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pCreate and publish your own interactive data visualization projects on the web--even if you have little or no experience with data visualization or web development. It's inspiring and fun with this friendly, accessible, and practical hands-on introduction. This fully updated and expanded second edition takes you through the fundamental concepts and methods of D3, the most powerful JavaScript library for expressing data visually in a web browser.ppIdeal for designers with no coding experience, reporters exploring data journalism, and ianyonei who wants to visualize and share data, this step-by-step guide will also help you expand your web programming skills by teaching you the basics of HTML, CSS, JavaScript, and SVG.pulliLearn D3 4.x--the latest D3 version--with downloadable code and over 140 examplesliliCreate bar charts, scatter plots, pie charts, stacked bar charts, and force-directed graphsliliUse smooth, animated transitions to show changes in your dataliliIntroduce interactivity

Interactive Data Visualization for the Web | Murray Scott | Twarda

This is the first book written on using Blender an open source visualization suite widely used in the entertainment and gaming industries for scientific visualization. It is a practical and interesting introduction to Blender for understanding key parts of 3D rendering and animation that pertain to the sciences via step- by-step guided tutorials. 3D Scientific Visualization with Blender takes you through an understanding of 3D graphics and modeling for different visualization scenarios in the physical sciences. This includes guides and tutorials for - Understanding and manipulating the interface - Generating 3D models - Understanding lighting, animation, and camera control - Scripting data import with the Python API The agility of Blender and its well organized Python API make it an exciting and unique visualization suite every modern scientificengineering workbench should include. Blender provides multiple scientific visualizations including solid modelssurfacesrigid body simulations 

3D Scientific Visualization with Blender | Kent Brian R. | Twarda | Twarda

pbIntroduces professionals and scientists to statistics and machine learning using the programming language Rbp pWritten by and for practitioners, this book provides an overall introduction to R, focusing on tools and methods commonly used in data science, and placing emphasis on practice and business use. It covers a wide range of topics in a single volume, including big data, databases, statistical machine learning, data wrangling, data visualization, and the reporting of results. The topics covered are all important for someone with a sciencemath background that is looking to quickly learn several practical technologies to enter or transition to the growing field of data science. p piThe Big R-Book for Professionals From Data Science to Learning Machines and Reporting with Ri includes nine parts, starting with an introduction to the subject and followed by an overview of R and elements of statistics. The third part revolves around data, while the fourth focuses on data wrangling. Pa

The Big R | Book | de Brouwer Philippe J. S. | Twarda

pstrongemANOVA and Mixed Models A Short Introduction Using Remstrong provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA models, but also models for more advanced designs and mixed models, which are common in many practical applications.ppFeaturespul ul ul liAccessible to readers with a basic background in probability and statisticsli liCovers fundamental concepts of experimental design and cause-effect relationshipsli liIntroduces classical ANOVA mo

ANOVA and Mixed Models | Meier Lukas | Twarda

pThis is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. pbbrbrpKey Features pbrbrulbbrbrpbrbrliProvides a comprehensive, practical and accessible introduction to multivariate analysis. librbrppbrbrpbrbrliKeeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. librbrppbrbrpbrbrliIncludes lots of detailed worked examples, guidance on computing, a

Practical Multivariate Analysis | Afifi Abdelmonem | Paperback | Twarda

ppppMATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as CC or Java.pemMATLAB Control Systems Engineeringem introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to design and analyze control systems using MATLAB's specialized Control Systems Toolbox. The Control Systems Toolbox offers an extensive range of tools for classical and modern control design. Using these tools you can create models of linear time-invariant systems in transfer function, zero-p

MATLAB Control Systems Engineering | Lopez Cesar | Paperback | Twarda

pbChapter 1 Data Visualization with LeatherbbrppChapter Goal Introduce readers to the data visualization with a simple library leatherppNo of pages 15ppSub - Topics pp1. Introduction to leatherpp2. Installation to leatherpp3. Various types of graphs with leatherppppbChapter 2 Introduction to the Scientific Python Ecosystem and NumPybppChapter Goal Explore Scientific Python 3 ecosystem and constituent member libraries. We will also learn basics of the NumPy multidimensional data structure Ndarrays.ppNo of pages 15ppSub - Topics pp1. Scientific Python 3 Ecosystempp2. Member librariespp3. Installation of NumPypp4. NumPy basicspp5. NdarraysppppbChapter 3 NumPy Routines and Visualization with MatplotlibbpChapter goal - Learn to visualize data with Matplotlib. Readers working in the data science and scientific domains will be thrilled to get started with this.pppNo of pages 15ppSub - Topics pp1. NumPy Ndarray creation Routinespp2. Installation of Matplotlibpp3. Visualization with Matplotlibp

Practical Python Data Visualization | Pajankar Ashwin | Twarda

pThis book provides a practical approach to dealing with the Data Life Cycle in the business environment, including p ul liAn extensive overview of R and RStudio using both simple and large datasetsli liInteractive examples of using Git, GitHub, and GitKraken to manage versions and collaborate with othersli liGuidance on collecting and cleaning data - An overview of using PostgreSQL databases from within Rli liAn introduction to data analysis with RCmdrli liAn overview of data visualization with ggplot2li ul

Introduction to R for Business | Adair Troy A. | Paperback | Twarda

strongThe best guide for beginners to get started with data analytics using Python strongpstrongstrongbrppA step by step guide to data analytics and its applications using easy to understand and practical examples.brppInside you will learn brpulliVecotrized computationbrliliNumPysbrliliAn introduction to PandasliliPredictive modellingbrlilibbData visualization techniquesliulpand so much more ppWhatever the type of data you're dealing with, you will learn the A-Z of managing and visualizing it with this book. Grab your copy today pstrongBONUS Get the e-book absolutely free when you purchase the paperback with Kindle matchbook strong

Python Data Analytics | Booth Travis | Twarda

bCreate stunning interactive dashboard applications in Python with the Dash visualization and data analysis tool. Build interfaces that make sense of your data, and make it pretty.b pA swift and practical introduction to building interactive data visualization apps in Python, known as dashboards. You've seen dashboards before think election result visualizations you can update in real time, or population maps you can filter by demographic. With the Python Dash library you'll create analytic dashboards that present data in effective, usable, elegant ways in just a few lines of code. pThe book is fast-paced and caters to those entirely new to dashboards. It will talk you through the necessary software, then get straight into building the dashboards themselves. You'll learn the basic format of a Dash app in a Twitter analysis dashboard that tracks numbers of likes over time. You'll then build up skills through three more sophisticated projects. The first compares world data in three areas

The Book of Dash | Schroeder Adam | Twarda

pstrongemANOVA and Mixed Models A Short Introduction Using Remstrong provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA models, but also models for more advanced designs and mixed models, which are common in many practical applications.pb pFeaturesp ul ulb ppul liAccessible to readers with a basic background in probability and statisticsli liCovers fundamental concepts of experimental design and cause-effect relationshipsli liIntroduces classical AN

Anova and Mixed Models | Meier Lukas | Twarda

pThis is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. pb pKey Features p ulb p liProvides a comprehensive, practical and accessible introduction to multivariate analysis. li pp p liKeeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. li pp p liIncludes lots of detailed worked examples, guidance on computing, and exercises. li pp p liUpdate

Practical Multivariate Analysis | Afifi Abdelmonem | Twarda | Twarda

pBuild and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how to use Python and popular libraries to build trading models and strategies from scratch. It covers practical trading strategies coupled with step-by-step implementations that touch upon a wide range of topics, including data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning, all coupled with practical examples in Python.ppPart one of iQuantitative Trading Strategies with Pythoni covers the fundamentals of trading strategies, including an introduction to quantitative trading, the electronic market, risk and return, and forward and futures contracts. Part two introduces common trading strategies, including trend-following, momentum trading, and evaluation process via backtesting. Part three covers more advanced topics, including statistical arbitrage using hypothesis testing, op

Quantitative Trading Strategies Using Python | Liu Peng | Twarda

pMATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as CC or Java.pppProgramming MATLAB for Numerical Analysis introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. You will first become familiar with the MATLAB environment, and then you will begin to harness the power of MATLAB. You will learn the MATLAB language, starting with an introduction to variables, and how to manipulate numbers, vectors, matrices, arrays and character strings. You will learn about MATLAB's high-precision capabilities, and how you can use MATLAB to solve problems, making use of arithmetic, relational and lo

MATLAB Programming for Numerical Analysis | Lopez Cesar | Paperback | Twarda

This introduction to visualization techniques and statistical models for second language research focuses on three types of data continuous, binary, and scalar, helping readers to understand regression models fully and to apply them in their work. Garcia offers advanced coverage of Bayesian analysis, simulated data, exercises, implementable script code, and practical guidance on the latest R software packages. The book, also demonstrating the benefits to the L2 field of this type of statistical work, is a resource for graduate students and researchers in second language acquisition, applied linguistics, and corpus linguistics who are interested in quantitative data analysis.

Data Visualization and Analysis in Second Language Research | Garcia Guilherme D. | Paperback | Twarda

pR is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. pUnderscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance ANOVA, correlation, and linear and nonlinear regression analyses. This volume also includes a section on ad

A Primer in Biological Data Analysis and Visualization Using R | Hartvigsen Gregg | Paperback | Twarda

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pHow can music withstand the death and destruction brought on by war Global conflicts of the 20th century fundamentally transformed not only national boundaries, power relations, and global economies, but also the arts and culture of every nation involved. An important, unacknowledged aspect of these conflicts is that they have unique musical soundtracks. iMusic in World War IIi explores how music and sound took on radically different dimensions in the United States and Europe before, during, and after World War II. Additionally, the collection examines the impact of radio and film as the disseminators of the war's musical soundtrack. Contributors contend that the European and American soundtrack of World War II was largely one of escapism rather than the lofty, solemn, heroic, and celebratory mode of war music in the past. Furthermore, they explore the variety of experiences of populations forced from their homes and interned in civilian and POW camps in Europe and the United States, 

Music in World War II | Potter Pamela M. | Twarda

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data visualization a practical introduction