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Building Web Applications with Shiny in R

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

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4 Horas16 Videos61 Exercises

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Descrição do Curso

Shiny is an R package that makes it easy to build highly interactive web apps directly in R. Using Shiny, data scientists can create interactive web apps that allow your team to dive in and explore your data as dashboards or visualizations. If you want to bring your data to life, Shiny is the way to go! Using data about baby names, food ingredients, and UFO sightings, you'll build a variety of different Shiny apps that leverage different inputs and outputs. You’ll also learn the basics of reactive expressions. By the end of this course, you’ll have the Shiny skills you need to build your first app in R.

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1
Get Started with Shiny
Livre
To kick off the course you'll learn what a web app is and when you should build one, plus build a few apps of your own! You'll first learn to make text inputs and outputs in a few ways, including exploring the popularity of certain names over time.
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Introduction to Shiny
50 xp
Client vs. Server
50 xp
When to build a web-app?
100 xp
Build a "Hello, world" Shiny app
50 xp
Build a "Hello, world" Shiny app (2)
100 xp
"Hello, World" app input (UI)
100 xp
"Hello, World" app output (UI/Server)
100 xp
Build a babynames explorer Shiny app
50 xp
Add input (UI)
100 xp
Add output (UI/Server)
100 xp
Update layout (UI)
100 xp
Update output (server)
100 xp
2
Inputs, Outputs, and Layouts
In this chapter you will learn how to take advantage of different input and output options in shiny. You''ll learn the syntax for taking inputs from users and rendering different kinds of outputs, including text, plots, and tables.
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Inputs
50 xp
Selecting an input
100 xp
Add a select input
100 xp
Add a slider input to select year
100 xp
Outputs
50 xp
Add a table output
100 xp
Add an interactive table output
100 xp
Add interactive plot output
100 xp
Layouts and themes
50 xp
Sidebar layouts
100 xp
Tab layouts
100 xp
Themes
100 xp
Building apps
50 xp
App 1: Multilingual Greeting
100 xp
App 2: Popular Baby Names
100 xp
App 3: Popular Baby Names Redux
100 xp
3
Reactive Programming
In this chapter, you will learn about reactive programming. You will learn about reactive sources, conductors and endpoints and how they come together to drive the magic behind Shiny. You will also learn how to utilize your understanding of reactivity to build performant Shiny apps.
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Reactivity 101
50 xp
Source vs. Conductor vs. Endpoint
100 xp
Add a reactive expression
100 xp
Understanding reactive expressions
50 xp
Observers vs. reactives
50 xp
Add another reactive expression
100 xp
Does this have a side effect?
50 xp
Add an observer to display notifications
100 xp
Stop - delay - trigger
50 xp
Stop reactions with isolate()
100 xp
Delay reactions with eventReactive()
100 xp
Trigger reactions with observeEvent()
100 xp
Controlling action triggers
50 xp
Applying reactivity concepts
50 xp
Reactivity concepts: observe & reactive
100 xp
Convert height from inches to centimeters
100 xp
4
Build Shiny Apps
It’s time to build your own Shiny apps. You’ll make several apps from scratch, including one that allows you to gather insights from the Mental Health in Tech Survey and another that uses recipe ingredients as its input to accurately categorize different cuisines of the world. Along the way, you’ll also learn about more advanced input and output widgets, such as input validation, word clouds, and interactive maps.
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Build an Alien Sightings Dashboard
50 xp
Alien sightings: add inputs
100 xp
Alien sightings: add outputs
100 xp
Alien sightings: tab layout
100 xp
Exploring the 2014 Mental Health in Tech Survey
50 xp
The shinyWidgets gallery
50 xp
Explore the Mental Health in Tech 2014 Survey
100 xp
Validate that a user made a selection
100 xp
Explore cuisines
50 xp
Explore cuisines: top ingredients
100 xp
Explore cuisines: top ingredients redux
100 xp
Explore cuisines: wordclouds
100 xp
Mass shootings
50 xp
Mass shootings: add inputs
100 xp
Mass shootings: modify output
100 xp
Mass shootings: display help
100 xp
Wrap up video
50 xp

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Nas seguintes faixas

Fundamentos brilhantes com R

Ir para a trilha

Datasets

Recipes UFO Sightings Mental Health in Tech Survey Shootings

Collaborators

Anneleen Beckers

Maggie Matsui

Prerequisites

Introduction to the Tidyverse Intermediate R

kaelen medeiros

Data Scientist

Ramnath Vaidyanathan

VP of Product Research at DataCamp

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