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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
Author Profile Icon Richard M. Reese
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
2. Getting Started with Data Science FREE CHAPTER 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

Creating index charts


An index chart is a line chart that shows the percentage change of something over time. Frequently, such a chart is based on a single data attribute. In the following example, we will be using the Belgian population for six decades. The data is a subset of population data found at https://ourworldindata.org/grapher/population-by-country?tab=data:

Decade

Population

1950

8639369

1960

9118700

1970

9637800

1980

9846800

1990

9969310

2000

10263618

 

We start by creating the MainApp class, which extends Application. We create a series of instance variables. The XYChart.Series class represents a series of data points for some plot. In our case, this will be for the decades and population, which we will initialize shortly. The next declaration is for the CategoryAxis and NumberAxis instances. These represent the X and Y axes respectively. The declaration for the Y axis includes range and increment values for the population. This makes the chart a bit more readable. The last declaration is a...

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