Data Visualisation

Data Visualisation PDF
Author: Andy Kirk
Publisher: SAGE
ISBN: 1526482908
Size: 36.23 MB
Format: PDF, ePub, Mobi
Category : Reference
Languages : en
Pages : 328
View: 131

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One of the "six best books for data geeks" - Financial Times With over 200 images and extensive how-to and how-not-to examples, this new edition has everything students and scholars need to understand and create effective data visualisations. Combining ‘how to think’ instruction with a ‘how to produce’ mentality, this book takes readers step-by-step through analysing, designing, and curating information into useful, impactful tools of communication. With this book and its extensive collection of online support, readers can: - Decide what visualisations work best for their data and their audience using the chart gallery - See data visualisation in action and learn the tools to try it themselves - Follow online checklists, tutorials, and exercises to build skills and confidence - Get advice from the UK’s leading data visualisation trainer on everything from getting started to honing the craft. Explore more resources about data visualisation and Andy Kirk.

Low Latency Big Data Visualisation

Low latency big data visualisation PDF
Author: Tan Jerome, Nicholas
Publisher: KIT Scientific Publishing
ISBN: 3731509407
Size: 69.95 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 242
View: 6232

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Introductory R A Beginner S Guide To Data Visualisation Statistical Analysis And Programming In R

Introductory R  A Beginner s Guide to Data Visualisation  Statistical Analysis and Programming in R PDF
Author: Robert Knell
Publisher: Robert Knell
ISBN: 0957597118
Size: 38.22 MB
Format: PDF
Category :
Languages : en
Pages : 531
View: 481

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R is now the most widely used statistical software in academic science and it is rapidly expanding into other fields such as finance. R is almost limitlessly flexible and powerful, hence its appeal, but can be very difficult for the novice user. There are no easy pull-down menus, error messages are often cryptic and simple tasks like importing your data or exporting a graph can be difficult and frustrating. Introductory R is written for the novice user who knows a little about statistics but who hasn't yet got to grips with the ways of R. This new edition is completely revised and greatly expanded with new chapters on the basics of descriptive statistics and statistical testing, considerably more information on statistics and six new chapters on programming in R. Topics covered include: A walkthrough of the basics of R's command line interface Data structures including vectors, matrices and data frames R functions and how to use them Expanding your analysis and plotting capacities with add-in R packages A set of simple rules to follow to make sure you import your data properly An introduction to the script editor and advice on workflow A detailed introduction to drawing publication-standard graphs in R How to understand the help files and how to deal with some of the most common errors that you might encounter. Basic descriptive statistics The theory behind statistical testing and how to interpret the output of statistical tests Thorough coverage of the basics of data analysis in R with chapters on using chi-squared tests, t-tests, correlation analysis, regression, ANOVA and general linear models What the assumptions behind the analyses mean and how to test them using diagnostic plots Explanations of the summary tables produced for statistical analyses such as regression and ANOVA Writing your own functions in R Using table operations to manipulate matrices and data frames Using conditional statements and loops in R programmes. Writing longer R programmes. The techniques of statistical analysis in R are illustrated by a series of chapters where experimental and survey data are analysed. There is a strong emphasis on using real data from real scientific research, with all the problems and uncertainty that implies, rather than well-behaved made-up data that give ideal and easy to analyse results.

Digital Personalized Health And Medicine

Digital Personalized Health and Medicine PDF
Author: L.B. Pape-Haugaard
Publisher: IOS Press
ISBN: 1643680838
Size: 36.71 MB
Format: PDF, Mobi
Category : Medical
Languages : en
Pages : 1496
View: 2342

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Digital health and medical informatics have grown in importance in recent years, and have now become central to the provision of effective healthcare around the world. This book presents the proceedings of the 30th Medical Informatics Europe conference (MIE). This edition of the conference, hosted by the European Federation for Medical Informatics (EFMI) since the 1970s, was due to be held in Geneva, Switzerland in April 2020, but as a result of measures to prevent the spread of the Covid19 pandemic, the conference itself had to be cancelled. Nevertheless, because this collection of papers offers a wealth of knowledge and experience across the full spectrum of digital health and medicine, it was decided to publish the submissions accepted in the review process and confirmed by the Scientific Program Committee for publication, and these are published here as planned. The 232 papers are themed under 6 section headings: biomedical data, tools and methods; supporting care delivery; health and prevention; precision medicine and public health; human factors and citizen centered digital health; and ethics, legal and societal aspects. A 7th section deals with the Swiss personalized health network, and section 8 includes the 125 posters accepted for the conference. Offering an overview of current trends and developments in digital health and medical informatics, the book provides a valuable information resource for researchers and health practitioners alike.

Principal Manifolds For Data Visualization And Dimension Reduction

Principal Manifolds for Data Visualization and Dimension Reduction PDF
Author: Alexander N. Gorban
Publisher: Springer Science & Business Media
ISBN: 3540737502
Size: 51.85 MB
Format: PDF
Category : Technology & Engineering
Languages : en
Pages : 340
View: 5471

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The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described. Presentation of algorithms is supplemented by case studies. The volume ends with a tutorial PCA deciphers genome.

Data Visualization

Data Visualization PDF
Author: Robert Grant
Publisher: Chapman & Hall/CRC
ISBN: 9781138707603
Size: 78.44 MB
Format: PDF, ePub, Mobi
Category : Information visualization
Languages : en
Pages : 248
View: 4045

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This is the age of data. There are more innovations and more opportunities for interesting work with data than ever before, but there is also an overwhelming amount of quantitative information being published every day. Data visualisation has become big business, because communication is the difference between success and failure, no matter how clever the analysis may have been. The ability to visualize data is now a skill in demand across business, government, NGOs and academia. Data Visualization: Charts, Maps, and Interactive Graphics gives an overview of a wide range of techniques and challenges, while staying accessible to anyone interested in working with and understanding data. Features: Focusses on concepts and ways of thinking about data rather than algebra or computer code. Features 17 short chapters that can be read in one sitting. Includes chapters on big data, statistical and machine learning models, visual perception, high-dimensional data, and maps and geographic data. Contains more than 125 visualizations, most created by the author. Supported by a website with all code for creating the visualizations, further reading, datasets and practical advice on crafting the images. Whether you are a student considering a career in data science, an analyst who wants to learn more about visualization, or the manager of a team working with data, this book will introduce you to a broad range of data visualization methods.

Data Visualisation 2003

Data Visualisation 2003 PDF
Author: Georges-Pierre Bonneau
Publisher:
ISBN: 9781581136982
Size: 78.39 MB
Format: PDF
Category :
Languages : en
Pages :
View: 6373

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Data Visualization Handbook

Data Visualization Handbook PDF
Author: Juuso Koponen
Publisher: Aalto korkeakoulusäätiö
ISBN: 9526074483
Size: 48.78 MB
Format: PDF, ePub, Mobi
Category : Design
Languages : en
Pages : 352
View: 2257

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The data visualization handbook is a practical guide to creating compelling graphics to explain or explore data. It is primarily aimed for designers, journalists, researchers, analysts, and other professionals who want to learn the basics of visualization, but also includes plenty of material for people with intermediate level visualization skills.

Handbook Of Data Visualization

Handbook of Data Visualization PDF
Author: Chun-houh Chen
Publisher: Springer Science & Business Media
ISBN: 9783540330370
Size: 32.59 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 936
View: 5576

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Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools such as mosaic plots, parallel coordinate plots, and linked views. Coverage also examines graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well software for graphics.

Data Mining And Data Visualization

Data Mining and Data Visualization PDF
Author:
Publisher: Elsevier
ISBN: 9780080459400
Size: 26.70 MB
Format: PDF, Kindle
Category : Mathematics
Languages : en
Pages : 800
View: 986

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Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. Distinguished contributors who are international experts in aspects of data mining Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions Thorough discussion of data visualization issues blending statistical, human factors, and computational insights

Graph Based Clustering And Data Visualization Algorithms

Graph Based Clustering and Data Visualization Algorithms PDF
Author: Ágnes Vathy-Fogarassy
Publisher: Springer Science & Business Media
ISBN: 1447151585
Size: 15.72 MB
Format: PDF
Category : Computers
Languages : en
Pages : 110
View: 6297

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This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on the synergistic combination of clustering, graph-theory, neural networks, data visualization, dimensionality reduction, fuzzy methods, and topology learning. The work contains numerous examples to aid in the understanding and implementation of the proposed algorithms, supported by a MATLAB toolbox available at an associated website.

Data Visualization

Data Visualization PDF
Author: Frits H. Post
Publisher: Springer Science & Business Media
ISBN: 9781402072598
Size: 76.38 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 453
View: 4688

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Data visualization is currently a very active and vital area of research, teaching and development. The term unites the established field of scientific visualization and the more recent field of information visualization. The success of data visualization is due to the soundness of the basic idea behind it: the use of computer-generated images to gain insight and knowledge from data and its inherent patterns and relationships. A second premise is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes, and simulations involving data sets from diverse scientific disciplines and large collections of abstract data from many sources. These concepts are extremely important and have a profound and widespread impact on the methodology of computational science and engineering, as well as on management and administration. The interplay between various application areas and their specific problem solving visualization techniques is emphasized in this book. Reflecting the heterogeneous structure of Data Visualization, emphasis was placed on these topics: -Visualization Algorithms and Techniques; -Volume Visualization; -Information Visualization; -Multiresolution Techniques; -Interactive Data Exploration. Data Visualization: The State of the Art presents the state of the art in scientific and information visualization techniques by experts in this field. It can serve as an overview for the inquiring scientist, and as a basic foundation for developers. This edited volume contains chapters dedicated to surveys of specific topics, and a great deal of original work not previously published illustrated by examples from a wealth of applications. The book will also provide basic material for teaching the state of the art techniques in data visualization. Data Visualization: The State of the Art is designed to meet the needs of practitioners and researchers in scientific and information visualization. This book is also suitable as a secondary text for graduate level students in computer science and engineering.