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Mastering Java for Data Science

You're reading from   Mastering Java for Data Science Analytics and more for production-ready applications

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781782174271
Length 364 pages
Edition 1st Edition
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Author (1):
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Alexey Grigorev Alexey Grigorev
Author Profile Icon Alexey Grigorev
Alexey Grigorev
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Exploratory data analysis in Java

Exploratory Data Analysis is about taking a dataset and extracting the most important information from it, in such a way that it is possible to get an idea of what the data looks like. This includes two main parts: summarization and visualization.

The summarization step is very helpful for understanding data. For numerical variables, in this step we calculate the most important sample statistics: 

  • The extremes (the minimal and the maximal values)
  • The mean value, or the sample average
  • The standard deviation, which describes the spread of the data

Often we consider other statistics, such as the median and the quartiles (25% and 75%).

As we have already seen in the previous chapter, Java offers a great set of tools for data preparation. The same set of tools can be used for EDA, and especially for creating summaries.

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