Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

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 (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Importing data from tab-delimited files


Another very common format of flat datafile is the tab-delimited file. This can also come from an Excel export but can be the output of some custom software we must get our input from.

The good thing is that usually this format can be read in almost the same way as CSV files as the Python module csv supports the so-called dialects that enable us to use the same principles to read variations of similar file formats, one of them being the tab- delimited format.

Getting ready

Now you're already able to read CSV files. If not, please refer to the Importing data from CSV recipe first.

How to do it...

We will reuse the code from the Importing data from CSV recipe, where all we need to change is the dialect we are using as shown in the following code:

import csv

filename = 'ch02-data.tab'

data = []
try:
    with open(filename) as f:
        reader = csv.reader(f, dialect=csv.excel_tab)
       header = reader.next()
       data = [row for row in reader]
except...