We have demonstrated how to draw line plots and scatter plots in the previous chapter. We know that scatter plots are made up of dots denoting each data point, whereas line plots are generated by joining dots of data points. In Matplotlib, the marker to mark the location of data points can be customized to have different styles, including shape, size, color, and transparency. Similarly, the line segments joining the data points as well as different 2D lines that share the same class in the object-oriented Matplotlib structure can have their styles adjusted, as briefly demonstrated in the grid section of the previous chapter. Adjusting marker and line styles is useful in making the data series more distinguishable, and sometimes for aesthetic considerations. In this section, we will go through the details and implementation methods of marker and line styles in Matplotlib.
Matplotlib for Python Developers - Second Edition
By :
Matplotlib for Python Developers - Second Edition
By:
Overview of this book
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.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Free Chapter
Introduction to Matplotlib
Getting Started with Matplotlib
Decorating Graphs with Plot Styles and Types
Advanced Matplotlib
Embedding Matplotlib in GTK+3
Embedding Matplotlib in Qt 5
Embedding Matplotlib in wxWidgets Using wxPython
Integrating Matplotlib with Web Applications
Matplotlib in the Real World
Integrating Data Visualization into the Workflow
Index
Customer Reviews