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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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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

Introduction to epidemiology

We can define epidemiology as the study of the determinants and a distribution of health-related states. We will study how a pathogen, such as the common flu or the influenza AH1N1, is spread within a population. This is particularly important because an outbreak can cause severe human and economic losses, as with the Spanish flu of 1918, which killed 40 million people globally. Take a look at the following screenshot:

Introduction to epidemiology

We can use the Center for Disease Control (CDC) data, which is freely available from their website. With these time series, we can perform statistical methods for descriptive epidemiology or causal inference. The CDC data is obtained using typical surveys and medical reports, providing real results.

We can use the dashboard for CDC Flu Trends and its data, which is freely available from the following link:

http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html

Seasonal influenza (flu) data can be found at http://www.cdc.gov/flu/.

The epidemiology...

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