Dive into the world of Kibana 7 with this hands-on guide that simplifies the process of visualizing and analyzing data using Elasticsearch. From fundamental concepts to advanced tools, this book enables you to create intuitive dashboards and leverage powerful machine learning capabilities effectively. Discover how to transform your data into actionable insights with ease. What this Book will help me do Configure Logstash to fetch and process CSV data for visualization. Master creating and managing index patterns within Kibana for efficient data navigation. Effectively apply filters to refine data presentations and insights. Develop and utilize machine learning jobs in Kibana to identify trends and anomalies. Create, customize, and share impactful visualizations and dashboards to drive data-driven decisions. Author(s) None Srivastava is a technical expert in data visualization and Elasticsearch tools, with practical experience implementing and teaching about the Elastic Stack. The author brings a hands-on approach to this book, simplifying complex concepts for ease of understanding. Their expertise ensures that the book serves both as a learning guide and a practical reference. Who is it for? This book is ideal for developers and IT professionals who are either new to Kibana or looking to deepen their understanding of its visualization capabilities. It is suitable for individuals working with the Elastic Stack or seeking to leverage Kibana for data analysis purposes. Even if you are progressing from a novice to an intermediate level, this guide will provide future-proof skills to optimize your workflow.

Discover the ultimate guide to Tableau 2019.x that offers over 115 practical recipes to tackle business intelligence and data analysis challenges. This book takes you from the basics to advanced techniques, empowering you to create insightful dashboards, leverage powerful analytics, and seamlessly integrate with modern cloud data platforms. What this Book will help me do Master both basic and advanced functionalities of Tableau Desktop to effectively analyze and visualize data. Understand how to create impactful dashboards and compelling data stories for drive decision-making. Deploy advanced analytical tools including R-based forecasting and statistical techniques with Tableau. Set up and utilize Tableau Server in multi-node environments on Linux and Windows. Utilize Tableau Prep to efficiently clean, shape, and transform data for seamless integration into Tableau workflows. Author(s) The authors of the Tableau 2019.x Cookbook are recognized industry professionals with rich expertise in business intelligence, data analytics, and Tableau's ecosystem. Dmitry Anoshin and his co-authors bring hands-on experience from various industries to provide actionable insights. They focus on delivering practical solutions through structured learning paths. Who is it for? This book is tailored for data analysts, BI developers, and professionals equipped with some knowledge of Tableau wanting to enhance their skills. If you're aiming to solve complex analytics challenges or want to fully utilize the capabilities of Tableau products, this book offers the guidance and knowledge you need.

In "Go Web Scraping Quick Start Guide", you'll learn how to harness the power of the Go programming language to scrape and crawl data from websites effectively. This book covers fundamental techniques and essential libraries such as Colly and Goquery, helping you efficiently extract useful data while understanding best practices and avoiding common pitfalls. What this Book will help me do Master web scraping techniques using Go and libraries like Colly and Goquery. Understand HTTP request and response handling in the context of web scraping. Explore web scraping navigation strategies to retrieve the data you need efficiently and effectively. Learn to use Go's concurrency model for parallelized and scalable web scraping. Protect your scrapers from being blocked by implementing proxies and best practices. Author(s) None Smith is an experienced Go developer with a passion for teaching and simplifying technical concepts. With a strong background in software development and web technologies, they bring a practical approach to mastering Go and web scraping. Their clear writing style helps readers gain hands-on knowledge in applying technology effectively. Who is it for? This book is perfect for data scientists and web developers who have some prior knowledge of Go and want to extend their skills to include effective web scraping. Whether you're looking to extract data for analysis or develop solutions for web crawling tasks, this book provides a step-by-step approach tailored to practical applications. It's especially suited for professionals aiming to expand their technical toolkit for data and web projects.

A good visualization can communicate the nature and potential impact of ideas more powerfully than any other form of communication. For a long time, "dataviz" was left to specialists--data scientists and professional designers. No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could. The Harvard Business Review Good Charts Collection brings together two popular books to help you become more sophisticated in understanding and using dataviz to communicate your ideas and advance your career. In Good Charts, dataviz maven and Harvard Business Review editor Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. He lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping. In Good Charts Workbook, Berinato extends the usefulness of Good Charts by putting theory into practice. He leads readers step-by-step through several example datasets and basic charts, providing space to practice the Good Charts talk-sketch-prototype process for improving those charts. Examples include a "Discussion Key" showing how to approach the challenge and why. Each challenge focuses on a different, common visualization problem such as simplification, storytelling, creating conceptual charts, and many others. The Harvard Business Review Good Charts Collection is your go-to resource for turning plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (with R) presents a broad coverage of the theory of robust statistics that is integrated with computing methods and applications. Updated to include important new research results of the last decade and focus on the use of the popular software package R, it features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series modeling. The book is illustrated throughout by a range of examples and applications that are supported by a companion website featuring data sets and R code that allow the reader to reproduce the examples given in the book. Unlike other books on the market, Robust Statistics: Theory and Methods (with R) offers the most comprehensive, definitive, and up-to-date treatment of the subject. It features chapters on estimating location and scale; measuring robustness; linear regression with fixed and with random predictors; multivariate analysis; generalized linear models; time series; numerical algorithms; and asymptotic theory of M-estimates. Explains both the use and theoretical justification of robust methods Guides readers in selecting and using the most appropriate robust methods for their problems Features computational algorithms for the core methods Robust statistics research results of the last decade included in this 2nd edition include: fast deterministic robust regression, finite-sample robustness, robust regularized regression, robust location and scatter estimation with missing data, robust estimation with independent outliers in variables, and robust mixed linear models. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.

Communicating your idea in a clear, compelling, and persuasive manner is critical when trying to launch a new venture. This Harvard Business Review collection brings together two popular books to help you craft your story, design better visualizations, impress your audience, and turn your idea into reality. Understanding and using data viz to persuade is a must-have skill for anyone in business today--especially if you're launching a new venture. In Good Charts, dataviz maven Scott Berinato provides an essential guide to how visualization works. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping. How do you launch the venture of your dreams? In Get Backed, entrepreneurs Evan Baehr and Evan Loomis argue that it's not just about securing startup funding. It's about building the right relationships, crafting a compelling story, and creating the perfect pitch deck. Filled with proven tips, exercises, and templates, this book shows the process for how to successfully communicate your vision. Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas. Get Backed will show you exactly what it takes to get funded and will give you the tools to launch a new venture. Together, these books will help you bring your idea to life.

Talk. Sketch. Prototype. Repeat. You know right away when you see an effective chart or graphic. It hits you with an immediate sense of its meaning and impact. But what actually makes it clearer, sharper, and more effective? If you're ready to create your own "good charts"--data visualizations that powerfully communicate your ideas and research and that advance your career—the Good Charts Workbook is the hands-on guide you've been looking for. The original Good Charts changed the landscape by helping readers understand how to think visually and by laying out a process for creating powerful data visualizations. Now, the Good Charts Workbook provides tools, exercises, and practical insights to help people in all kinds of enterprises gain the skills they need to get started. Harvard Business Review Senior Editor and dataviz expert Scott Berinato leads you, step-by-step, through the key challenges in creating good charts—controlling color, crafting for clarity, choosing chart types, practicing persuasion, capturing concepts—with warm-up exercises and mini-challenges for each. The Workbook includes helpful prompts and reminders throughout, as well as white space for users to practice the Good Charts talk-sketch-prototype process. Good Charts Workbook is the must-have manual for better understanding the dataviz around you and for creating better charts to make your case more effectively.

Explore and understand data with the powerful data visualization techniques of Tableau, and then communicate insights in powerful ways Key Features Apply best practices in data visualization and chart types exploration Explore the latest version of Tableau Desktop with hands-on examples Understand the fundamentals of Tableau storytelling Book Description Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You'll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. This Learning Path includes content from the following Packt products: Learning Tableau 10 - Second Edition by Joshua N. Milligan Getting Started with Tableau 2018.x by Tristan Guillevin What you will learn Build effective visualizations, dashboards, and story points Build basic to more advanced charts with step-by-step recipes Become familiar row-level, aggregate, and table calculations Dig deep into data with clustering and distribution models Prepare and transform data for analysis Leverage Tableau's mapping capabilities to visualize data Use data storytelling techniques to aid decision making strategy Who this book is for Tableau 10 Complete Reference is designed for anyone who wants to understand their data better and represent it in an effective manner. It is also used for BI professionals and data analysts who want to do better at their jobs. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace). It builds on the author's previous book, Fundamental Statistical Inference: A Computational Approach, which introduced the major concepts of statistical inference. Attention is explicitly paid to application and numeric computation, with examples of Matlab code throughout. The code offers a framework for discussion and illustration of numerics, and shows the mapping from theory to computation. The topic of time series analysis is on firm footing, with numerous textbooks and research journals dedicated to it. With respect to the subject/technology, many chapters in Linear Models and Time-Series Analysis cover firmly entrenched topics (regression and ARMA). Several others are dedicated to very modern methods, as used in empirical finance, asset pricing, risk management, and portfolio optimization, in order to address the severe change in performance of many pension funds, and changes in how fund managers work. Covers traditional time series analysis with new guidelines Provides access to cutting edge topics that are at the forefront of financial econometrics and industry Includes latest developments and topics such as financial returns data, notably also in a multivariate context Written by a leading expert in time series analysis Extensively classroom tested Includes a tutorial on SAS Supplemented with a companion website containing numerous Matlab programs Solutions to most exercises are provided in the book Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH is suitable for advanced masters students in statistics and quantitative finance, as well as doctoral students in economics and finance. It is also useful for quantitative financial practitioners in large financial institutions and smaller finance outlets.

Mastering Matplotlib 2.x guides you through the art and science of creating sophisticated data visualizations with Python's powerful Matplotlib library. You will start by learning the basics of plotting and customizing your charts, progressing to more advanced topics such as 3D visualization, geospatial data display, and creating interactive plots using Jupyter Notebook. What this Book will help me do Create complex and highly customizable data plots using Matplotlib. Effectively visualize data in three dimensions, including geospatial data. Use advanced matplotlib features to represent non-Cartesian and vector data. Build interactive visualizations using Jupyter Notebook and Python. Develop special-purpose and movie-style plots to enhance data representation. Author(s) None Keller is a seasoned software engineer and data visualization enthusiast with years of experience using Python for data analysis. Their practical and hands-on approach ensures that readers can directly apply the concepts taught in their projects. None aims to make advanced visualization techniques accessible to all. Who is it for? This book is perfect for developers, scientists, and analysts who need sophisticated visualization tools for their projects. Prior experience with Python and basic familiarity with Matplotlib will help you get the most out of the book. If you're looking to deepen your understanding of data visualization or to create interactive and advanced visualizations, this book is for you.

This textbook reviews the methodologies of reliability prediction as currently used in industries such as electronics, automotive, aircraft, aerospace, off-highway, farm machinery, and others. It then discusses why these are not successful; and, presents methods developed by the authors for obtaining accurate information for successful prediction. The approach is founded on approaches that accurately duplicate the real world use of the product. Their approach is based on two fundamental components needed for successful reliability prediction; first, the methodology necessary; and, second, use of accelerated reliability and durability testing as a source of the necessary data. Applicable to all areas of engineering, this textbook details the newest techniques and tools to achieve successful reliabilityprediction and testing. It demonstrates practical examples of the implementation of the approaches described. This book is a tool for engineers, managers, researchers, in industry, teachers, and students. The reader will learn the importance of the interactions of the influencing factors and the interconnections of safety and human factors in product prediction and testing.

Discover the essentials of web scraping with R through this comprehensive guide. In this book, you will learn powerful techniques to extract valuable data from websites using the R programming language and tools like rvest and RSelenium. By understanding how to write efficient scripts, you will gain the ability to automate data collection and analysis for your projects. What this Book will help me do Understand the fundamentals of web scraping and its applications. Master the use of rvest for extracting data from static websites. Learn advanced techniques for dynamic websites using RSelenium. Write effective RegEx and XPath rules to enhance data extraction. Store, manage, and visualize the scraped data efficiently. Author(s) None Aydin is an experienced data analyst and R programmer with a deep passion for data manipulation and analysis. With years of firsthand expertise in utilizing R for various data-related tasks, Aydin brings a practical and methodological approach to teaching complex concepts. His clear instruction style ensures that readers quickly grasp and apply the techniques taught in this book. Who is it for? This book is ideal for R programmers seeking to expand their skills by delving into web scraping techniques. Whether you are a beginner with a basic knowledge of R or a data analyst exploring new ways to extract and utilize data, this guide is tailored for you. It suits readers who aspire to automate data collection and expand their analytical capabilities.

Matplotlib 3.0 Cookbook is your go-to guide for mastering the Matplotlib library in Python for creating a wide range of data visualizations. Through 150+ practical recipes, you will learn how to design intuitive and detailed charts, graphs, and dashboards, navigating from simple plots to advanced interactive and 3D visualizations. What this Book will help me do Develop professional-quality data visualizations using Matplotlib. Leverage Matplotlib's API for both quick plotting and advanced customization. Create interactive and animative plots for engaging data representation. Extend Matplotlib functionalities with toolkits like cartopy and axisartist. Integrate Matplotlib figures into GUI applications for broader usage. Author(s) None Poladi and None Borkar are experienced Python developers and enthusiasts who have collaborated in creating a resourceful guide to Matplotlib. They bring extensive experience in data science visualization and Python programming. Their collaborative effort ensures clarity and an approachable learning curve for anyone delving into graphical data representation using Matplotlib. Who is it for? This book is ideal for data scientists, Python developers, and visualization enthusiasts eager to enhance their technical plotting skills. The content covers both fundamentals and advanced topics, suitable for users ranging from beginners curious about Python visualization to experts seeking streamlined workflows and advanced techniques.

The text considers Simple Linear Regression and ask what is it doing? how good is it? how accurate is it? and how can we use it to create estimates? The book considers all this and looks at how you can exploit this transformability and use the capability of Simple Linear Regression.

This book presents the developments in problems of state estimation and optimal control of continuous-time dynamical systems using orthogonal functions since 1975. It deals with both full and reduced-order state estimation and problems of linear time-invariant systems. It also addresses optimal control problems of varieties of continuous-time systems such as linear and nonlinear systems, time-invariant and time-varying systems, as well as delay-free and time-delay systems. Content focuses on development of recursive algorithms for studying state estimation and optimal control problems.

Master Statistical Quality Control using JMP ! Using examples from the popular textbook by Douglas Montgomery, Introduction to Statistical Quality Control: A JMP Companion demonstrates the powerful Statistical Quality Control (SQC) tools found in JMP. Geared toward students and practitioners of SQC who are using these techniques to monitor and improve products and processes, this companion provides step-by-step instructions on how to use JMP to generate the output and solutions found in Montgomery’s book. The authors combine their many years of experience as passionate practitioners of SQC and their expertise using JMP to highlight the recent advances in JMP’s Analyze menu, and in particular, Quality and Process. Key JMP platforms include: Control Chart Builder CUSUM Control Chart Control Chart (XBar, IR, P, NP, C, U, UWMA, EWMA, CUSUM) Process Screening Process Capability Measurement System Analysis Time Series Multivariate Control Chart Multivariate and Principal Components Distribution For anyone who wants to learn how to use JMP to more easily explore data using tools associated with Statistical Process Control, Process Capability Analysis, Measurement System Analysis, Advanced Statistical Process Control, and Process Health Assessment, this book is a must!

Dive into the world of data visualization with "Getting Started with Tableau 2018.x." This comprehensive guide introduces you to both the fundamental and advanced functionalities of Tableau 2018.x, making it easier to create impactful data visualizations. Learn to unlock Tableau's full potential through practical examples and clear explanations. What this Book will help me do Understand the new Tableau 2018.x features like density, extensions, and transparency and how to leverage them. Learn how to connect to data sources, perform transformations, and build efficient data models to support your analysis. Master visualization techniques to design effective and insightful dashboards tailored to business needs. Explore advanced concepts such as calculations, cross-database joins, and data blending to handle complex scenarios. Develop the confidence to publish and interact with content on Tableau Server and share your insights effectively. Author(s) None Guillevin and None Pires are data visualization experts with extensive experience using Tableau. They aim to make data analysis accessible through hands-on examples and easy-to-follow explanations. Their writing balances clear instruction with practical application, making advanced concepts understandable for all readers. Who is it for? This book is ideal for beginners or experienced BI professionals who wish to gain expertise in Tableau 2018.x. It caters to aspiring analysts and business professionals looking to answer complex business-specific questions through data visualization. Regardless of prior experience in Tableau or other BI tools, this book provides value through a structured learning approach.

D3.js Quick Start Guide is your go-to resource for mastering D3.js, a powerful JavaScript library for creating interactive visualizations in the browser. This book walks you through core concepts, from building scatter plots to creating force-directed graphs, helping you go from beginner to creating stunning visual data representations. What this Book will help me do Create interactive scatter plots showcasing data relationships. Implement bar graphs that dynamically update from API data. Design animated pie charts for visually appealing representations. Develop force-directed graphs to represent networked data. Leverage GeoJSON data for building informative interactive maps. Author(s) None Huntington is an experienced web developer with a clear knack for turning complex topics into understandable concepts. With expertise in data visualization and web technologies, Huntington explains technical subject matter in a friendly and approachable manner, ensuring learners grasp both theoretical and practical aspects effectively. Who is it for? This book is ideal for web developers and data enthusiasts eager to learn how to represent data via interactive visualizations using D3.js. If you have a basic understanding of JavaScript and are looking to enhance your web development skillset with dynamic visualization techniques, this guide is perfect for you. Through easy-to-follow examples, you'll get up to speed quickly and start building professional-looking visualizations right away. Whether you're a data scientist, interactive news developer, or just interested in bringing data to life, this book is your key to mastering D3.js.

Transform your R programming into interactive web applications with "Web Application Development with R Using Shiny." This book takes you step-by-step through creating dynamic user interfaces and web solutions with the R Shiny package, empowering you to build impactful tools that showcase your data. What this Book will help me do Create interactive web applications using R Shiny. Apply JavaScript for added functionality and customization in Shiny apps. Effortlessly deploy Shiny apps online for accessibility. Understand Shiny UI functions to design effective user interfaces. Leverage data visualization techniques for insightful analytics in apps. Author(s) Chris Beeley and Shitalkumar R. Sukhdeve bring their profound expertise in R programming and Shiny development to this book. Chris is an experienced data scientist passionate about interactive data solutions, while Shitalkumar, with a strong computing background, shares his hands-on insights. Their collaborative and tutorial approach ensures learners grasp each concept smoothly. Who is it for? This book is ideal for R programmers eager to transition from static data evaluation to engaging, interactive web applications. It caters to professionals and enthusiasts seeking practical, hands-on coding guidance. Readers should have foundational R programming knowledge, ensuring a smooth transition into Shiny concepts.

Learning is an empirical phenomenon whereby people or organisations undergo a level of efficiency improvement with recurring tasks. Alan Jones pragmatic guide to this important element within estimating introduces two key learning curve models: Wright and Crawford and explains where, how and when to apply them.