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You're reading from
Python Data Visualization Cookbook (Second Edition)
Visualize data using Python's most popular libraries
Product type
Paperback
Published in
Nov 2015
Publisher
ISBN-13
9781784396695
Length
302 pages
Edition
1st Edition
Languages
Python
Tools
Matplotlib
Concepts
Data Visualization
Table of Contents
(11) Chapters
Preface
What this book covers
What you need for this book
Who this book is for
Sections
Conventions
Reader feedback
Customer support
1. Preparing Your Working Environment
FREE CHAPTER
Introduction
Installing matplotlib, NumPy, and SciPy
Installing virtualenv and virtualenvwrapper
Installing matplotlib on Mac OS X
Installing matplotlib on Windows
Installing Python Imaging Library (PIL) for image processing
Installing a requests module
Customizing matplotlib's parameters in code
Customizing matplotlib's parameters per project
2. Knowing Your Data
Introduction
Importing data from CSV
Importing data from Microsoft Excel files
Importing data from fixed-width data files
Importing data from tab-delimited files
Importing data from a JSON resource
Exporting data to JSON, CSV, and Excel
Importing and manipulating data with Pandas
Importing data from a database
Cleaning up data from outliers
Reading files in chunks
Reading streaming data sources
Importing image data into NumPy arrays
Generating controlled random datasets
Smoothing the noise in real-world data
3. Drawing Your First Plots and Customizing Them
Introduction
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
4. More Plots and Customizations
Introduction
Setting the transparency and size of axis labels
Adding a shadow to the chart line
Adding a data table to the figure
Using subplots
Customizing grids
Creating contour plots
Filling an under-plot area
Drawing polar plots
Visualizing the filesystem tree using a polar bar
Customizing matplotlib with style
5. Making 3D Visualizations
Introduction
Creating 3D bars
Creating 3D histograms
Animating in matplotlib
Animating with OpenGL
6. Plotting Charts with Images and Maps
Introduction
Processing images with PIL
Plotting with images
Displaying images with other plots in the figure
Plotting data on a map using Basemap
Plotting data on a map using the Google Map API
Generating CAPTCHA images
7. Using the Right Plots to Understand Data
Introduction
Understanding logarithmic plots
Understanding spectrograms
Creating stem plot
Drawing streamlines of vector flow
Using colormaps
Using scatter plots and histograms
Plotting the cross correlation between two variables
Importance of autocorrelation
8. More on matplotlib Gems
Introduction
Drawing barbs
Making a box-and-whisker plot
Making Gantt charts
Making error bars
Making use of text and font properties
Rendering text with LaTeX
Understanding the difference between pyplot and OO API
9. Visualizations on the Clouds with Plot.ly
Introduction
Creating line charts
Creating bar charts
Plotting a 3D trefoil knot
Visualizing maps and bubbles
Index
Chapter 5. Making 3D Visualizations
You will learn the following recipes in this chapter:
Creating 3D bars
Creating 3D histograms
Animating in matplotlib
Animating with OpenGL
The rest of the chapter is locked
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