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Practical Data Analysis

You're reading from   Practical Data Analysis Pandas, MongoDB, Apache Spark, and more

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Product type Paperback
Published in Sep 2016
Publisher
ISBN-13 9781785289712
Length 338 pages
Edition 2nd Edition
Languages
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Authors (2):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
Dr. Sampath Kumar Dr. Sampath Kumar
Author Profile Icon Dr. Sampath Kumar
Dr. Sampath Kumar
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started 2. Preprocessing Data FREE CHAPTER 3. Getting to Grips with 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 Diseases with Cellular Automata 10. Working with Social Graphs 11. Working with Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with Jupyter and Wakari 15. Understanding Data Processing using Apache Spark

Working with web-based visualization


A data journalist and information designer David McCandless stated in his TED talk:

"By visualizing information, we turn it into a landscape that you can explore with your eyes, a sort of information map. And when you're lost in information, an information map is kind of useful."

The World Wide Web (WWW) is an information space, which publishes and displays information via the Internet. The accessibility of information through online information services and the WWW is increasing day by day. A vast amount of information is available on websites, which can be accessed through the Internet. But the user may find the information difficult to read, and hence spends a lot of time on the web. Therefore, on websites, the information should be user friendly and reading through it should not take too much time.

Most people prefer pictures over text, so the use of graphical representation of information is increasing daily, leading us to an understanding of how...

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