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Communication is a key part of the data science process. Dashboards are a popular way to present data in a cohesive visual display. In this course you'll learn how to assemble your results into a polished dashboard using the flexdashboard package. This can be as simple as adding a few lines of R Markdown to your existing code, or as rich as a fully interactive Shiny-powered experience. You will learn about the spectrum of dashboard creation tools available in R and complete this course with the ability to produce a professional quality dashboard.
In this chapter you will learn how R Markdown and the flexdashboard package are used to create a dashboard, and how to customize the layout of components on your dashboard.
Data Visualization for Dashboards
This chapter will introduce the many options for including data visualizations in your dashboard. You'll learn about how to optimize your plots for display on the web.
In this chapter you will learn about other components that will allow you to create a complete dashboard. This includes ways to present everything from a single value to a complete dataset.Highlighting single values50 xpCreate value box100 xpCreate gauge100 xpColor indicators100 xpLinking100 xpDashboard Tables50 xpStatic table100 xpWeb-friendly table100 xpDT::datatable100 xpText for Dashboards50 xpCaptions100 xpCaptions with Inline Code100 xpStoryboards100 xpStoryboard Commentary100 xp
Adding Interactivity with Shiny
This chapter will demonstrate how you can use Shiny to make your dashboard interactive. You'll keep working with the San Francisco bike sharing data and build a dashboard for exploring this data set.Incorporating Shiny into Dashboards50 xpWhat adding Shiny to a flexdashboard means50 xpConverting our flexdashboard to use Shiny100 xpThe reactive dataframe pattern50 xpAdding Sidebar100 xpAdding User Input100 xpMaking the Dataframe Reactive100 xpMaking a Chart React to Inputs100 xpMaking All Charts React to Inputs100 xpCustomized inputs for charts50 xpApply Input to Single Chart100 xpMove Input to Chart Box100 xpCreate Global Input Sidebar100 xpCourse Recap50 xp
In the following tracksShiny Fundamentals
PrerequisitesBuilding Web Applications with Shiny in R
Director of Quantitative Mobility, TransLoc
Elaine is a data scientist at the transit technology company TransLoc, where she leads the team that creates quantitative tools for mobility decision making. A recurring theme throughout Elaine’s career has been improving the processes by which statistics and data science work is done. This includes a focus on iteratively delivering value to the end user, with R-generated dashboards representing one powerful tool for doing this. Elaine led the creation of a company-wide analytics tool created with the flexdashboard R package.
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I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.
Devon Edwards Joseph
Lloyds Banking Group
DataCamp is the top resource I recommend for learning data science.
Harvard Business School
DataCamp is by far my favorite website to learn from.
Decision Science Analytics, USAA