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by Chad Adams
Learning Python Data Visualization
Learning Python Data Visualization
Table of Contents
Learning Python Data Visualization
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Setting Up Your Development Environment
Introduction
Setting up Python on Windows
Installation
Exploring the Python installation in Windows
Python editors
Setting up Python on Mac OS X
Setting up Python on Ubuntu
Summary
2. Python Refresher
Python basics
Importing modules and libraries
Input and output
Generating an image
Creating SVG graphics using svgwrite
For Windows users using VSPT
For Eclipse or other editors on Windows
For Eclipse on Mac and Linux
Summary
3. Getting Started with pygal
Why use pygal?
Installing pygal using pip
Installing pygal using Python Tools for Visual Studio
Building a line chart
Stacked line charts
Simple bar charts
Stacked bar charts
Horizontal bar charts
XY charts
Scatter plots
DateY charts
Summary
4. Advanced Charts
Pie charts
Stacked pie charts
Radar charts
Box plots
Dot charts
Funnel charts
Gauge charts
Pyramid charts
Worldmap charts
Summary
5. Tweaking pygal
Country charts
Parameters
Legend at the bottom
Legend settings
Label settings
Chart title settings
Displaying no data
pygal themes
Summary
6. Importing Dynamic Data
Pulling data from the Web
The XML refresher
RSS and the ATOM
Understanding HTTP
Using HTTP in Python
Parsing XML in Python with HTTP
About JSON
Parsing JSON in Python with HTTP
About JSONP
JSONP with Python
Summary
7. Putting It All Together
Chart usage for a blog
Getting our data in order
Converting date strings to dates
Using strptime
Saving the output as a counted array
Counting the array
Python modules
Building the main method
Modifying our RSS to return values
Building our chart module
Building a portable configuration for our chart
Setting up our chart for data
Configuring our main function to pass data
Project improvements
Summary
8. Further Resources
The matplotlib library
Installing the matplotlib library
matplotlib's library download page
Creating simple matplotlib charts
Plotly
Pyvot
Summary
A. References and Resources
Links for help and support
Charting libraries
Editors and IDEs for Python
Other libraries and Python alternative shells
Index
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Prev
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Cover
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Learning Python Data Visualization
Table of Contents
Learning Python Data Visualization
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Setting Up Your Development Environment
Introduction
Setting up Python on Windows
Installation
Exploring the Python installation in Windows
Python editors
Setting up Python on Mac OS X
Setting up Python on Ubuntu
Summary
2. Python Refresher
Python basics
Importing modules and libraries
Input and output
Generating an image
Creating SVG graphics using svgwrite
For Windows users using VSPT
For Eclipse or other editors on Windows
For Eclipse on Mac and Linux
Summary
3. Getting Started with pygal
Why use pygal?
Installing pygal using pip
Installing pygal using Python Tools for Visual Studio
Building a line chart
Stacked line charts
Simple bar charts
Stacked bar charts
Horizontal bar charts
XY charts
Scatter plots
DateY charts
Summary
4. Advanced Charts
Pie charts
Stacked pie charts
Radar charts
Box plots
Dot charts
Funnel charts
Gauge charts
Pyramid charts
Worldmap charts
Summary
5. Tweaking pygal
Country charts
Parameters
Legend at the bottom
Legend settings
Label settings
Chart title settings
Displaying no data
pygal themes
Summary
6. Importing Dynamic Data
Pulling data from the Web
The XML refresher
RSS and the ATOM
Understanding HTTP
Using HTTP in Python
Parsing XML in Python with HTTP
About JSON
Parsing JSON in Python with HTTP
About JSONP
JSONP with Python
Summary
7. Putting It All Together
Chart usage for a blog
Getting our data in order
Converting date strings to dates
Using strptime
Saving the output as a counted array
Counting the array
Python modules
Building the main method
Modifying our RSS to return values
Building our chart module
Building a portable configuration for our chart
Setting up our chart for data
Configuring our main function to pass data
Project improvements
Summary
8. Further Resources
The matplotlib library
Installing the matplotlib library
matplotlib's library download page
Creating simple matplotlib charts
Plotly
Pyvot
Summary
A. References and Resources
Links for help and support
Charting libraries
Editors and IDEs for Python
Other libraries and Python alternative shells
Index
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