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Home > Data > Data Analysis > Java Data Science Cookbook
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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Publication date : Mar 28, 2017
Length: 372 pages
Edition : 1st
Language : English
ISBN-13 : 9781787122536
Category :
Data
Languages :
Java
Concepts :
Data Analysis
Tools :
Weka

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Length: 372 pages
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Category :
Data
Languages :
Java
Concepts :
Data Analysis
Tools :
Weka

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Table of Contents

9 Chapters
1. Obtaining and Cleaning Data Chevron down icon Chevron up icon
1. Obtaining and Cleaning Data
Introduction
Retrieving all filenames from hierarchical directories using Java
Retrieving all filenames 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 (CSV) Files using Univocity
Parsing Tab Separated Value (TSV) file 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 a MySQL database
2. Indexing and Searching Data Chevron down icon Chevron up icon
2. Indexing and Searching Data
Introduction
Indexing data with Apache Lucene
Searching indexed data with Apache Lucene
3. Analyzing Data Statistically Chevron down icon Chevron up icon
3. Analyzing Data Statistically
Introduction
Generating descriptive statistics
Generating summary statistics
Generating summary statistics from multiple distributions
Computing frequency distribution
Counting word frequency in a string
Counting word frequency in a string using Java 8
Computing simple regression
Computing ordinary least squares regression
Computing generalized least squares regression
Calculating covariance of two sets of data points
Calculating Pearson's correlation of two sets of data points
Conducting a paired t-test
Conducting a Chi-square test
Conducting the one-way ANOVA test
Conducting a Kolmogorov-Smirnov test
4. Learning from Data - Part 1 Chevron down icon Chevron up icon
4. Learning from Data - Part 1
Introduction
Creating and saving an Attribute-Relation File Format (ARFF) file
Cross-validating a machine learning model
Classifying unseen test data
Classifying unseen test data with a filtered classifier
Generating linear regression models
Generating logistic regression models
Clustering data points using the KMeans algorithm
Clustering data from classes
Learning association rules from data
Selecting features/attributes using the low-level method, the filtering method, and the meta-classifier method
5. Learning from Data - Part 2 Chevron down icon Chevron up icon
5. Learning from Data - Part 2
Introduction
Applying machine learning on data using Java Machine Learning (Java-ML) library
Classifying data points using the Stanford classifier
Classifying data points using Massive Online Analysis (MOA)
Classifying multilabeled data points using Mulan
6. Retrieving Information from Text Data Chevron down icon Chevron up icon
6. Retrieving Information from Text Data
Introduction
Detecting tokens (words) using Java
Detecting sentences using Java
Detecting tokens (words) and sentences using OpenNLP
Retrieving lemma, part-of-speech, and recognizing named entities from tokens using Stanford CoreNLP
Measuring text similarity with Cosine Similarity measure using Java 8
Extracting topics from text documents using Mallet
Classifying text documents using Mallet
Classifying text documents using Weka
7. Handling Big Data Chevron down icon Chevron up icon
7. Handling Big Data
Introduction
Training an online logistic regression model using Apache Mahout
Applying an online logistic regression model using Apache Mahout
Solving simple text mining problems with Apache Spark
Clustering using KMeans algorithm with MLib
Creating a linear regression model with MLib
Classifying data points with Random Forest model using MLib
8. Learn Deeply from Data Chevron down icon Chevron up icon
8. Learn Deeply from Data
Introduction
Creating a Word2vec neural net using Deep Learning for Java (DL4j)
Creating a Deep Belief neural net using Deep Learning for Java (DL4j)
Creating a deep autoencoder using Deep Learning for Java (DL4j)
9. Visualizing Data Chevron down icon Chevron up icon
9. Visualizing Data
Introduction
Plotting a 2D sine graph
Plotting histograms
Plotting a bar chart
Plotting box plots or whisker diagrams
Plotting scatter plots
Plotting donut plots
Plotting area graphs

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About the author

Profile icon Shams
Shams
Rushdi Shams has a Ph.D. on Application of machine learning in Natural Language Processing (NLP) problem areas from Western University, Canada. Before starting work as a machine learning and NLP specialist in the industry, he was engaged in teaching undergrad and grad courses. He has been successfully maintaining his YouTube channel named "Learn with Rushdi" for learning computer technologies.
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Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
What is custom duty/charge? Chevron down icon Chevron up icon

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order? Chevron down icon Chevron up icon

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela