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Java for Data Science

Examine the techniques and Java tools supporting the growing field of data science

Richard M. Reese

Jennifer L. Reese

BIRMINGHAM - MUMBAI

Java for Data Science

Copyright © 2017 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

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First published: January 2017

Production reference: 1050117

Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.

ISBN 978-1-78528-011-5

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Authors

Richard M. Reese

Jennifer L. Reese

Reviewers

Walter Molina

Shilpi Saxena

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About the Authors

Richard M. Reese has worked in both industry and academics. For 17 years, he worked in the telephone and aerospace industries, serving in several capacities, including research and development, software development, supervision, and training. He currently teaches at Tarleton State University, where he has the opportunity to apply his years of industry experience to enhance his teaching.

Richard has written several Java books and a C Pointer book. He uses a concise and easy-tofollow approach to topics at hand. His Java books have addressed EJB 3.1, updates to Java 7 and 8, certification, jMonkeyEngine, natural language processing, functional programming, and networks.

Richard would like to thank his wife, Karla, for her continued support, and to the staff of Packt Publishing for their work in making this a better book.

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to highschool students. Her research interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education.

She previously worked as a software engineer developing software for county- and districtlevel government offices throughout Texas. In her free time she enjoys reading, cooking, and traveling especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.

I would like to thank Dad for his inspiration and guidance, Mom for her patience and perspective, and Jace for his support and always believing in me.

About the Reviewers

Walter Molina is a UI and UX developer from Villa Mercedes, San Luis, Argentina. His skills include, but are not limited to, HTML5, CSS3, and JavaScript. He uses these technologies at a Jedi/ninja level (along with a plethora of JavaScript libraries) in his daily work as a frontend developer at Tachuso, a creative content agency. He holds a bachelor's degree in computer science and is a member of the School of Engineering at local National University, where he teaches programming skills to second- and third-year students. His LinkedIn profile is https://ar.linkedin.com/in/waltermolina.

Shilpi Saxena is an IT professional and also a technology evangelist. She is an engineer who has had exposure to various domains (IOT and cloud computing space, healthcare, telecom, hiring, and manufacturing). She has experience in all the aspects of conception and execution of enterprise solutions. She has been architecting, managing, and delivering solutions in the big data space for the last 3 years; she also handles a high-performance and geographically distributed team of elite engineers.

Shilpi has more than 14 years (3 years in the big data space) of experience in the development and execution of various facets of enterprise solutions both in the products and services dimensions of the software industry. An engineer by degree and profession, she has worn various hats, such as developer, technical leader, product owner, tech manager, and so on, and has seen all the flavors that the industry has to offer. She has architected and worked through some of the pioneers' production implementations in big data on Storm and Impala with autoscaling in AWS.

Shilpi has also authored Real-time Analytics with Storm and Cassandra (https://www.pack tpub.com/big-data-and-business-intelligence/learning-real-time-analytics-sto rm-and-cassandra) and Real time Big Data Analytics (https://www.packtpub.com/big-d ata-and-business-intelligence/real-time-big-data-analytics) with Packt Publishing.

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Preface

In this book, we examine Java-based approaches to the field of data science. Data science is a broad topic and includes such subtopics as data mining, statistical analysis, audio and video analysis, and text analysis. A number of Java APIs provide support for these topics. The ability to apply these specific techniques allows for the creation of new, innovative applications able to handle the vast amounts of data available for analysis.

This book takes an expansive yet cursory approach to various aspects of data science. A brief introduction to the field is presented in the first chapter. Subsequent chapters cover significant aspects of data science, such as data cleaning and the application of neural networks. The last chapter combines topics discussed throughout the book to create a comprehensive data science application.

What this book covers

Chapter 1, Getting Started with Data Science, provides an introduction to the technologies covered by the book. A brief explanation of each technology is given, followed by a short overview and demonstration of the support Java provides.

Chapter 2, Data Acquisition, demonstrates how to acquire data from a number of sources, including Twitter, Wikipedia, and YouTube. The first step of a data science application is to acquire data.

Chapter 3, Data Cleaning, explains that once data has been acquired, it needs to be cleaned. This can involve such activities as removing stop words, validating the data, and data conversion.

Chapter 4, Data Visualization, shows that while numerical processing is a critical step in many data science tasks, people often prefer visual depictions of the results of analysis. This chapter demonstrates various Java approaches to this task.

Chapter 5, Statistical Data Analysis Techniques, reviews basic statistical techniques, including regression analysis, and demonstrates how various Java APIs provide statistical support. Statistical analysis is key to many data analysis tasks.

Chapter 6, Machine Learning, covers several machine learning algorithms, including decision trees and support vector machines. The abundance of available data provides an opportunity to apply machine learning techniques.

Chapter 7, Neural Networks, explains that neural networks can be applied to solve a variety of data science problems. In this chapter, we explain how they work and demonstrate the use of several different types of neural networks.

Chapter 8, Deep Learning, shows that deep learning algorithms are often described as multilevel neural networks. Java provides significant support in this area, and we will illustrate the use of this approach.

Chapter 9, Text Analysis, explains that significant portions of available datasets exist in textual formats. The field of natural language processing has advanced considerably and is frequently used in data science applications. We demonstrate various Java APIs used to support this type of analysis.

Chapter 10, Visual and Audio Analysis, tells us that data science is not restricted to text processing. Many social media sites use visual data extensively. This chapter illustrates the Java supports available for this type of analysis.

Chapter 11, Mathematical and Parallel Techniques for Data Analysis, investigates the support provided for low-level math operations and how they can be supported in a multiple processor environment. Data analysis, at its heart, necessitates the ability to manipulate and analyze large quantities of numeric data.

Chapter 12, Bringing It All Together, examines how the integration of the various technologies introduced in this book can be used to create a data science application. This chapter begins with data acquisition and incorporates many of the techniques used in subsequent chapters to build a complete application.

What you need for this book

Many of the examples in the book use Java 8 features. There are a number of Java APIs demonstrated, each of which is introduced before it is applied. An IDE is not required but is desirable.

Who this book is for

This book is aimed at experienced Java programmers who are interested in gaining a better understanding of the field of data science and how Java supports the underlying techniques. No prior experience in the field is needed.

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A block of code is set as follows: Voice[] voices = voiceManager.getVoices(); for (Voice v : voices) { out.println(v); }

Any command-line input or output is written as follows:

Name: kevin16

Description: default 16-bit diphone voice

Organization: cmu

Age: YOUNGER_ADULT

Gender: MALE

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Select the Images category and then filter for Labeled for reuse. "

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Tips and tricks appear like this.

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1 Getting Started with Data Science

Data science is not a single science as much as it is a collection of various scientific disciplines integrated for the purpose of analyzing data. These disciplines include various statistical and mathematical techniques, including:

Computer science

Data engineering

Visualization

Domain-specific knowledge and approaches

With the advent of cheaper storage technology, more and more data has been collected and stored permitting previously unfeasible processing and analysis of data. With this analysis came the need for various techniques to make sense of the data. These large sets of data, when used to analyze data and identify trends and patterns, become known as big data.

This in turn gave rise to cloud computing and concurrent techniques such as map-reduce, which distributed the analysis process across a large number of processors, taking advantage of the power of parallel processing.

The process of analyzing big data is not simple and evolves to the specialization of developers who were known as data scientists. Drawing upon a myriad of technologies and expertise, they are able to analyze data to solve problems that previously were either not envisioned or were too difficult to solve.

Early big data applications were typified by the emergence of search engines capable of more powerful and accurate searches than their predecessors. For example, AltaVista was an early popular search engine that was eventually superseded by Google. While big data applications were not limited to these search engine functionalities, these applications laid the groundwork for future work in big data.

The term, data science, has been used since 1974 and evolved over time to include statistical analysis of data. The concepts of data mining and data analytics have been associated with data science. Around 2008, the term data scientist appeared and was used to describe a person who performs data analysis. A more in-depth discussion of the history of data science can be found at http://www.forbes.com/sites/gilpress/2013/05/28/a-very-sh ort-history-of-data-science/#3d9ea08369fd.

This book aims to take a broad look at data science using Java and will briefly touch on many topics. It is likely that the reader may find topics of interest and pursue these at greater depth independently. The purpose of this book, however, is simply to introduce the reader to the significant data science topics and to illustrate how they can be addressed using Java.

There are many algorithms used in data science. In this book, we do not attempt to explain how they work except at an introductory level. Rather, we are more interested in explaining how they can be used to solve problems. Specifically, we are interested in knowing how they can be used with Java.

Problems solved using data science

The various data science techniques that we will illustrate have been used to solve a variety of problems. Many of these techniques are motivated to achieve some economic gain, but they have also been used to solve many pressing social and environmental problems. Problem domains where these techniques have been used include finance, optimizing business processes, understanding customer needs, performing DNA analysis, foiling terrorist plots, and finding relationships between transactions to detect fraud, among many other data-intensive problems.

Data mining is a popular application area for data science. In this activity, large quantities of data are processed and analyzed to glean information about the dataset, to provide meaningful insights, and to develop meaningful conclusions and predictions. It has been used to analyze customer behavior, detecting relationships between what may appear to be unrelated events, and to make predictions about future behavior.

Machine learning is an important aspect of data science. This technique allows the computer to solve various problems without needing to be explicitly programmed. It has been used in self-driving cars, speech recognition, and in web searches. In data mining, the data is extracted and processed. With machine learning, computers use the data to take some sort of action.

Understanding the data science problem solving approach

Data science is concerned with the processing and analysis of large quantities of data to create models that can be used to make predictions or otherwise support a specific goal. This process often involves the building and training of models. The specific approach to solve a problem is dependent on the nature of the problem. However, in general, the following are the high-level tasks that are used in the analysis process:

Acquiring the data: Before we can process the data, it must be acquired. The data is frequently stored in a variety of formats and will come from a wide range of data sources.

Cleaning the data: Once the data has been acquired, it often needs to be converted to a different format before it can be used. In addition, the data needs to be processed, or cleaned, so as to remove errors, resolve inconsistencies, and otherwise put it in a form ready for analysis.

Analyzing the data: This can be performed using a number of techniques including:

Statistical analysis: This uses a multitude of statistical approaches to provide insight into data. It includes simple techniques and more advanced techniques such as regression analysis.

AI analysis: These can be grouped as machine learning, neural networks, and deep learning techniques:

Machine learning approaches are characterized by programs that can learn without being specifically programmed to complete a specific task

Neural networks are built around models patterned after the neural connection of the brain

Deep learning attempts to identify higher levels of abstraction within a set of data

Text analysis: This is a common form of analysis, which works with natural languages to identify features such as the names of people and places, the relationship between parts of text, and the implied meaning of text.

Data visualization: This is an important analysis tool. By displaying the data in a visual form, a hard-to-understand set of numbers can be more readily understood.

Video, image, and audio processing and analysis: This is a more specialized form of analysis, which is becoming more common as better analysis techniques are discovered and faster processors become available. This is in contrast to the more common text processing and analysis tasks.

Complementing this set of tasks is the need to develop applications that are efficient. The introduction of machines with multiple processors and GPUs contributes significantly to the end result.

While the exact steps used will vary by application, understanding these basic steps provides the basis for constructing solutions to many data science problems.

Using Java to support data science

Java and its associated third-party libraries provide a range of support for the development of data science applications. There are numerous core Java capabilities that can be used, such as the basic string processing methods. The introduction of lambda expressions in Java 8 helps enable more powerful and expressive means of building applications. In many of the examples that follow in subsequent chapters, we will show alternative techniques using lambda expressions.

There is ample support provided for the basic data science tasks. These include multiple ways of acquiring data, libraries for cleaning data, and a wide variety of analysis approaches for tasks such as natural language processing and statistical analysis. There are also myriad of libraries supporting neural network types of analysis.

Java can be a very good choice for data science problems. The language provides both object-oriented and functional support for solving problems. There is a large developer community to draw upon and there exist multiple APIs that support data science tasks. These are but a few reasons as to why Java should be used.

The remainder of this chapter will provide an overview of the data science tasks and Java support demonstrated in the book. Each section is only able to present a brief introduction to the topics and the available support. The subsequent chapter will go into considerably more depth regarding these topics.

Acquiring data for an application

Data acquisition is an important step in the data analysis process. When data is acquired, it is often in a specialized form and its contents may be inconsistent or different from an application's need. There are many sources of data, which are found on the Internet. Several examples will be demonstrated in Chapter 2, Data Acquisition.

Data may be stored in a variety of formats. Popular formats for text data include HTML, Comma Separated Values (CSV), JavaScript Object Notation (JSON), and XML. Image and audio data are stored in a number of formats. However, it is frequently necessary to convert one data format into another format, typically plain text.

For example, JSON (http://www.JSON.org/) is stored using blocks of curly braces containing key-value pairs. In the following example, parts of a YouTube result is shown:

{ "kind": "youtube#searchResult", "etag": etag, "id": { "kind": string, "videoId": string, "channelId": string, "playlistId": string

Data is acquired using techniques such as processing live streams, downloading compressed files, and through screen scraping, where the information on a web page is extracted. Web crawling is a technique where a program examines a series of web pages, moving from one page to another, acquiring the data that it needs.

With many popular media sites, it is necessary to acquire a user ID and password to access data. A commonly used technique is OAuth, which is an open standard used to authenticate users to many different websites. The technique delegates access to a server resource and works over HTTPS. Several companies use OAuth 2.0, including PayPal, Facebook, Twitter, and Yelp.

The importance and process of cleaning data

Once the data has been acquired, it will need to be cleaned. Frequently, the data will contain errors, duplicate entries, or be inconsistent. It often needs to be converted to a simpler data type such as text. Data cleaning is often referred to as data wrangling, reshaping, or munging. They are effectively synonyms.

When data is cleaned, there are several tasks that often need to be performed, including checking its validity, accuracy, completeness, consistency, and uniformity. For example, when the data is incomplete, it may be necessary to provide substitute values.

Consider CSV data. It can be handled in one of several ways. We can use simple Java techniques such as the String class' split method. In the following sequence, a string array, csvArray, is assumed to hold comma-delimited data. The split method populates a second array, tokenArray.

for(int i=0; i<csvArray.length; i++) { tokenArray[i] = csvArray[i].split(","); }

More complex data types require APIs to retrieve the data. For example, in Chapter 3, Data Cleaning, we will use the Jackson Project (https://github.com/FasterXML/jackson) to retrieve fields from a JSON file. The example uses a file containing a JSON-formatted presentation of a person, as shown next:

{ "firstname":"Smith", "lastname":"Peter", "phone":8475552222, "address":["100 Main Street","Corpus","Oklahoma"] }

The code sequence that follows shows how to extract the values for fields of a person. A parser is created, which uses getCurrentName to retrieve a field name. If the name is firstname, then the getText method returns the value for that field. The other fields are handled in a similar manner.

try {

JsonFactory jsonfactory = new JsonFactory(); JsonParser parser = jsonfactory.createParser( new File("Person.json")); while (parser.nextToken() != JsonToken.END_OBJECT) { String token = parser.getCurrentName(); if ("firstname".equals(token)) { parser.nextToken(); String fname = parser.getText(); out.println("firstname : " + fname); } } parser.close(); } catch (IOException ex) { // Handle exceptions }

The output of this example is as follows:

firstname : Smith

Simple data cleaning may involve converting the text to lowercase, replacing certain text with blanks, and removing multiple whitespace characters with a single blank. One way of doing this is shown next, where a combination of the String class' toLowerCase, replaceAll, and trim methods are used. Here, a string containing dirty text is processed:

dirtyText = dirtyText .toLowerCase() .replaceAll("[\\d[^\\w\\s]]+", " .trim(); while(dirtyText.contains(" ")){ dirtyText = dirtyText.replaceAll(" ", " "); }

Stop words are words such as the, and, or but that do not always contribute to the analysis of text. Removing these stop words can often improve the results and speed up the processing.

The LingPipe API can be used to remove stop words. In the next code sequence, a TokenizerFactory class instance is used to tokenize text. Tokenization is the process of returning individual words. The EnglishStopTokenizerFactory class is a special tokenizer that removes common English stop words.

text = text.toLowerCase().trim();

TokenizerFactory fact = IndoEuropeanTokenizerFactory.INSTANCE; fact = new EnglishStopTokenizerFactory(fact); Tokenizer tok = fact.tokenizer( text.toCharArray(), 0, text.length()); for(String word : tok){

out.print(word + " "); }

Consider the following text, which was pulled from the book, Moby Dick:

Call me Ishmael. Some years ago- never mind how long precisely - having little or no money in my purse, and nothing particular to interest me on shore, I thought I would sail about a little and see the watery part of the world.

The output will be as follows:

call me ishmael . years ago - never mind how long precisely - having little money my purse , nothing particular interest me shore , i thought i sail little see watery part world .

These are just a couple of the data cleaning tasks discussed in Chapter 3, Data Cleaning.

Visualizing data to enhance understanding

The analysis of data often results in a series of numbers representing the results of the analysis. However, for most people, this way of expressing results is not always intuitive. A better way to understand the results is to create graphs and charts to depict the results and the relationship between the elements of the result.

The human mind is often good at seeing patterns, trends, and outliers in visual representation. The large amount of data present in many data science problems can be analyzed using visualization techniques. Visualization is appropriate for a wide range of audiences ranging from analysts to upper-level management to clientele. In this chapter, we present various visualization techniques and demonstrate how they are supported in Java.

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"But I must tell you about George."

He looked at her, and decided that she really must tell him about George.

"I'm sorry. I didn't mean to bully. One has an ancestral idea that women must be treated like imbeciles in a crisis. Centuries of the 'women-and-children-first' idea, I suppose. Poor devils!"

"Who, the women?"

"Yes. No wonder they sometimes lose their heads. Pushed into corners, told nothing of what's happening and made to sit quiet and do nothing. Strong men would go dotty in the circs. I suppose that's why we've always grabbed the privilege of rushing about and doing the heroic bits."

"That's quite true. Give me the kettle."

"No, no. I'll do that. You sit down and—I mean, sorry, take the kettle. Fill it, light the gas, put it on. And tell me about George."

The trouble, it seemed, had begun at breakfast. Ever since the story of the murder had come out, George had been very nervy and jumpy, and, to Sheila's horror, had "started muttering again." "Muttering," Wimsey remembered, had formerly been the prelude to one of George's "queer fits." These had been a form of shell-shock, and they had generally ended in his going off and wandering about in a distraught manner for several days, sometimes with partial and occasionally with complete temporary loss of memory. There was the time when he had been found dancing naked in a field among a flock of sheep and singing to them. It had been the more ludicrously painful in that George was altogether tone-deaf, so that his singing, though loud, was like a hoarse and rumbling wind in the chimney. Then there was a dreadful time when George had deliberately walked into a bonfire. That was when they had been staying down in the country. George had been badly burnt, and the shock of the pain had brought him round. He never remembered afterwards why he had tried to do these things, and had only the faintest recollection of having done them at all. The next vagary might be even more disconcerting.

At any rate, George had been "muttering."

They were at breakfast that morning, when they saw two men coming up the path. Sheila, who sat opposite the window, saw them first, and said carelessly: "Hullo! who are these? They look like plainclothes policemen." George took one look, jumped up and rushed out of the room. She called to him to know what was the matter, but he did not answer, and she heard him "rummaging" in the back room, which was the bedroom. She was going to him, when she heard Mr. Munns open the door to the policemen and then heard them inquiring for George. Mr. Munns ushered them into the front room with a grim face on which "police" seemed written in capital letters. George——

At this point the kettle boiled. Sheila was taking it off the stove to make the Bovril, when Wimsey became aware of a hand on his coatcollar. He looked round into the face of a gentleman who appeared not to have shaved for several days.

"Now then," said this apparition, "what's the meaning of this?"

"Which," added an indignant voice from the door, "I thought as there was something behind all this talk of the Captain being missing. You didn't expect him to be missing, I suppose, ma'am. Oh, dear no! Nor your gentleman friend, neither, sneaking up in a taxi and you waiting at the door so's Munns and me shouldn't hear. But I'd have you know this is a respectable house, Lord Knows Who or whatever you call yourself—more likely one of these low-down confidence fellers, I expect, if the truth was known. With a monocle too, like that man we was reading about in the News of the World. And in my kitchen too, and drinking my Bovril in the middle of the night, the impudence! Not to speak of the goings-in-and-out all day, banging the front door, and that was the police come here this morning, you think I didn't know? Up to something, that's what they've been, the pair of them, and the captain as he says he is but that's as may be, I daresay he had his reasons for clearing off, and the sooner you goes after him my fine madam, the better I'll be pleased, I can tell you." "That's right," said Mr. Munns—"ow!"

Lord Peter had removed the intrusive hand from his collar with a sharp jerk which appeared to cause anguish out of all proportion to the force used.

"I'm glad you've come along," he said. "In fact, I was just going to give you a call. Have you anything to drink in the house, by the way?"

"Drink?" cried Mrs. Munns on a high note, "the impudence! And if I see you, Joe, giving drinks to thieves and worse in the middle of the night in my kitchen, you'll get a piece of my mind. Coming in here as bold as brass and the captain run away, and asking for drink——"

"Because," said Wimsey, fingering his note-case, "the public houses in this law-abiding neighborhood are of course closed. Otherwise a bottle of Scotch——"

Mr. Munns appeared to hesitate.

"Call yourself a man!" said Mrs. Munns.

"Of course," said Mr. Munns, "if I was to go in a friendly manner to Jimmy Rowe at the Dragon, and ask him to give me a bottle of Johnny Walker as a friend to a friend, and provided no money was to pass between him and me, that is——"

"A good idea," said Wimsey, cordially.

Mrs. Munns gave a loud shriek.

"The ladies," said Mr. Munns, "gets nervous at times." He shrugged his shoulders.

"I daresay a drop of Scotch wouldn't do Mrs. Munns's nerves any harm," said Wimsey.

"If you dare, Joe Munns," said the landlady, "if you dare to go out at this time of night, hob-nobbing with Jimmy Rowe and making a fool of yourself with burglars and such——"

Mr. Munns executed a sudden volte-face.

"You shut up!" he shouted. "Always sticking your face in where you aren't wanted."

"Are you speaking to me?"

"Yes. Shut up!"

Mrs. Munns sat down suddenly on a kitchen chair and began to sniff.

"I'll just hop round to the Dragon now, sir," said Mr. Munns, "before old Jimmy goes to bed. And then we'll go into this here."

He departed. Possibly he forgot what he had said about no money passing, for he certainly took the note which Wimsey absentmindedly held out to him.

"Your drink's getting cold," said Wimsey to Sheila. She came across to him.

"Can't we get rid of these people?"

"In half a jiff. It's not good having a row with them. I'd do it like a shot, only, you see, you've got to stay on here for a bit, in case George comes back."

"Of course. I'm sorry for all this upset, Mrs. Munns," she added, a little stiffly, "but I'm so worried about my husband."

"Husband?" snorted Mrs. Munns. "A lot husbands are to worry about. Look at that Joe. Off he goes to the Dragon, never mind what I say to him. They're dirt, that's what husbands are, the whole pack of them. And I don't care what anybody says."

"Are they?" said Wimsey. "Well, I'm not one—yet—so you needn't mind what you say to me."

"It's the same thing," said the lady, viciously, "husbands and parricides, there's not a half-penny to choose between them. Only parricides aren't respectable—but then, they're easier got rid of."

"Oh!" replied Wimsey, "but I'm not a parricide either—not Mrs. Fentiman's parricide at any rate, I assure you. Hullo! here's Joe. Did you get the doings, old man? You did? Good work. Now, Mrs. Munns, have just a spot with us. You'll feel all the better for it. And why shouldn't we go into the sitting-room where it's warmer?"

Mrs. Munns complied. "Oh, well," she said, "here's friends all round. But you'll allow it all looked a bit queer, now, didn't it? And the police this morning, asking all those questions, and emptying the dust-bin all over the back-yard."

"Whatever did they want with the dust-bin?"

"Lord knows; and that Cummins woman looking on all the time over the wall. I can tell you, I was vexed. 'Why, Mrs. Munns,' she said, 'have you been poisoning people?' she said. 'I always told you,' she said 'your cooking 'ud do for somebody one of these days.' The nasty cat."

"What a rotten thing to say," said Wimsey, sympathetically. "Just jealousy, I expect. But what did the police find in the dust-bin?"

"Find? Them find anything? I should like to see them finding things in my dust-bin. The less I see of their interfering ways the better I'm pleased. I told them so. I said, 'If you want to come upsetting my dust-bin,' I said, 'you'll have to come with a search-warrant,' I said. That's the law and they couldn't deny it. They said Mrs. Fentiman had given them leave to look, so I told them Mrs. Fentiman had no leave to give them. It was my dust-bin, I told them, not hers. So they went off with a flea in their ear."

"That's the stuff to give 'em, Mrs. Munns."

"Not but what I'm respectable. If the police come to me in a right and lawful manner, I'll gladly give them any help they want. I don't want to get into trouble, not for any number of captains. But interference with a free-born woman and no search-warrant I will not stand. And they can either come to me in a fitting way or they can go and whistle for their bottle."

"What bottle?" asked Wimsey, quickly.

"The bottle they were looking for in my dust-bin, what the captain put there after breakfast."

Sheila gave a faint cry.

"What bottle was that, Mrs. Munns?"

"One of them little tablet bottles," said Mrs. Munns, "same as you have standing on the wash-hand stand, Mrs. Fentiman. When I saw the Captain smashing it up in the yard with a poker——"

"There now, Primrose," said Mr. Munns, "can't you see as Mrs. Fentiman ain't well?"

"I'm quite all right," said Sheila, hastily, pushing away the hair which clung damply to her forehead. "What was my husband doing?"

"I saw him," said Mrs. Munns, "run out into the back-yard—just after your breakfast it was, because I recollect Munns was letting the officers into the house at the time. Not that I knew then who it was, for, if you will excuse me mentioning of it, I was in the outside lavatory, and that was how I come to see the Captain. Which ordinarily, you can't see the dust-bin from the house, my lord I should say, I suppose, if you really are one, but you meet so many bad characters nowadays that one can't be too careful—on account of the lavatory standing out as you may say and hiding it."

"Just so," said Wimsey.

"So when I saw the captain breaking the bottle as I said, and throwing the bits into the dust-bin, 'Hullo!' I said, 'that's funny,' and I went to see what it was and I put it in an envelope, thinking, you see, as it might be something poisonous, and the cat such a dreadful thief as he is, I never can keep him out of that dust-bin. And when I came in, I found the police here. So after a bit, I found them poking about in the yard and I asked them what they were doing there. Such a mess as they'd made, you never would believe. So they showed me a little cap they'd found, same as it might be off that tablet-bottle. Did I know where the rest of it was?' they said. And I said, what business had they got with the dust-bin at all. So they said——"

"Yes, I know," said Wimsey. "I think you acted very sensibly, Mrs. Munns. And what did you do with the envelope and things?"

"I kept it," replied Mrs. Munns, nodding her head, "I kept it. Because, you see, if they did return with a warrant and I'd destroyed that bottle, where should I be?"

"Quite right," said Wimsey, with his eye on Sheila.

"Always keep on the right side of the law," agreed Mr Munns, "and nobody can't interfere with you. That's what I say. I'm a Conservative, I am. I don't hold with these Socialist games. Have another."

"Not just now," said Wimsey. "And we really must not keep you and Mrs. Munns up any longer. But, look here! You see, Captain Fentiman had shell-shock after the War, and he is liable to do these little odd things at times—break things up, I mean, and lose his memory and go wandering about. So Mrs. Fentiman is naturally anxious about his not having turned up this evening."

"Ay," said Mr. Munns, with relish. "I knew a fellow like that. Went clean off his rocker he did one night. Smashed up his family with a beetle—a pavior he was by profession, and that's how he came to have a beetle in the house—pounded 'em to a jelly, he did, his wife and five little children, and went off and drownded himself in the Regent's Canal. And, what's more, when they got him out, he didn't remember a word about it, not one word. So they sent him to— what's that place? Dartmoor? no, Broadmoor, that's it, where Ronnie True went to with his little toys and all."

"Shut up, you fool," said Wimsey, savagely.

"Haven't you got feelings?" demanded his wife.

Sheila got up, and made a blind effort in the direction of the door.

"Come and lie down," said Wimsey, "you're worn out. Hullo! there's Robert, I expect. I left a message for him to come round as soon as he got home."

Mr. Munns went to answer the bell.

"We'd better get her to bed as quick as possible," said Wimsey to the landlady. "Have you got such a thing as a hot-water bottle?"

Mrs. Munns departed to fetch one, and Sheila caught Wimsey's hand.

"Can't you get hold of that bottle? Make her give it to you. You can. You can do anything. Make her."

"Better not," said Wimsey "Look suspicious. Look here, Sheila, what is the bottle?"

"My heart medicine. I missed it. It's something to do with digitalin."

"Oh, lord," said Wimsey, as Robert came in.

"It's all pretty damnable," said Robert.

He thumped the fire gloomily; it was burning badly, the lower bars were choked with the ashes of a day and night.

"I've been having a talk with Frobisher," he added. "All this talk in the Club—and the papers—naturally he couldn't overlook it."

"Was he decent?"

"Very decent. But of course I couldn't explain the thing. I'm sending in my papers."

Wimsey nodded. Colonel Frobisher could scarcely overlook an attempted fraud—not after things had been said in the papers.

"If I'd only let the old man alone. Too late now. He'd have been buried. Nobody would have asked questions."

"I didn't want to interfere," said Wimsey, defending himself against the unspoken reproach.

"Oh, I know. I'm not blaming you. People ... money oughtn't to depend on people's deaths ... old people, with no use for their lives ... it's a devil of a temptation. Look here, Wimsey, what are we to do about this woman?"

"The Munns female?"

"Yes. It's the devil and all she should have got hold of the stuff. If they find out what it's supposed to be, we shall be blackmailed for the rest of our lives."

"No," said Wimsey, "I'm sorry, old man, but the police have got to know about it."

Robert sprang to his feet.

"My God!—you wouldn't——"

"Sit down, Fentiman. Yes, I must. Don't you see I must? We can't suppress things. It always means trouble. It's not even as though they hadn't got their eyes on us already. They're suspicious——"

"Yes, and why?" burst out Robert, violently. "Who put it into their heads?... For God's sake don't start talking about law and justice! Law and justice! You'd sell your best friend for the sake of making a sensational appearance in the witness-box, you infernal little police spy!"

"Chuck that, Fentiman!"

"I'll not chuck it! You'd go and give away a man to the police—when you know perfectly well he isn't responsible—just because you can't afford to be mixed up in anything unpleasant. I know you. Nothing's too dirty for you to meddle in, provided you can pose as the pious little friend of justice. You make me sick!"

"I tried to keep out of this——"

"You tried!—don't be a blasted hypocrite! You get out of it now, and stay out—do you hear?"

"Yes, but listen a moment——"

"Get out!" said Robert.

Wimsey stood up.

"I know how you feel, Fentiman——"

"Don't stand there being righteous and forebearing, you sickening prig. For the last time—are you going to shut up, or are you going to trot round to your policeman friend and earn the thanks of a grateful country for splitting on George? Get on! Which is it to be?"

"You won't do George any good——"

"Never mind that. Are you going to hold your tongue?"

"Be reasonable, Fentiman."

"Reasonable be damned. Are you going to the police? No shuffling. Yes or no?"

"Yes."

"You dirty little squirt," said Robert, striking out passionately. Wimsey's return blow caught him neatly on the chin and landed him in the wastepaper basket.

"And now, look here," said Wimsey, standing over him, hat and stick in hand. "It's no odds to me what you do or say. You think your brother murdered your grandfather. I don't know whether he did or not. But the worst thing you can do for him is to try and destroy evidence. And the worst thing you can possibly do for his wife is to make her a party to anything of the sort. And next time you try to smash anybody's face in, remember to cover up your chin. That's all. I can let myself out. Good-bye."

He went round to 12 Great Ormond Street and rousted Parker out of bed.

Parker listened thoughtfully to what he had to say.

"I wish we'd stopped Fentiman before he bolted," he said. "Yes; why didn't you?"

"Well, Dykes seems to have muffed it rather. I wasn't there myself. But everything seemed all right. Fentiman looked a bit nervy, but many people do when they're interviewed by the police—think of their hideous pasts, I suppose, and wonder what's coming next. Or else it's just stage-fright. He stuck to the same tale he told you—said he was quite sure the old General hadn't taken any pills or anything in the taxi—didn't attempt to pretend he knew anything about Lady Dormer's will. There was nothing to detain him for He said he had to get to his job in Great Portland Street. So they let him go. Dykes sent a man to follow him up, and he went along to Hubbard-Walmisley's all right. Dykes said, might he just have a look round the place before he went, and Mrs. Fentiman said certainly. He didn't expect to find anything, really. Just happened to step into the back-yard, and saw a bit of broken glass. He then had a look round, and there was

the cap of the tablet-bottle in the dust-bin. Well, then, of course, he started to get interested, and was just having a hunt through for the rest of it, when old mother Munns appeared and said the dust-bin was her property. So they had to clear out. But Dykes oughtn't to have let Fentiman go till they'd finished going over the place. He 'phoned through to Hubbard-Walmisley's at once, and heard that Fentiman had arrived and immediately gone out with the car, to visit a prospective customer in Herts. The fellow who was supposed to be trailing Fentiman got carburetor trouble just beyond St. Albans, and by the time he was fixed, he'd lost Fentiman."

"Did Fentiman go to the customer's house?"

"Not he. Disappeared completely. We shall find the car, of course— it's only a matter of time."

"Yes," said Wimsey. His voice sounded tired and constrained.

"This alters the look of things a bit," said Parker, "doesn't it?"

"Yes."

"What have you done to your face, old man?"

Wimsey glanced at the looking-glass, and saw that an angry red flush had come up on the cheekbone.

"Had a bit of a dust-up with Robert," he said.

"Oh!"

Parker was aware of a thin veil of hostility, drawn between himself and the friend he valued. He knew that for the first time, Wimsey was seeing him as the police. Wimsey was ashamed and his shame made Parker ashamed too.

"You'd better have some breakfast," said Parker. His voice sounded awkward to himself.

"No—no thanks, old man. I'll go home and get a bath and shave."

"Oh, right-oh!"

There was a pause.

"Well, I'd better be going," said Wimsey

"Oh, yes," said Parker again. "Right-oh!"

"Er—cheerio!" said Wimsey at the door.

"Cheerio!" said Parker.

The bedroom door shut. The flat door shut. The front door shut.

Parker pulled the telephone towards him and called up Scotland Yard.

The atmosphere of his own office was bracing to Parker when he got down there. For one thing, he was taken aside by a friend and congratulated in conspiratorial whispers.

"Your promotion's gone through," said the friend. "Dead certainty. The Chief's no end pleased. Between you and me, of course. But you've got your Chief-Inspectorship all right. Damn good."

Then, at ten o'clock, the news came through that the missing Walmisley-Hubbard had turned up. It had been abandoned in a remote Hertfordshire lane. It was in perfectly good order, the gearlever in neutral and the tank full of petrol. Evidently, Fentiman had left it and wandered away somewhere, but he could not be far off. Parker made the necessary arrangements for combing out the neighborhood. The bustle and occupation soothed his mind. Guilty or insane or both, George Fentiman had to be found; it was just a job to be done.

The man who had been sent to interview Mrs. Munns (armed this time with a warrant) returned with the fragments of the bottle and tablets. Parker duly passed these along to the police analyst. One of the detectives who was shadowing Miss Dorland rang up to announce that a young woman had come to see her, and that the two had then come out carrying a suit-case and driven away in a taxi. Maddison, the other detective, was following them. Parker said, "All right; stay where you are for the present," and considered this

new development. The telephone rang again. He thought it would be Maddison, but it was Wimsey—a determinedly brisk and cheerful Wimsey this time.

"I say, Charles. I want something."

"What?"

"I want to go and see Miss Dorland."

"You can't. She's gone off somewhere. My man hasn't reported yet."

"Oh! Well, never mind her. What I really want to see is her studio."

"Yes? Well, there's no reason why you shouldn't."

"Will they let me in?"

"Probably not. I'll meet you there and take you in with me. I was going out any way. I've got to interview the nurse. We've just got hold of her."

"Thanks awfully. Sure you can spare the time?"

"Yes. I'd like your opinion."

"I'm glad somebody wants it. I'm beginning to feel like a pelican in the wilderness."

"Rot! I'll be round in ten minutes."

"Of course," explained Parker, as he ushered Wimsey into the studio, "we've taken away all the chemicals and things. There's not much to look at, really."

"Well, you can deal best with all that. It's the books and paintings I want to look at. H'm! Books, you know, Charles, are like lobster shells, we surround ourselves with 'em, then we grow out of 'em and leave 'em behind, as evidence of our earlier stages of development."

"That's a fact," said Parker. "I've got rows of school-boy stuff at home —never touch it now, of course. And W. J. Locke—read everything he wrote once upon a time. And Le Queux, and Conan Doyle, and all that stuff."

"And now you read theology. And what else?"

"Well, I read Hardy a good bit. And when I'm not too tired, I have a go at Henry James."

"The refined self-examinations of the infinitely-sophisticated. 'M-m. Well now. Let's start with the shelves by the fireplace. Dorothy Richardson—Virginia Woolf—E. B. C. Jones—May Sinclair— Katherine Mansfield—the modern female writers are well represented, aren't they? Galsworthy. Yes. No J. D. Beresford—no Wells—no Bennett. Dear me, quite a row of D. H. Lawrence. I wonder if she reads him very often."

He pulled down "Women in Love" at random, and slapped the pages open and shut.

"Not kept very well dusted, are they? But they have been read. Compton Mackenzie—Storm Jameson—yes—I see."

"The medical stuff is over here."

"Oh!—a few text-books—first steps in chemistry. What's that tumbled down at the back of the book-case? Louis Berman, eh? The Personal Equation. And here's Why We Behave Like Human Beings. And Julian Huxley's essays. A determined effort at self-education here, what?"

"Girls seem to go in for that sort of thing nowadays."

"Yes—hardly nice, is it? Hullo!"

"What?"

"Over here by the couch. This represents the latest of our lobstershells, I fancy. Austin Freeman, Austin Freeman, Austin Freeman— bless me! she must have ordered him in wholesale. Through the Wall—that's a good 'tec story, Charles—all about the third degree— Isabel Ostrander—three Edgar Wallaces—the girl's been indulging in an orgy of crime!"

"I shouldn't wonder," said Parker, with emphasis. "That fellow Freeman is full of plots about poisonings and wills and survivorship, isn't he?"

"Yes"—Wimsey balanced A Silent Witness gently in his hand, and laid it down again. "This one, for instance, is all about a bloke who murdered somebody and kept him in cold storage till he was ready to dispose of him. It would suit Robert Fentiman."

Parker grinned.

"A bit elaborate for the ordinary criminal. But I daresay people do get ideas out of these books. Like to look at the pictures? They're pretty awful."

"Don't try to break it gently. Show us the worst at once.... Oh, lord!"

"Well, it gives me a pain," said Parker. "But I thought perhaps that was my lack of artistic education."

"It was your natural good taste. What vile color, and viler drawing."

"But nobody cares about drawing nowadays, do they?"

"Ah! but there's a difference between the man who can draw and won't draw, and the man who can't draw at all. Go on. Let's see the rest."

Parker produced them, one after the other. Wimsey glanced quickly at each. He had picked up the brush and palette and was fingering them as he talked.

"These," he said, "are the paintings of a completely untalented person, who is, moreover, trying to copy the mannerisms of a very advanced school. By the way, you have noticed, of course, that she has been painting within the last few days, but chucked it in sudden disgust. She has left the paints on the palette, and the brushes are still stuck in the turps, turning their ends up and generally ruining themselves. Suggestive, I fancy. The—stop a minute! Let's look at that again."

Parker had brought forward the head of the sallow, squinting man which he had mentioned to Wimsey before.

"Put that up on the easel. That's very interesting. The others, you see, are all an effort to imitate other people's art, but this—this is an effort to imitate nature. Why?—it's very bad, but it's meant for

somebody And it's been worked on a lot. Now what was it made her do that?"

"Well, it wasn't for his beauty, I should think."

"No?—but there must have been a reason. Dante, you may remember, once painted an angel. Do you know the limerick about the old man of Khartoum?"

"What did he do?"

"He kept two black sheep in his room. They remind me (he said) of two friends who are dead. But I cannot remember of whom."

"If that reminds you of anybody you know, I don't care much for your friends. I never saw an uglier mug."

"He's not beautiful. But I think the sinister squint is chiefly due to bad drawing. It's very difficult to get eyes looking the same way, when you can't draw. Cover up one eye, Charles—not yours, the portrait's."

Parker did so.

Wimsey looked again, and shook his head.

"It escapes me for the moment," he said. "Probably it's nobody I know after all. But, whoever it is, surely this room tells you something."

"It suggests to me," said Parker, "that the girl's been taking more interest in crimes and chemistry stuff than is altogether healthy in the circumstances."

Wimsey looked at him for a moment.

"I wish I could think as you do."

"What do you think?" demanded Parker, impatiently.

"No," said Wimsey. "I told you about that George business this morning, because glass bottles are facts, and one mustn't conceal facts. But I'm not obliged to tell you what I think."

"You don't think, then, that Ann Dorland did the murder?"

"I don't know about that, Charles. I came here hoping that this room would tell me the same thing that it told you. But it hasn't. It's told me different. It's told me what I thought all along."

"A penny for your thoughts, then," said Parker, trying desperately to keep the conversation on a jocular footing.

"Not even thirty pieces of silver," replied Wimsey, mournfully.

Parker stacked the canvasses away without another word.

CHAPTER XIX

Lord Peter Plays Dummy

"Do you want to come with me to the Armstrong woman?"

"May as well," said Wimsey, "you never know."

Nurse Armstrong belonged to an expensive nursing home in Great Wimpole Street. She had not been interviewed before, having only returned the previous evening from escorting an invalid lady to Italy. She was a large, good-looking, imperturbable woman, rather like the Venus of Milo, and she answered Parker's questions in a cheerful, matter-of-fact tone, as though they had been about bandages or temperatures.

"Oh, yes, Constable; I remember the poor old gentleman being brought in, perfectly."

Parker had a natural dislike to being called constable. However, a detective must not let little things like that irritate him.

"Was Miss Dorland present at the interview between your patient and her brother?"

"Only for a few moments. She said good afternoon to the old gentleman and led him up to the bed, and then, when she saw them comfortable together, she went out."

"How do you mean, comfortable together?"

"Well, the patient called the old gentleman by his name, and he answered, and then he took her hand and said, 'I'm sorry, Felicity; forgive me,' or something of that sort, and she said, 'There's nothing to forgive; don't distress yourself, Arthur,'—crying, he was, the poor old man. So he sat down on the chair by the bed, and Miss Dorland went out."

"Nothing was said about the will?"

"Not while Miss Dorland was in the room, if that's what you mean."

"Suppose anybody had listened at the door afterwards—could they have heard what was said?"

"Oh, no! The patient was very weak and spoke very low. I couldn't hear myself half she said."

"Where were you?"

"Well, I went away, because I thought they'd like to be alone. But I was in my own room with the door open between, and I was looking in most of the time. She was so ill, you see, and the old gentleman looked so frail, I didn't like to go out of earshot. In our work, you see, we often have to see and hear a lot that we don't say anything about."

"Of course, Nurse—I am sure you did quite right. Now when Miss Dorland brought the brandy up—the General was feeling very ill?"

"Yes—he had a nasty turn. I put him in the big chair and bent him over till the spasm went off. He asked for his own medicine, and I gave it to him—no, it wasn't drops—it was amyl nitrate; you inhale it. Then I rang the bell and sent the girl for the brandy."

"Amyl nitrate—you're sure that's all he had?"

"Positive; there wasn't anything else. Lady Dormer had been having strychnine injections to keep her heart going, of course, and we'd tried oxygen; but we shouldn't give him those, you know." She smiled, competently, condescendingly.

"Now, you say Lady Dormer had been having this, that and the other Were there any medicines lying about that General Fentiman might have accidentally taken up and swallowed?"

"Oh, dear no."

"No drops or tabloids or anything of that kind?"

"Certainly not; the medicines were kept in my room."

"Nothing on the bedside table or the mantelpiece?"

"There was a cup of diluted Listerine by the bed, for washing out the patient's mouth from time to time, that was all."

"And there's no digitalin in Listerine—no, of course not. Well now, who brought up the brandy-and-water?"

"The housemaid went to Mrs. Mitcham for it. I should have had some upstairs, as a matter of fact, but the patient couldn't keep it down. Some of them can't, you know."

"Did the girl bring it straight up to you?"

"No—she stopped to call Miss Dorland on the way. Of course, she ought to have brought the brandy at once and gone to Miss Dorland afterwards—but it's anything to save trouble with these girls, as I daresay you know."

"Did Miss Dorland bring it straight up—?" began Parker. Nurse Armstrong broke in upon him.

"If you're thinking, did she put the digitalin into the brandy, you can dismiss that from your mind, constable. If he'd had as big a dose as that in solution at half-past four, he'd have been taken ill ever so much earlier than he was."

"You seem to be well up in the case, Nurse."

"Oh, I am. Naturally I was interested, Lady Dormer being my patient and all."

"Of course. But all the same, did Miss Dorland bring the brandy straight along to you?"

"I think so. I heard Nellie go along the passage on the half landing, and looked out to call to her, but by the time I'd got the door open, I saw Miss Dorland coming out of the studio with the brandy in her hand."

"And where was Nellie then?"

"Just got back to the end of the passage and starting downstairs to the telephone."

"At that rate, Miss Dorland couldn't have been more than ten seconds alone with the brandy," said Peter, thoughtfully. "And who gave it to General Fentiman?"

"I did. I took it out of Miss Dorland's hand at the door and gave it to him at once. He seemed better then, and only took a little of it."

"Did you leave him again?"

"I did not. Miss Dorland went out on to the landing presently to see if the taxi was coming."

"She was never alone with him?"

"Not for a moment."

"Did you like Miss Dorland, Nurse? Is she a nice girl, I mean?" Wimsey had not spoken for so long that Parker quite started.

"She was always very pleasant to me," said Nurse Armstrong. "I shouldn't call her an attractive girl, not to my mind."

"Did she ever mention Lady Dormer's testamentary arrangements in your hearing?" asked Parker, picking up what he conceived to be Wimsey's train of thought.

"Well—not exactly. But I remember her once talking about her painting, and saying she did it for a hobby, as her aunt would see she always had enough to live on."

"That's true enough," said Parker. "At the worst, she would get fifteen thousand pounds, which carefully invested, might mean six or seven hundred a year. She didn't say she expected to be very rich?"

"No."

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