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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. Preparing Your Working Environment FREE CHAPTER 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly 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...
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