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  • Book Overview & Buying Python Data Visualization Cookbook (Second Edition)
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Python Data Visualization Cookbook (Second Edition)

Python Data Visualization Cookbook (Second Edition)

By : Igor Milovanovic, Foures, Giuseppe Vettigli
4 (6)
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Python Data Visualization Cookbook (Second Edition)

Python Data Visualization Cookbook (Second Edition)

4 (6)
By: Igor Milovanovic, Foures, Giuseppe Vettigli

Overview of this book

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.
Table of Contents (11 chapters)
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10
Index

Chapter 3. Drawing Your First Plots and Customizing Them

In this chapter, we will go into a lot more detail and present most of the possibilities of matplotlib. We will cover the following points:

  • Defining plot types – bar, line, and stacked charts
  • Drawing simple sine and cosine plots
  • Defining axis lengths and limits
  • Defining plot line styles, properties, and format strings
  • Setting ticks, labels, and grids
  • Adding legends and annotations
  • Moving spines to the center
  • Making histograms
  • Making bar charts with error bars
  • Making pie charts count
  • Plotting with filled areas
  • Making stacked plots
  • Drawing scatter plots with colored markers
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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Python Data Visualization Cookbook (Second Edition)
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