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Java Data Science Cookbook

You're reading from   Java Data Science Cookbook Explore the power of MLlib, DL4j, Weka, and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787122536
Length 372 pages
Edition 1st Edition
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Author (1):
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Rushdi Shams Rushdi Shams
Author Profile Icon Rushdi Shams
Rushdi Shams
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Toc

Table of Contents (10) Chapters Close

Preface 1. Obtaining and Cleaning Data FREE CHAPTER 2. Indexing and Searching Data 3. Analyzing Data Statistically 4. Learning from Data - Part 1 5. Learning from Data - Part 2 6. Retrieving Information from Text Data 7. Handling Big Data 8. Learn Deeply from Data 9. Visualizing Data

Parsing Tab Separated Value (TSV) file using Univocity

Unlike CSV files, Tab Separated Value (TSV) files contain data that is separated by tab delimiters. This recipe shows you how to retrieve data points from TSV files.

Getting ready

In order to perform this recipe, we will require the following:

  1. Download the Univocity JAR file from http://oss.sonatype.org/content/repositories/releases/com/univocity/univocity-parsers/2.2.1/univocity-parsers-2.2.1.jar. Include the JAR file in your project in Eclipse an external library.
  2. Create a TSV file from the following data using Notepad. The extension of the file should be .tsv. You save the file as C:/testTSV.tsv:
Year    Make    Model   Description Price 
1997    Ford    E350    ac, abs, moon   3000.00 
1999    Chevy   Venture "Extended Edition"      4900.00 
1996    Jeep    Grand Cherokee  MUST SELL!nair, moon roof, loaded  4799.00 
1999    Chevy   Venture "Extended Edition, Very Large"      5000.00 
        Venture "Extended Edition"      4900.00 

How to do it...

  1. Create a method named parseTsv(String) that takes the name of the file as a String argument:
            public void parseTsv(String fileName){ 
    
  2. The line separator for the TSV file in this recipe is a newline character or n. To set this character as the line separator, modify the settings:
            settings.getFormat().setLineSeparator("n"); 
    
  3. Using these settings, create a TSV parser:
            TsvParser parser = new TsvParser(settings); 
    
  4. Parse all rows of the TSV file at once as follows:
            List<String[]> allRows = parser.parseAll(new File(fileName)); 
    
  5. Iterate over the list object to print/process the rows as follows:
            for (int i = 0; i < allRows.size(); i++){ 
                     System.out.println(Arrays.asList(allRows.get(i))); 
                   } 
    
  6. Finally, close the method:
        } 

The full method with the driver method in a class will look like the following:

import java.io.File; 
import java.util.Arrays; 
import java.util.List; 
 
import com.univocity.parsers.tsv.TsvParser; 
import com.univocity.parsers.tsv.TsvParserSettings; 
 
public class TestTsv { 
   public void parseTsv(String fileName){ 
       TsvParserSettings settings = new TsvParserSettings(); 
       settings.getFormat().setLineSeparator("n"); 
       TsvParser parser = new TsvParser(settings); 
       List<String[]> allRows = parser.parseAll(new File(fileName)); 
       for (int i = 0; i < allRows.size(); i++){ 
         System.out.println(Arrays.asList(allRows.get(i))); 
       } 
   } 
} 
You have been reading a chapter from
Java Data Science Cookbook
Published in: Mar 2017
Publisher: Packt
ISBN-13: 9781787122536
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