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Java Data Science Cookbook
Java Data Science Cookbook

Java Data Science Cookbook: Explore the power of MLlib, DL4j, Weka, and more

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Java Data Science Cookbook

Chapter 1. Obtaining and Cleaning Data

In this chapter, we will cover the following recipes:

  • Retrieving all file names from hierarchical directories using Java
  • Retrieving all file names from hierarchical directories using Apache Commons IO
  • Reading contents from text files all at once using Java 8
  • Reading contents from text files all at once using Apache Commons IO
  • Extracting PDF text using Apache Tika
  • Cleaning ASCII text files using Regular Expressions
  • Parsing Comma Separated Value files using Univocity
  • Parsing Tab Separated Value files using Univocity
  • Parsing XML files using JDOM
  • Writing JSON files using JSON.simple
  • Reading JSON files using JSON.simple
  • Extracting web data from a URL using JSoup
  • Extracting web data from a website using Selenium Webdriver
  • Reading table data from MySQL database

Introduction

Every data scientist needs to deal with data that is stored on disks in several formats, such as ASCII text, PDF, XML, JSON, and so on. Also, data can be stored in database tables. The first and foremost task for a data scientist before doing any analysis is to obtain data from these data sources and of these formats, and apply data-cleaning techniques to get rid of noises present in them. In this chapter, we will see recipes to accomplish this important task.

We will be using external Java libraries (Java archive files or simply JAR files) not only for this chapter but throughout the book. These libraries are created by developers or organizations to make everybody's life easier. We will be using Eclipse IDE for code development, preferably on the Windows platform, and execution throughout the book. Here is how you can include any external JAR file, and in many recipes, where I instruct you to include external JAR files into your project, this is what you need to do.

You can add a JAR file in a project in Eclipse by right-clicking on the Project | Build Path | Configure Build Path. Under the Libraries tab, click on Add External JARs..., and select the external JAR file(s) that you are going to use for a particular project:

Introduction

Retrieving all filenames from hierarchical directories using Java

This recipe (and the following) is for the data scientist who wants to retrieve the file paths and names (for some future analysis) from a complex directory structure that contains numerous directories and files inside a root directory.

Getting ready

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

  1. Create directories within directories (as many layers as you want).
  2. Create text files in some of these directories while leaving some directories empty for more excitement.

How to do it...

  1. We are going to create a static method that takes a File argument, which is eventually the root directory or the directory to start with. The method will return a set of files that are found within this root directory (and in all other subsequent directories):
            public static Set<File> listFiles(File rootDir) {  
    
  2. First, create a HashSet that will contain the file information:
            Set<File> fileSet = new HashSet<File>(); 
    
  3. Once the HashSet is created, we need to check whether the root directory or the directories within it are null. For such cases, we do not need to proceed further:
            if (rootDir == null || rootDir.listFiles() == null){ 
                         return fileSet; 
               } 
    
  4. We consider one directory (or file) from the root directory at a time and check whether we are dealing with a file or with a directory. In the case of a file, we add that to our HashSet. In the case of a directory, we recursively call this method again by sending the path and name of the directory:
            for (File fileOrDir : rootDir.listFiles()) { 
                         if (fileOrDir.isFile()){ 
                           fileSet.add(fileOrDir); 
                         } 
                         else{ 
                           fileSet.addAll(listFiles(fileOrDir)); 
                         } 
                 } 
    
  5. Finally, we return the HashSet to the caller of this method:
           return fileSet; 
              } 
    

    The complete method, with the class and the driver method to run it, is as follows:

    import java.io.File; 
    import java.util.HashSet; 
    import java.util.Set; 
     
    public class TestRecursiveDirectoryTraversal { 
       public static void main(String[] args){ 
          System.out.println(listFiles(new File("Path for root 
              directory")).size()); 
       } 
        
       public static Set<File> listFiles(File rootDir) { 
           Set<File> fileSet = new HashSet<File>(); 
           if(rootDir == null || rootDir.listFiles()==null){ 
               return fileSet; 
           } 
           for (File fileOrDir : rootDir.listFiles()) { 
                 if (fileOrDir.isFile()){ 
                   fileSet.add(fileOrDir); 
                 } 
                 else{ 
                   fileSet.addAll(listFiles(fileOrDir)); 
                 } 
         } 
     
           return fileSet; 
       } 
    } 
    

Note

Note the use of HashSet to store the paths and names of the files. This means that we will not have any duplicates since the Set data structures in Java do not contain duplicate entries.

Retrieving all filenames from hierarchical directories using Apache Commons IO

Listing of file names in hierarchical directories can be done recursively as demonstrated in the previous recipe. However, this can be done in a much easier and convenient way and with less coding using the Apache Commons IO library.

Getting ready

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

  1. In this recipe, we will be using a Java library from Apache named Commons IO. Throughout the book, we will be using version 2.5. Download the JAR file of your choice from here: https://commons.apache.org/proper/commons-io/download_io.cgi
  2. Include the JAR file in your project an external JAR in Eclipse.

How to do it...

  1. Create a method that takes the root directory in the hierarchy of directories as input:
            public void listFiles(String rootDir){ 
    
  2. Create a file object with the root directory name:
            File dir = new File(rootDir); 
    
  3. The FileUtils class of the Apache Commons library contains a method named listFiles(). Use this method to retrieve all the file names, and put the names in a list variable with <File> generics. Use TrueFileFilter.INSTANCE to match all directories:
            List<File> files = (List<File>) FileUtils.listFiles(dir,   
              TrueFileFilter.INSTANCE, TrueFileFilter.INSTANCE); 
    
  4. The file names can be displayed on the standard output as follows. As we now have the names in a list, we have a means to process the data in these files further:
            for (File file : files) { 
               System.out.println("file: " + file.getAbsolutePath()); 
            } 
    
  5. Close the method:
           } 
    

    The method in this recipe, the class for it, and the driver method to run it are as follows:

    import java.io.File; 
    import java.util.List; 
    import org.apache.commons.io.FileUtils; 
    import org.apache.commons.io.filefilter.TrueFileFilter; 
     
    public class FileListing{ 
       public static void main (String[] args){ 
          FileListing fileListing = new FileListing(); 
          fileListing.listFiles("Path for the root directory here"); 
       } 
       public void listFiles(String rootDir){ 
          File dir = new File(rootDir); 
     
          List<File> files = (List<File>) FileUtils.listFiles(dir,  
            TrueFileFilter.INSTANCE, TrueFileFilter.INSTANCE); 
          for (File file : files) { 
             System.out.println("file: " + file.getAbsolutePath()); 
          } 
       } 
    

Tip

If you want to list files with some particular extensions, there is a method in Apache Commons library called listFiles, too. However, the parameters are different; the method takes three parameters, namely, file directory, String[] extensions, boolean recursive. Another interesting method in this library is listFilesAndDirs (File directory, IOFileFilter fileFilter, IOFileFilter dirFilter) if someone is interested in listing not only files but also directories. Detailed information can be found at https://commons.apache.org/proper/commons-io/javadocs/.

Reading contents from text files all at once using Java 8

On many occasions, data scientists have their data in text format. There are many different ways to read text file contents, and they each have their own pros and cons: some of them consume time and memory, while some are fast and do not require much computer memory; some read the text contents all at once, while some read text files line by line. The choice depends on the task at hand and a data scientist's approach to that task.

This recipe demonstrates how to read text file contents all at once using Java 8.

How to do it...

  1. First, create a String object to hold the path and name of the text file you are going to read:
            String file = "C:/dummy.txt";  
    
  2. Using the get() method of the Paths class, we get to the path of the file we are trying to read. The parameter for this method is the String object that points to the name of the file. The output of this method is fed to another method named lines(), which is in the Files class. This method reads all lines from a file as a Stream, and therefore, the output of this method is directed to a Stream variable. Because our dummy.txt file contains string data, the generics of the Stream variable is set to String.

The entire process of reading needs a try...catch block for attempts such as reading a file that does not exist or damaged and so on.

The following code segment displays the contents of our dummy.txt file. The stream variable contains the lines of the text file, and therefore, the forEach() method of the variable is used to display each line content:

        try (Stream<String> stream = Files.lines(Paths.get(file))) { 
        stream.forEach(System.out::println); } catch (IOException e) { 
        System.out.println("Error reading " +  file.getAbsolutePath()); 
        } 
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Key benefits

  • This book provides modern recipes in small steps to help an apprentice cook become a master chef in data science
  • Use these recipes to obtain, clean, analyze, and learn from your data
  • Learn how to get your data science applications to production and enterprise environments effortlessly

Description

If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to. This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data. Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more - things that will come in handy at work.

Who is this book for?

This book is for Java developers who are familiar with the fundamentals of data science and want to improve their skills to become a pro.

What you will learn

  • Find out how to clean and make datasets ready so you can acquire actual insights by removing noise and outliers
  • Develop the skills to use modern machine learning techniques to retrieve information and transform data to knowledge. retrieve information from large amount of data in text format.
  • Familiarize yourself with cutting-edge techniques to store and search large volumes of data and retrieve information from large amounts of data in text format
  • Develop basic skills to apply big data and deep learning technologies on large volumes of data
  • Evolve your data visualization skills and gain valuable insights from your data
  • Get to know a step-by-step formula to develop an industry-standard, large-scale, real-life data product
  • Gain the skills to visualize data and interact with users through data insights
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Table of Contents

9 Chapters
1. Obtaining and Cleaning Data Chevron down icon Chevron up icon
2. Indexing and Searching Data Chevron down icon Chevron up icon
3. Analyzing Data Statistically Chevron down icon Chevron up icon
4. Learning from Data - Part 1 Chevron down icon Chevron up icon
5. Learning from Data - Part 2 Chevron down icon Chevron up icon
6. Retrieving Information from Text Data Chevron down icon Chevron up icon
7. Handling Big Data Chevron down icon Chevron up icon
8. Learn Deeply from Data Chevron down icon Chevron up icon
9. Visualizing Data Chevron down icon Chevron up icon
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