Introduction to Data Visualization

Learn the essence of data science and visualization using R in no time at allAbout This Book- Become a pro at making stunning visualizations and dashboards quickly and without hassle- For better decision making in business, apply the R programming language with the help of useful statistical techniques.- From seasoned authors comes a book that offers you a plethora of fast-paced techniques to detect and analyze data patternsWho This Book Is ForIf you are an aspiring data scientist or analyst who has a basic understanding of data science and has basic hands-on experience in R or any other analytics tool, then R Data Science Essentials is the book for you.What You Will Learn- Perform data preprocessing and basic operations on data- Implement visual and non-visual implementation data exploration techniques- Mine patterns from data using affinity and sequential analysis- Use different clustering algorithms and visualize them- Implement logistic and linear regression and find out how to evaluate and improve the performance of an algorithm- Extract patterns through visualization and build a forecasting algorithm- Build a recommendation engine using different collaborative filtering algorithms- Make a stunning visualization and dashboard using ggplot and R shinyIn DetailWith organizations increasingly embedding data science across their enterprise and with management becoming more data-driven it is an urgent requirement for analysts and managers to understand the key concept of data science. The data science concepts discussed in this book will help you make key decisions and solve the complex problems you will inevitably face in this new world.R Data Science Essentials will introduce you to various important concepts in the field of data science using R. We start by reading data from multiple sources, then move on to processing the data, extracting hidden patterns, building predictive and forecasting models, building a recommendation engine, and communicating to the user through stunning visualizations and dashboards.By the end of this book, you will have an understanding of some very important techniques in data science, be able to implement them using R, understand and interpret the outcomes, and know how they helps businesses make a decision.Style and approachThis easy-to-follow guide contains hands-on examples of the concepts of data science using R.

Translate your data into info-graphics using popular packages in RAbout This Book* Use R's popular packages-such as ggplot2, ggvis, ggforce, and more-to create custom, interactive visualization solutions.* Create, design, and build interactive dashboards using Shiny* A highly practical guide to help you get to grips with the basics of data visualization techniques, and how you can implement them using RWho This Book Is ForIf you are looking to create custom data visualization solutions using the R programming language and are stuck somewhere in the process, this book will come to your rescue. Prior exposure to packages such as ggplot2 would be useful but not necessary. However, some R programming knowledge is required.What You Will Learn* Get to know various data visualization libraries available in R to represent data* Generate elegant codes to craft graphics using ggplot2, ggvis and plotly* Add elements, text, animation, and colors to your plot to make sense of data* Deepen your knowledge by adding bar-charts, scatterplots, and time series plots using ggplot2* Build interactive dashboards using Shiny.* Color specific map regions based on the values of a variable in your data frame* Create high-quality journal-publishable scatterplots* Create and design various three-dimensional and multivariate plotsIn DetailR is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions.This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using ShinyBy the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision.Style and approachThis book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization with R. You will learn to leverage the power of R and ggplot2 to create highly customizable data visualizations of varying complexities. The readers will then learn how to create, design, and build interactive dashboards using Shiny.

Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis. You'll see how to use R to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually. With the popularity of the R language, the art and practice of creating data visualizations is no longer the preserve of mathematicians, statisticians, or cartographers. As technology leaders, we can gather metrics around what we do and use data visualizations to communicate that information. Pro Data Visualization using R and JavaScript combines the power of the R language with the simplicity and familiarity of JavaScript to display clear and informative data visualizations. Gathering and analyzing empirical data is the key to truly understanding anything. We can track operational metrics to quantify the health of our products in production. We can track quality metrics of our projects, and even use our data to identify bad code. Visualizing this data allows anyone to read our analysis and easily get a deep understanding of the story the data tells.

Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization About This Book Learn how to set up an optimal Python environment for data visualization Understand how to import, clean and organize your data Determine different approaches to data visualization and how to choose the most appropriate for your needs Who This Book Is For If you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you. What You Will Learn Introduce yourself to the essential tooling to set up your working environment Explore your data using the capabilities of standard Python Data Library and Panda Library Draw your first chart and customize it Use the most popular data visualization Python libraries Make 3D visualizations mainly using mplot3d Create charts with images and maps Understand the most appropriate charts to describe your data Know the matplotlib hidden gems Use plot.ly to share your visualization online In Detail Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python. Style and approach A step-by-step recipe based approach to data visualization. The topics are explained sequentially as cookbook recipes consisting of a code snippet and the resulting visualization."

"MATLAB Graphics and Data Visualization Cookbook" will serve as your handbook in recipe format with ample screenshots. Each independent recipe will help you in achieving target-oriented solutions to your problems with concise explanation. For those who are already using MATLAB for their computational needs but need to also harness its powerful visualization capabilities.

This book provides visualizations of many topics in general physics. The aim is to have an interactive MATLAB script wherein the user can vary parameters in a specific problem and then immediately see the outcome by way of dynamic "movies" of the response of the system in question. MATLAB tools are used throughout and the software scripts accompany the text in Symbolic Mathematics, Classical Mechanics, Electromagnetism, Waves and Optics, Gases and Fluid Flow, Quantum Mechanics, Special and General Relativity, and Astrophysics and Cosmology. The emphasis is on building up an intuition by running many different parametric choices chosen actively by the user and watching the subsequent behavior of the system.Physics books using MATLAB do not have the range -- or the intent -- of this text. They are rather steeped in technical detail. Symbolic math is used extensively and is integral to the aim of using MATLAB tools to accomplish the technical aspects of problem solving.

About this book. Gives the reader hands on example-base experience for simulating dynamical models in MATLAB(r)/Simulink(r) and animating them in VRML . More than 150 images describe each step in the model realizations helping readers to understand them visually . Diverse examples and profound problem treatment enable the reader to animate complex dynamical problems m-files, Simulink models, VRML files and jpegs available for download provide full solutions for the end-of-chapter problems Virtual Reality and Animation for MATLAB(r) and Simulink(r) Users demonstrates the simulation and animation of physical systems using the MATLAB(r) Virtual Reality Toolbox (virtual models are created in V-Realm Builder). The book is divided into two parts; the first addresses MATLAB(r) and the second Simulink(r). The presentation is problem-based with each chapter teaching the reader a group of essential principles in the context of a step-by-step solution to a particular issue. Examples of the systems covered include mass-spring-dampers, a crank-slider mechanism and a moving vehicle. The examples are given in ascending level of difficulty and contain MATLAB(r)/Simulink(r) codes deliberately simplified so that readers can focus on: understanding how to link a 3-d virtual scene to MATLAB(r)/Simulink(r); and manipulating the 3-d virtual scene in MATLAB(r)/Simulink(r). When studied in sequence, the chapters of this text form a coherent whole enabling the reader to gain a thorough expertise in virtual simulation and animation of dynamical models using MATLAB(r)/Simulink(r). Individual chapters stand on their own, however, so that readers interested in a particular system can concentrate on it easily. Problemsare provided in each chapter to give practice in the techniques demonstrated and to extend the range of the systems studied, for example, into the control sphere. Solution code for these problems can be downloaded from insert URL. Whether modeling the dynamics of a simple pendulum, a robot arm or a moving car, animation of a dynamical model can enliven and encourage understanding of mechanical systems and thus contribute to control design. Virtual Reality and Animation for MATLAB(r) and Simulink(r) Users will be instructive and interesting to anyone, researcher or student, working with the dynamics of physical systems. Readers are assumed to have some familiarity with MATLAB(r)."