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Java: Data Science Made Easy

You're reading from   Java: Data Science Made Easy Data collection, processing, analysis, and more

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Product type Course
Published in Jul 2017
Publisher Packt
ISBN-13 9781788475655
Length 734 pages
Edition 1st Edition
Languages
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Authors (3):
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Alexey Grigorev Alexey Grigorev
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Alexey Grigorev
Richard M. Reese Richard M. Reese
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Richard M. Reese
Jennifer L. Reese Jennifer L. Reese
Author Profile Icon Jennifer L. Reese
Jennifer L. Reese
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Toc

Table of Contents (29) Chapters Close

Title Page
Credits
Preface
1. Module 1 FREE CHAPTER
2. Getting Started with Data Science 3. Data Acquisition 4. Data Cleaning 5. Data Visualization 6. Statistical Data Analysis Techniques 7. Machine Learning 8. Neural Networks 9. Deep Learning 10. Text Analysis 11. Visual and Audio Analysis 12. Visual and Audio Analysis 13. Mathematical and Parallel Techniques for Data Analysis 14. Bringing It All Together 15. Module 2
16. Data Science Using Java 17. Data Processing Toolbox 18. Exploratory Data Analysis 19. Supervised Learning - Classification and Regression 20. Unsupervised Learning - Clustering and Dimensionality Reduction 21. Working with Text - Natural Language Processing and Information Retrieval 22. Extreme Gradient Boosting 23. Deep Learning with DeepLearning4J 24. Scaling Data Science 25. Deploying Data Science Models 26. Bibliography

Accessing data


By now we already have spent a lot of time describing how to read and write data. But there is much more to that: data often comes in different formats such as CSV, HTML, or JSON or it can be stored in a database. Knowing how to access and process this data is important for Data Science and now we will describe in detail how to do it for the most common data formats and sources.

Text data and CSV

We already have spoken about reading text data in great detail, and it can be done, for example, using the Files helper class from the NIO API or IOUtils from Commons IO.

CSV (Comma Separated Values) is a common way to organize tabular data in plain text files. While it is possible to parse CSV files by hand, there are some corner cases, which make it a bit cumbersome. Luckily, there are nice libraries for that purpose, and one of them is Apache Commons CSV:

<dependency> 
  <groupId>org.apache.commons</groupId> 
  <artifactId>commons-csv</artifactId> 
 ...
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