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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 ofmathematicians, statisticians, or cartographers.
Get A Copy. Paperback , pages. Published June 19th by Apress first published June 12th More Details Other Editions 1.
Friend Reviews. To see what your friends thought of this book, please sign up. Lists with This Book. This book is not yet featured on Listopia. Dynamic UI. Update input demo. Reactive programming These examples illustrate some useful features and idioms of Shiny's reactive programming framework. Observer demo. Reactive poll and file reader.
Advanced Shiny These examples show how to extend Shiny and use advanced features.
Server-to-client custom messages. Client data and query string. Image output.
Chat room. Generating reports. Download knitr Reports. Selectize rendering methods. Option groups for server-side selectize. Creating a UI from a loop. Progress bar example. Bookmarking - URL. Bookmarking with updateQueryString. Modal dialogs. Interactive plots These examples show how to use Shiny's interactive plotting features. Plot interaction - basic. Plot interaction - advanced. Although strongly based on the ggplot2 package, other approaches are included as well.
This is a collection of the discussion lists from Macroeconomics. Item 2 is for data visualization. And item 3 is for general discussion regarding world news. Data Visualization Project […] This study aims at investigating how the change of information dissemination process would affect the window-dressing behaviors of mutual fund managers. By convention, window-dressing is defined as the portfolio manipulations right before the quarter-end date, when all the fund managers are required to disclosure their holding firms of that date.
Over the past decades, technological progresses largely change the way how information disseminates, and these further influence the information flow of capital markets. This is a collection of data visualization handouts from Macroeconomics. The book covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations.
You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers.
Data Science and Visualizations with R […] This is a course on the use of tidyverse packages tidyverse provides a complete suite of modern data-handling tools. It is an essential toolbox for any data scientist using R. The tidyverse package is designed to be easy to install. This course will dive into using tidyverse. It will assume you have already installed r and rstudio and how some familiarity on how to use the rstudio.
This book will use the nycflights13 dataset This package contains information about all flights that departed from NYC in , flights with 16 variables. Regarding further use of this material contact Paul.
Some of the material is inspired by the official shiny tutorial and Plotly for R by Carston Sievert. Each chapter features static visualizations relevant to the games that week.
Greatly extended, fully-interactive and constantly updated versions can be found on the accompanying dashboard site Additional data is available at the Premier League Web site Most of the underlying data is unofficial, unguaranteed error-free and available for a million dollars. A practical introduction.