Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Matplotlib for Python Developers
Matplotlib for Python Developers

Matplotlib for Python Developers: Effective techniques for data visualization with Python , Second Edition

Arrow left icon
Profile Icon Aldrin Yim Profile Icon Claire Chung Profile Icon Allen Yu
Arrow right icon
AU$24.99 per month
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2 (2 Ratings)
Paperback Apr 2018 300 pages 2nd Edition
eBook
AU$14.99 AU$48.99
Paperback
AU$60.99
Subscription
Free Trial
Renews at AU$24.99p/m
Arrow left icon
Profile Icon Aldrin Yim Profile Icon Claire Chung Profile Icon Allen Yu
Arrow right icon
AU$24.99 per month
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2 (2 Ratings)
Paperback Apr 2018 300 pages 2nd Edition
eBook
AU$14.99 AU$48.99
Paperback
AU$60.99
Subscription
Free Trial
Renews at AU$24.99p/m
eBook
AU$14.99 AU$48.99
Paperback
AU$60.99
Subscription
Free Trial
Renews at AU$24.99p/m

What do you get with a Packt Subscription?

Free for first 7 days. $24.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

Matplotlib for Python Developers

Getting Started with Matplotlib

Now that we are familiar with the capabilities and functionalities of Matplotlib and all geared up with the Python environment, let's go straight ahead and create our first plots.

In this chapter, we will learn how to:

  • Draw basic line and scatter plots
  • Overlay multiple data series on the same plots
  • Adjust grids, axes, and labels
  • Add a title and legend
  • Save created plots as separate files
  • Configure Matplotlib global settings

Loading data

Before we start plotting, we need to import the data we intend to plot and get familiar with basic plotting commands in Matplotlib. Let's start going through these basic commands!

While working on data visualization projects, we need to ensure that we have basic familiarity and understanding of the tools used for data processing. Before we begin, let's briefly revise the most common data structures you will encounter when handling data with Python.

List

This is the most basic Python data structure; it stores a collection of values. While you can store any data type as an element in a Python list, for our purpose of data visualization, we mostly handle lists of numerical values as data input, or at, most...

Our first plots with Matplotlib

We have just revised the basic ways of data handling with Python. Without further ado, let's create our first "Hello World!" plot example.

Importing the pyplot

To create a pandas DataFrame from objects such as lists and ndarrays, you may call:

import pandas as pd

To start creating Matplotlib plots, we first import the plotting API pyplot by entering this command:

import matplotlib.pyplot as plt

This will start your plotting routine.

In Jupyter Notebook, you need to import modules once you begin a notebook session after starting the kernel.

Line plot

...

Adjusting axes, grids, labels, titles, and legends

We have just learned how to turn numerical values into dots and lines with Matplotlib. By default, Matplotlib optimizes the display by calculating various values in the background, such as the reasonable axis range and font sizes. However, good visualization often requires more design input to suit our custom data visualization needs and purpose. Moreover, text labels are needed to make figures informative in many cases. In the following sections, we will demonstrate the methods to adjust these elements.

Adjusting axis limits

While Matplotlib automatically chooses the range of x and y axis limits to spread data onto the whole plotting area, sometimes we want some adjustment...

A complete example

To get further acquainted with Matplotlib functions, let us plot a multiline plot with axes, labels, title, and legend configured in one single snippet.

In this example, we take real-world data from the World Bank on agriculture. As the world population continues to grow, food security continues to be an important global issue. Let us have a look at the production data of a few major crops in the recent decade by plotting a multiline plot with the following code:

Data source: https://data.oecd.org/agroutput/crop-production.htm
OECD (2017), Crop production (indicator). doi: 10.1787/49a4e677-en (Accessed on 25 December 2017)
# Import relevant modules import pandas as pd import matplotlib.pyplot as plt # Import dataset crop_prod = pd.read_csv('OECD-THND_TONNES.txt',delimiter='\t') years = crop_prod[crop_prod['Crop']=='SOYBEAN...

Saving plots to a file

To save a figure, we put plt.savefig(outputpath) at the end of plotting commands. It can be used in place of plt.show(), to directly save the figure without displaying it.

If you want to save the figure as a file as well as display it on the notebook output, you can call both plt.savefig() and plt.show().

Reversing the order can result in the plot elements being cleaned up, leaving a blank canvas for the saved figure file.

Setting the output format

plt.savefig() automatically detects the file extension of the specified output path, and generates the corresponding file format if it is supported. If no file extension is specified in the input, a PNG format file would be obtained as output with...

Configuring Matplotlib

We have learned to tweak a few major elements in a Matplotlib plot. When we recurrently generate figures of similar style, it would be nice to have a way to store and apply the persistent global settings. Matplotlib offers a few options for configuration.

Configuring within Python code

To keep settings throughout the current session, we can execute matplotlib.rcParams to override configuration file settings.

For instance, we can set the font size of all text in plots to 18 with the following:

matplotlib.rcParams['font.size'] = 18

Alternatively we can call the matplotlib.rc() function. As matplotlib.rc() just changes one property, to change multiple settings, we can use the function matplotlib...

Summary

Congratulations! We are now familiar with the basic plotting techniques using Matplotlib syntax! Remember, the success of a data visualization project relies heavily upon making appealing visuals.

In the next chapters, we will learn how to beautify our plots and select the right kind of plot that communicates our data effectively!

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Perform effective data visualization with Matplotlib and get actionable insights from your data
  • Design attractive graphs, charts, and 2D plots, and deploy them to the web
  • Get the most out of Matplotlib in this practical guide with updated code and examples

Description

Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.

Who is this book for?

This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you’re a data scientist or analyst and wish to create attractive visualizations using Python, you’ll find this book useful. Some knowledge of Python programming is all you need to get started.

What you will learn

  • Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots
  • Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib
  • Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn
  • Create interactive plots with real-time updates
  • Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django
  • Write data visualization code that is readily expandable on the cloud platform

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 24, 2018
Length: 300 pages
Edition : 2nd
Language : English
ISBN-13 : 9781788625173
Category :
Languages :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $24.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Apr 24, 2018
Length: 300 pages
Edition : 2nd
Language : English
ISBN-13 : 9781788625173
Category :
Languages :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
AU$24.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
AU$249.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just AU$5 each
Feature tick icon Exclusive print discounts
AU$349.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just AU$5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total AU$ 204.97
Matplotlib for Python Developers
AU$60.99
Building Serverless Applications with Python
AU$75.99
Python Deep Learning Cookbook
AU$67.99
Total AU$ 204.97 Stars icon
Banner background image

Table of Contents

10 Chapters
Introduction to Matplotlib Chevron down icon Chevron up icon
Getting Started with Matplotlib Chevron down icon Chevron up icon
Decorating Graphs with Plot Styles and Types Chevron down icon Chevron up icon
Advanced Matplotlib Chevron down icon Chevron up icon
Embedding Matplotlib in GTK+3 Chevron down icon Chevron up icon
Embedding Matplotlib in Qt 5 Chevron down icon Chevron up icon
Embedding Matplotlib in wxWidgets Using wxPython Chevron down icon Chevron up icon
Integrating Matplotlib with Web Applications Chevron down icon Chevron up icon
Matplotlib in the Real World Chevron down icon Chevron up icon
Integrating Data Visualization into the Workflow Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
(2 Ratings)
5 star 0%
4 star 0%
3 star 50%
2 star 0%
1 star 50%
d Aug 02, 2018
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
This book is a good introduction to Matplotlib with a few advanced topics, however, almost half of the book is dedicated to embedding matplotlib in various GUIs. This could have been a book by itself and internal functionality of matplotlib, pandas, and seaborn could have been greatly expanded. The authors do a great job of introducing the reader to fundamental matplotlib concepts, but fail to delineate the core of Pyplot vs the use of Axes/Figure. They do not go into detail about how these two are different, how to access similar functions through the Axes object, or even what an Axes object is before using it in the advanced matplotlib section. The coverage of subplots is fairly good, but overall, the book could be improved further.
Amazon Verified review Amazon
bikiteron Nov 06, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
I thought this book will be colour printed but this book is not colour printed.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.