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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
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Concepts
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis FREE CHAPTER 2. Data Preprocessing 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Data ranking


Another common way to present small datasets is to rank the data, assigning ordinal labels (first, second, third, and so on) to the data points. This can be done by sorting the data on the key field.

Figure 3-17 shows an Excel worksheet with data on students' grade-point averages (GPAs).

Figure 3-17. Excel data

To rank these, select Tools | Data Analysis | Rank and Percentile to bring up the Moving Average dialog box:

Figure 3-18. Ranking scores in Excel

Here, we have identified cells B1 to B17 as holding the data, with the first cell being a label. The output is to start in cell D1. The results are shown in the following screenshot:

Figure 3-19. Results from Excel ranking

Column D contains the (relative) index of the record being ranked. For example, cells D3-G3 show the record of the third student in the original list (in column A) with name Cohen: that student ranks second, at the 86th percentile.

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