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Matplotlib for Python Developers

Matplotlib for Python Developers - Second Edition

By : Aldrin Yim, Claire Chung, Allen Yu
2 (2)
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Matplotlib for Python Developers

Matplotlib for Python Developers

2 (2)
By: Aldrin Yim, Claire Chung, Allen Yu

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 (11 chapters)
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More on Pandas-Matplotlib integration


Pandas provides the DataFrame data structure commonly used in handling multivariate data. When we usually use the Pandas package for data I/O, storage, and preprocessing, it also provides a number of native integrations with Matplotlib for quick visualization. 

To create these plots, we can call df.plot(kind=plot_type)df.plot.scatter(), and so on. Here is a list of available plot types:

  • line: Line plot (default)
  • bar: Vertical bar plot
  • barh: Horizontal bar plot
  • hist: Histogram
  • box: Boxplot
  • kde: Kernel Density Estimation (KDE) plot
  • density: The same as kde
  • area: Area plot
  • pie: Pie plot

We have created some of the simpler graphs in the previous chapters. Here, we will take the density plot as an example for discussion.

Showing distribution with the KDE plot

Similar to a histogram, the KDE plot is a method to visualize the shape of data distribution. It uses kernel smoothing to create smooth curves and is often combined with a histogram. It is useful in exploratory...

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Matplotlib for Python Developers
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