of the world

      Getting ready

      How to do it...

      How it works...

      Plotting the top five and bottom five populated countries

      Getting ready

      How to do it...

      How it works...

      Plotting temperatures across the globe

      Getting ready

      How to do it...

      How it works...

      Plotting time zones

      Getting ready

      How to do it...

      How it works...

      Plotting an animated map

      Getting ready

      How to do it...

      How it works...

      Exploratory Data Analysis Using the Seaborn Toolkit

      Introduction

      Snacks Sales dataset

      Wine Quality

      Semantic and facet variables

      Relational plots

      Line plots with one-to-one and one-to-many relationships

      Getting ready

      How to do it...

      How it works...

      There's more...

      Line plots with a long-form dataset

      Getting ready

      How to do it...

      How it works...

      Scatter plots

      Getting ready

      How to do it...

      How it works...

      There's more...

      Categorical plots

      Strip and swarm plots

      Getting ready

      How to do it...

      How it works...

      Box and boxn plots

      Getting ready

      How to do it...

      How it works...

      Bar and count plots

      Getting ready

      How to do it...

      How it works...

      Violin plots

      Getting ready

      How to do it...

      How it works...

      Point plots

      Getting ready

      How to do it...

      How it works...

      Distribution plots

      distplot()

      Getting ready

      How to do it...

      How it works...

      kdeplot()

      Getting ready

      How to do it...

      How it works...

      Regression plots

      regplot() and residplot()

      Getting ready

      How to do it...

      How it works...

      lmplot()

      Getting ready

      How to do it...

      How it works...

      Multi-plot grids

      jointplot() and JointGrid()

      Getting ready

      jointplot()

      How to do it...

      How it works...

      JointGrid()

      How to do it...

      How it works...

      pairplot() and PairGrid()

      Getting ready

      pairplot()

      How to do it...

      How it works...

      PairGrid()

      How to do it...

      How it works...

      FacetGrid()

      Getting ready

      How to do it...

      How it works...

      Matrix plots

      Heatmaps

      Getting ready

      How to do it...

      How it works...

      Clustermaps

      Getting ready

      How to do it...

      How it works...

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      Preface

      In the era of big data, finding valuable business insights is akin to finding a needle in a haystack. Visualization plays a critical role in finding those nuggets from an ever-increasing volume and variety of data. Matplotlib, with its rich visualization functionality, makes the process of exploratory data analysis user friendly and more productive. 

      Matplotlib's core functionality is vast, and it is further enhanced by many in-house and third-party toolkits. Many of the books on the market cover only a small portion of its complete functionality. In this book, we have covered Matplotlib's complete core functionality and many of its popular toolkits.

      Matplotlib is popular among machine learning practitioners and researchers who use the Python ecosystem. With its rich functionality, it can be used in business intelligence and operational reporting applications. In this book, we have made an attempt to present examples from these applications.

      While a recipe-based cookbook approach makes this book a reference guide for quick solutions, we have covered sufficient theoretical background to make it easy for beginners as well.

      Who this book is for

      This book is for data analysts, business analysts, data scientists, and Python developers who are looking for quick solutions for a wide variety of visualization applications, such as ad hoc reports, professional dashboards, exploratory data analysis, interactive analysis, embedded visualizations in selected GUI toolkits and web applications, three-dimensional plots, and geographical maps.

      Those who are interested in developing business intelligence, machine learning, scientific, or engineering applications will also benefit from the recipes that are relevant for each of these disciplines.

      What this book covers

      Chapter 1, Anatomy of Matplotlib, explains the architecture of Matplotlib, various elements of a figure, interactive and non-interactive modes of operation, and how to customize environmental parameters.

      Chapter 2, Getting Started with Basic Plots, introduces many types of graph that are commonly used in business intelligence and machine learning applications, including line, scatter, bar, stacked, histogram, box, violin, contour plots, heatmaps, and Hinton diagrams.

      Chapter 3, Plotting Multiple Graphs, Subplots, and Figures, shows how to organize graphs into subplots and figures.

      Chapter 4, Developing Visualizations for Publishing Quality, illustrates how to customize various attributes of a figure, including color, fonts, labels, titles, legend, spines, styles, markers, and annotation.

      Chapter 5, Plotting with the Object-Oriented API, introduces the object-oriented API and compares it with the pyplot API. The object-oriented API gives flexibility in designing complex dashboards as required, but requires Python programming experience if you want to write code. The pyplot API comes with pre-packaged graphs that require simple commands to plot, without needing to write much Python code.

      Chapter 6, Plotting with Advanced Features, covers how to develop complex visualization applications by using the advanced customization of legends, artist, and layout, as well as cycling object properties, origin and extent in images, transforms, animations, event handling, and path effects.

      Chapter 7, Embedding Text and Expressions, covers how to add text to plots with regular text, annotations and mathematical expressions.

      Chapter 8, Saving the Figure in Different Formats, explains how to save figures to external output files in PNG, PDF, SVG, and PS formats.

      Chapter 9, Developing Interactive Plots, explains how to develop interactive plots using event handling, animations, and widgets. These features enable the users to perform interactive analysis.

      Chapter 10, Embedding Plots in Graphical User Interface, explains how to embed Matplotlib plots into other graphical user interfaces used for developing applications.

      Chapter 11, Plotting 3D Graphs Using the mplot3d Toolkit, covers how to use the mplot3D toolkit to plot 3D graphs, and the next two chapters cover two more toolkits.

      Chapter 12, Using the axisartist Toolkit, explains that while the standard Matplotlib axes uses a traditional Cartesian coordinate system, it can't handle special features such as curved or floating axes that are useful in plotting geographical or planetary systems. This chapter explains how to create special applications using the axisartist toolkit.

      Chapter 13, Using the axes_grid1 Toolkit, covers the axes_grid1 toolkit. This toolkit enables you to plot images in a grid with an associated color bar that aligns well with the image and also enables anchor images as legends, zoom in/out effects, and more.

      Chapter 14, Plotting Geographical Maps Using the Cartopy Toolkit, explains wide variety of features that cater to many different user communities. We will cover most of the features typically used in business applications.

      Chapter 15, Exploratory Data Analysis Using the Seaborn Toolkit, explains the process of exploratory data analysis using exhaustive features of seaborn toolkit.

      To get the most out of this book

      Basic knowledge of Python is enough to understand the content in this book, except for Chapters 9, Developing Interactive Plots and Chapter 10, Embedding Plots in a Graphical User Interface. These two chapters deal with interactive plotting and embedded applications that need medium-level Python programming experience.

      Many Python distributions automatically include Matplotlib, along with all its dependencies. If you have not installed any standard Python distributions, you can follow the installation process at https://matplotlib.org/users/installing.html to install Matplotlib and its associated dependencies.

      Download the example code files

      You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

      You can download the code files by following these steps:

      Log in or register at www.packt.com.

      Select the SUPPORT tab.

      Click on Code Downloads & Errata.

      Enter the name of the book in the Search box and follow the onscreen instructions.

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      The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Matplotlib-3.0-Cookbook. In case there's an update to the code, it will be updated on the existing GitHub repository.

      We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

      Download the color images

      We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/9781789135718_ColorImages.pdf.

      Conventions used

      There are a number of text conventions used throughout this book.

      CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: We will follow the order of .txt, .csv, and .xlsx files, in three separate sections.

      A block of code is set as follows:

      import matplotlib.pyplot as plt

      import pandas as pd

      import numpy as np

      from matplotlib import cm

      Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "When you run the program and click Next and Next, you will see the following three figures, representing each of the clusters, as shown in the header of each figure."

      Warnings or important notes appear like this.

      Tips and tricks appear like this.

      Sections

      In this book, you will find several headings that appear frequently (Getting ready, How to do it..., How it works..., There's more..., and See also).

      To give clear instructions on how to complete a recipe, use these sections as follows:

      Getting ready

      This section tells you what to expect in the recipe and describes how to set up any software or any preliminary settings required for the recipe.

      How to do it…

      This section contains the steps required to follow the recipe.

      How it works…

      This section usually consists of a detailed explanation of what happened in the previous section.

      There's more…

      This section consists of additional information about the recipe in order to make you more knowledgeable about the recipe.

      See also

      This section provides helpful links to other useful information for the recipe.

      Get in touch

      Feedback from our readers is always welcome.

      General feedback: If you have questions about any aspect of this book, mention the book title in the subject of your message and email us at [email protected].

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      Anatomy of Matplotlib

      This chapter begins with an introduction to Matplotlib, including the architecture of Matplotlib and the elements of a figure, followed by the recipes. The following are the recipes that will be covered in this chapter: 

      Working in interactive mode

      Working in non-interactive mode

      Reading from external files and plotting

      How to change and reset default environment variables 

      Introduction

      Matplotlib is a cross-platform Python library for plotting two-dimensional graphs (also called plots). It can be used in a variety of user interfaces such as Python scripts, IPython shells, Jupyter Notebooks, web applications, and GUI toolkits. It can be used to develop professional reporting applications, interactive analytical applications, complex dashboard applications or embed into web/GUI applications. It supports saving figures into various hard-copy formats as well. It also has limited support for three-dimensional figures. It also supports many third-party toolkits to extend its functionality.

      Please note that all the examples in this book are tested with Matplotlib 3.0 and Jupyter Notebook 5.1.0.

      Architecture of Matplotlib

      Matplotlib has a three-layer architecture: backend, artist, and scripting, organized logically as a stack. Scripting is an API that developers use to create the graphs. Artist does the actual job of creating the graph internally. Backend is where the graph is displayed.

      Backend layer

      This is the bottom-most layer where the graphs are displayed on to an output device. This can be any of the user interfaces that Matplotlib supports. There are two types of backends: user interface backends (for use in pygtk, wxpython, tkinter, qt4, or macosx, and so on, also referred to as interactive backends) and hard-copy backends to make image files (.png, .svg, .pdf, and .ps, also referred to as non-interactive backends). We will learn how to configure these backends in later Chapter 9, Developing Interactive Plots and Chapter 10, Embedding Plots in a Graphical User Interface.

      Artist layer

      This is the middle layer of the stack. Matplotlib uses the artist object to draw various elements of the graph. So, every element (see elements of a figure) we see in the graph is an artist. This layer provides an object-oriented API for plotting graphs with maximum flexibility. This interface is meant for seasoned Python programmers, who can create complex dashboard applications.

      Scripting layer

      This is the topmost layer of the stack. This layer provides a simple interface for creating graphs. This is meant for use by end users who don't have much programming expertise. This is called a pyplot API.

      Elements of a figure

      The high-level Matplotlib object that contains all the elements of the output graph is called a figure. Multiple graphs can be arranged in different ways to form a figure. Each of the figure's elements is customizable.

      Figure

      The following diagram is the anatomy of a figure, containing all its elements:

      Anatomy of a figure (Source : http://diagramss.us/plotting-a-graph-in-matlab.html)

      Axes

      axes is a sub-section of the figure, where a graph is plotted. axes has a title, an x-label and a y-label. A figure can have many such axes, each representing one or more graphs. In the preceding figure, there is only one axes, two line graphs in blue and red colors.

      Axis

      These are number lines representing the scale of the graphs being plotted. Two-dimensional graphs have an x axis and a y axis, and three-dimensional graphs have an x axis, a y axis, and a z axis.

      Don't get confused between axes and axis. Axis is an element of axes. Grammatically, axes is also the plural for axis, so interpret the meaning of axes depending on the context, whether multiple axis elements are being referred to or an axes object is being referred to.

      Label

      This is the name given to various elements of the figure, for example, x axis label, y axis label, graph label (blue signal/red signal in the preceding figure Anatomy of a figure), and so on.

      Legend

      When there are multiple graphs in the axes (as in the preceding figure Anatomy of a figure), each of them has its own label, and all these labels are represented as a legend. In the preceding figure, the legend is placed at the top-right corner of the figure.

      Title

      It is the name given to each of the axes. The figure also can have its own title, when the figure has multiple axes with their own titles. The preceding figure has only one axes, so there is only one title for the axes as well as the figure.

      Ticklabels

      Each axis (x, y, or z) will have a range of values that are divided into many equal bins. Bins are chosen at two levels. In the preceding figure Anatomy of a figure, the x axis scale ranges from 0 to 4, divided into four major bins (0-1, 1-2, 2-3, and 3-4) and each of the major bins is further divided into four minor bins (0-0.25, 0.25-0.5, and 0.5-0.75). Ticks on both sides of major bins are called major ticks and minor bins are called minor ticks, and the names given to them are major ticklabels and minor ticklabels.

      Spines

      Boundaries of the figure are called spines. There are four spines for each axes(top, bottom, left, and right).

      Grid

      For easier readability of the coordinates of various points on the graph, the area of the graph is divided into a grid. Usually, this grid is drawn along major ticks of the x and y axis. In the preceding figure, the grid is shown in dashed lines.

      Working in interactive mode

      Matplotlib can be used in an interactive or non-interactive modes. In the interactive mode, the graph display gets updated after each statement. In the non-interactive mode, the graph does not get displayed until explicitly asked to do so. 

      Getting ready

      You need working installations of Python, NumPy, and Matplotlib packages. 

      Using the following commands, interactive mode can be set on or off, and also checked for current mode at any point in time:

      matplotlib.pyplot.ion() to set the interactive mode ON

      matplotlib.pyplot.ioff() to switch OFF the interactive mode

      matplotlib.is_interactive() to check whether the interactive mode is ON (True) or OFF (False)

      How to do it...

      Let's see how simple it is to work in interactive mode:

      Set the screen output as the backend:

      %matplotlib inline

      Import the matplotlib and pyplot libraries. It is common practice in Python to import libraries with crisp synonyms. Note plt is the synonym for the matplotlib.pyplot package:

      import matplotlib as mpl

      import matplotlib.pyplot as plt

      Set the interactive mode to ON:

      plt.ion()

      Check the status of interactive mode:

      mpl.is_interactive()

      You should get the output as True.

      Plot a line graph:

      plt.plot([1.5, 3.0])

      You should see the following graph as the output:

      Now add the axis labels and a title to the graph with the help of the following code:

      # Add labels and title

      plt.title(Interactive Plot) #Prints the title on top of graph

      plt.xlabel(X-axis)        # Prints X axis label as X-axis

      plt.ylabel(Y-axis)        # Prints Y axis label as Y-axis

      After executing the preceding three statements, your graph should look as follows:

      How

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