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Python Data Visualization Cookbook

You're reading from   Python Data Visualization Cookbook As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Length 280 pages
Edition 1st Edition
Languages
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Author (1):
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Igor Milovanovic Igor Milovanovic
Author Profile Icon Igor Milovanovic
Igor Milovanovic
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Table of Contents (15) Chapters Close

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
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 Right Plots to Understand Data 8. More on matplotlib Gems Index

Importing data from CSV


In this recipe we will work with the most common file format that one will encounter in the wild world of data, CSV. It stands for Comma Separated Values, which almost explains all the formatting there is. (There is also a header part of the file, but those values are also comma separated.)

Python has a module called csv that supports reading and writing CSV files in various dialects. Dialects are important because there is no standard CSV and different applications implement CSV in slightly different ways. A file's dialect is almost always recognizable by the first look into the file.

Getting ready

What we need for this recipe is the CSV file itself. We will use sample CSV data that you can download from ch02-data.csv.

We assume that sample datafiles is in the same folder as the code reading it.

How to do it...

The following code example demonstrates how to import data from a CSV file. We will:

  1. Open the ch02-data.csv file for reading.

  2. Read the header first.

  3. Read the rest...

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