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Data Visualization Cookbook


Data Visualization Cookbook
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Tableau Data Visualization Cookbook


Tableau Data Visualization Cookbook
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Author : Ashutosh Nandeshwar
language : en
Publisher: Packt Publishing
Release Date : 2013

Tableau Data Visualization Cookbook written by Ashutosh Nandeshwar and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.


This Cookbook contains step-by-step instructions for Tableau users to create effective graphics. The book is designed in such a way that you can refer to it chapter by chapter; you can look at the list of recipes and read them in no particular order.You'll gain the most from this book if you have basic understanding of various chart types and of their importance. Knowing when to employ a certain graphic will be equally useful. This book will get you up to speed if you just started using Tableau. You'll find this book useful if you spend a lot of time conducting data analysis and creating reports.



R Data Visualization Cookbook


R Data Visualization Cookbook
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Author : Atmajitsinh Gohil
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-01-29

R Data Visualization Cookbook written by Atmajitsinh Gohil and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-29 with Computers categories.


If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.



Opengl Data Visualization Cookbook


Opengl Data Visualization Cookbook
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Author : Raymond C. H. Lo
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-08-24

Opengl Data Visualization Cookbook written by Raymond C. H. Lo and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-24 with Computers categories.


Over 35 hands-on recipes to create impressive, stunning visuals for a wide range of real-time, interactive applications using OpenGL About This Book Get acquainted with a set of fundamental OpenGL primitives and concepts that enable users to create stunning visuals of arbitrarily complex 2D and 3D datasets for many common applications Explore interactive, real-time visualization of large 2D and 3D datasets or models, including the use of more advanced techniques such as stereoscopic 3D rendering. Create stunning visuals on the latest platforms including mobile phones and state-of-the-art wearable computing devices Who This Book Is For This book is aimed at anyone interested in creating impressive data visualization tools using modern graphics hardware. Whether you are a developer, engineer, or scientist, if you are interested in exploring the power of OpenGL for data visualization, this book is for you. While familiarity with C/C++ is recommended, no previous experience with OpenGL is assumed. What You Will Learn Install, compile, and integrate the OpenGL pipeline into your own project Create interactive applications using GLFW to handle user inputs and the Android Sensor framework to detect gestures and motions on mobile devices Use OpenGL primitives to plot 2-D datasets such as time series dynamically Render complex 3D volumetric datasets with techniques such as data slicers and multiple viewpoint projection Render images, videos, and point cloud data from 3D range-sensing cameras using the OpenGL Shading Language (GLSL) Develop video see-through augmented reality applications on mobile devices with OpenGL ES 3.0 and OpenCV Visualize 3D models with meshes and surfaces using stereoscopic 3D technology In Detail OpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications. This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapter addresses different visualization problems encountered in real life and introduces the relevant OpenGL features and libraries in a modular fashion. By the end of this book, you will be equipped with the essential skills to develop a wide range of impressive OpenGL-based applications for your unique data visualization needs, on platforms ranging from conventional computers to the latest mobile/wearable devices. Style and approach This is an easy-to-follow, comprehensive Cookbook showing readers how to create an application with real-time, interactive data visualization in stereoscopic 3D. Each topic is explained in a step-by-step format. A range of hot topics is included, including data visualization on mobile and wearable platforms.



R Graphics Cookbook


R Graphics Cookbook
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Author : Winston Chang
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013

R Graphics Cookbook written by Winston Chang and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.


"Practical recipes for visualizing data"--Cover.



Python Data Visualization Cookbook Second Edition


Python Data Visualization Cookbook Second Edition
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Author : Igor Milovanovic
language : en
Publisher:
Release Date : 2015-11-30

Python Data Visualization Cookbook Second Edition written by Igor Milovanovic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-30 with Computers categories.


Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualizationAbout 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 needsWho This Book Is ForIf 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 onlineIn DetailPython 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 approachA 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.



Python Data Visualization Cookbook


Python Data Visualization Cookbook
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Author : Igor Milovanović
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-11-25

Python Data Visualization Cookbook written by Igor Milovanović and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-25 with Computers categories.


This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.



Data Visualization With D3 Js Cookbook


Data Visualization With D3 Js Cookbook
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Author : Nick Qi Zhu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-10-24

Data Visualization With D3 Js Cookbook written by Nick Qi Zhu and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-24 with Computers categories.


Packed with practical recipes, this is a step-by-step guide to learning data visualization with D3 with the help of detailed illustrations and code samples.If you are a developer familiar with HTML, CSS, and JavaScript, and you wish to get the most out of D3, then this book is for you. This book can also serve as a desktop quick-reference guide for experienced data visualization developers.



Matlab Graphics And Data Visualization Cookbook


Matlab Graphics And Data Visualization Cookbook
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Author : Nivedita Majumdar
language : en
Publisher: Packt Publishing
Release Date : 2012

Matlab Graphics And Data Visualization Cookbook written by Nivedita Majumdar and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.


"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.



Practical Data Science Cookbook


Practical Data Science Cookbook
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Author : Prabhanjan Tattar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-29

Practical Data Science Cookbook written by Prabhanjan Tattar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-29 with Computers categories.


Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization



Data Visualization


Data Visualization
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Author : Kieran Healy
language : en
Publisher: Princeton University Press
Release Date : 2018-12-18

Data Visualization written by Kieran Healy and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-18 with Social Science categories.


An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions