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| Author | : Atmajitsinh Gohil |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 236 |
| Release | : 2015-01-29 |
| Genre | : Computers |
| ISBN | : 1783989513 |
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.
| Author | : Winston Chang |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 414 |
| Release | : 2013 |
| Genre | : Computers |
| ISBN | : 1449316956 |
"Practical recipes for visualizing data"--Cover.
| Author | : Vitor Bianchi Lanzetta |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 358 |
| Release | : 2017-11-22 |
| Genre | : Computers |
| ISBN | : 1788394070 |
Translate your data into info-graphics using popular packages in R About 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 R Who This Book Is For If 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 plots In Detail R 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 Shiny By the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision. Style and approach This 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.
| Author | : Kieran Healy |
| Publisher | : Princeton University Press |
| Total Pages | : 292 |
| Release | : 2018-12-18 |
| Genre | : Social Science |
| ISBN | : 0691181624 |
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
| Author | : Paul Teetor |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 438 |
| Release | : 2011-03-03 |
| Genre | : Computers |
| ISBN | : 1449307264 |
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author
| Author | : Claus O. Wilke |
| Publisher | : O'Reilly Media |
| Total Pages | : 390 |
| Release | : 2019-03-18 |
| Genre | : Computers |
| ISBN | : 1492031054 |
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story
| Author | : Hadley Wickham |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 521 |
| Release | : 2016-12-12 |
| Genre | : Computers |
| ISBN | : 1491910364 |
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
| Author | : Igor Milovanovic |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 302 |
| Release | : 2015-11-30 |
| Genre | : Computers |
| ISBN | : 1784394947 |
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.
| Author | : JD Long |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 625 |
| Release | : 2019-06-21 |
| Genre | : Computers |
| ISBN | : 1492040630 |
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data
| Author | : Shweta Sankhe-Savale |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 504 |
| Release | : 2016-12-26 |
| Genre | : Computers |
| ISBN | : 1784392987 |
Create beautiful data visualizations and interactive dashboards with Tableau About This Book Delve into the features and functionalities of Tableau from the ground up with this step-by-step guide that has over 50 "follow-me" recipes Build rich visualizations to effectively highlight the underlying trends and patterns in your data Build beautiful interactive dashboards and storyboards to stitch your visualizations together and tell a story Who This Book Is For This book is for anyone who wishes to use Tableau. It will be of use to both beginners who want to learn Tableau from scratch and to more seasoned users who simply want a quick reference guide. This book is a ready reckoner guide for you. The book will be such that both new & existing Tableau users who don't know, or can't recall how to perform different Tableau tasks can use the book and be benefited from it. What You Will Learn Get to grips with the Tableau workspace and terminologies and understand what data sources you can connect Learn to create basic charts like bar chart, stacked bar, pie chart, line chart, area chart, tree map & word cloud Go even further with more advanced visualizations such as scatter plot, box & whiskers plot, dual axis, bullet chart, Histograms, Maps, etc Use pre-defined calculation and change its scope and direction to affect outcome Learn to define Parameters and call them into parametric calculations that provide outcomes based on user inputs Build Dashboards and use Actions to link multiple sheets on the dashboard Connect to multiple data sources using Data Blending, Multiple Table Join within the same data source as well as across data sources, Custom SQL and learn to work with data Extracts Compute statistical trends, build forecasting models and use Reference lines for benchmarking In Detail Data is everywhere and everything is data! Visualization of data allows us to bring out the underlying trends and patterns inherent in the data and gain insights that enable faster and smarter decision making. Tableau is one of the fastest growing and industry leading Business Intelligence platforms that empowers business users to easily visualize their data and discover insights at the speed of thought. Tableau is a self-service BI platform designed to make data visualization and analysis as intuitive as possible. Creating visualizations with simple drag-and-drop, you can be up and running on Tableau in no time. Starting from the fundamentals such as getting familiarized with Tableau Desktop, connecting to common data sources and building standard charts; you will walk through the nitty gritty of Tableau such as creating dynamic analytics with parameters, blended data sources, and advanced calculations. You will also learn to group members into higher levels, sort the data in a specific order & filter out the unnecessary information. You will then create calculations in Tableau & understand the flexibility & power they have and go on to building story-boards and share your insights with others. Whether you are just getting started or whether you need a quick reference on a "how-to" question, This book is the perfect companion for you Style and approach This cookbook takes a step-by-step approach and the text systematically evolves to cover more involved functionalities. Every recipe includes illustrative screenshots which provide a detailed visual resource for each step.
