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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Product type Paperback

Published in Oct 2013

Publisher Packt

ISBN-13 9781783280995

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

NLTK

Concepts

Data Analysis

Author (1):

Hector Cuesta

View More author details

Table of Contents (24) Chapters

Practical Data Analysis

Credits

Foreword

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

1. Getting Started FREE CHAPTER

2. Working with Data

3. Data Visualization

4. Text Classification

5. Similarity-based Image Retrieval

6. Simulation of Stock Prices

7. Predicting Gold Prices

8. Working with Support Vector Machines

9. Modeling Infectious Disease with Cellular Automata

10. Working with Social Graphs

11. Sentiment Analysis of Twitter Data

12. Data Processing and Aggregation with MongoDB

13. Working with MapReduce

14. Online Data Analysis with IPython and Wakari

Setting Up the Infrastructure

Index

Introduction to image processing with PIL

The goal of this chapter is to present some of the preinstalled capabilities of Wakari. In this section, we will explore some of the basic functions of the PIL (Python Image Library) such as histogram, filters, operations, and transformations. We have already installed and used PIL in Chapter 5, Similarity-based Image Retrieval.

First, we will upload the images 412.jpg (Dinosaur) and 826.jpg (Land) to the path (see the arrow in the following screenshot). The images came from the Caltech-256 images-dataset used in the Chapter 5, Similarity-based Image Retrieval.

Opening an image

The first thing we need to start working on is importing the PIL and pylab modules. Next, we will use the open method of the Image object. Finally, we will visualize the image with the imshow method of pylab. In the following screenshot, we may see the output of the code:

Tip

You can find more information about PIL from http://www.pythonware.com/products/pil/.

Image histogram

A histogram...

The rest of the chapter is locked