Shiny 1.2

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Do curso por Johns Hopkins University

Developing Data Products

1400 classificações

Johns Hopkins University

Developing Data Products

1400 classificações

Curso 9 de 10 em Specialization Data Science

A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.

Na lição

Shiny, GoogleVis, and Plotly

Now we can turn to the first substantive lessons. In this module, you'll learn how to develop basic applications and interactive graphics in shiny, compose interactive HTML graphics with GoogleVis, and prepare data visualizations with Plotly.

Conheça os instrutores

Brian Caffo, PhD
Professor, Biostatistics
Bloomberg School of Public Health
Jeff Leek, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health

Okay, so let's go ahead and create our first app.

So you need a relatively recent version of RStudio or

I think you should have a relatively recent version of RStudio

just because of some things like the filing.

So I think probably the easiest way to start is Alt+F or File,

and then New File, and then Shiny Web App, okay?

So when you click that, it brings up a thing, name it whatever you want, so

you could name it myApp or something like that.

And then you can choose whether to have the files in a single file which we did

not talk about or in two files.

A ui.R and a server.R file, which we did talk, and we will talk about.

I'm going to recommend doing it this way, just because I always like to have,

I'd rather have many small files than one big file with lots of functions in it.

So I always tend to work that way, but also note that it's not

the files that it needs, it's not ui.R and server.R that it needs.

It's the specific named functions in the ur.R and

server.R files that it actually needs.

And you'll see those in a second.

I'm not going to create this because I've already done it.

So when it creates it, it creates the directory and

then it creates the two files.

You can see here's my ur.R and server.R.

No I took the Shiny pre-populated ui.R and

server.R files and then just pasted in the versions from the lecture notes, okay?

So the key thing in the ui.r is you need to have this ShinyUI function,

well you need to have library(shiny), but you need to have this ShinyUI function,

that's going to control the user interface, okay?

And then in the server.R you need something called shinyServer.

In this case our server is not going to do anything, okay?

Now let's look at the shinyUI function a little bit In a little bit more detail.

Let's put a little space right there.

Okay, so we have fluid page, which just describes the page

type that we're going to use to create our user interface.

So this is kind of a default and

I would just suggest that you use it until you learn a little bit more.

So titlePanel, you'll see where this comes up.

And it's going to say Data science FTW!.

So this is just going to set one of the GUI elements, and

in this case just a title.

And then by default in the fluidPage it's got a main panel and a side panel.

So here we're going to give it the sidebar layout.

Okay, so it's just saying what's going to occur in the sidebar.

So the sidebarPanel is going to tell us what's going to occur in the sidebar.

And h3, so h3 is going to give you the html third level index.

So if you've learned a little bit of html, just h3 is just going to

be smaller text than h2, which is just going to be smaller text than h1.

So it's the heading level.

So third level heading.

And it's just going to say slidebar Text and this is where the slidebar goes.

So and main panel is just going to be that center panel and

we're also going to do that in h3 and it's going to say main panel text, okay.

So sidebar layout is just going to say in my fluid page I'm going to have a sidebar

type layout with a part on the left that's going to give us navigation and things

like that and a main panel on the right, that's going to have the main content.

Okay, and so just keep track of these three phrases,

titlePanel("Data science FTW!), sidebar,

Sidebar Text Main panel, main panel text, and you'll see where it puts them all.

So, there's two ways to run it.

The easiest way, if you have a relatively recent version of RStudio,

you can just click run app.

And I want to save them.

I should have clicked always save before build.

And there you go, there you see your elements, Data science FTW!

In the title, this is in the sidebar and this is in the main panel, okay?

So those are our three elements in our fluid page with the sidebar layout.

Let me just show you the other way to run it.

We gotta switch to the directory where our ui.R and server.R are at.

So you can just do Alt + S + W + Return.

Okay, so that's Alt + S + W + Return, or click on Session,

click on Set Working Directory and click on To Source File Location, okay?

And then you just type runApp().

There you go.

Okay?

When you type in runApp, you can put in here the path to the app, okay?

So, if you'd rather do it that way, you can put in the path to the app, and

then you don't even have to be in the directory.

Notice it's running it in RStudio.

This is RStudio bringing up the HTML page.

Let me show you one other thing.

So here it is running, but if you look down here,

it says listening on and it gives a URL.

So basically what it's doing,

Shiny is just creating a little web server on your computer and

that web page is just RStudio's browser accessing that web server.

So when you run and debug things locally.

It's just going to create a little web server for you running locally.

And that RStudio is going to be able to access.

And at some point we want to push it up in to the Internet so that it's running

on a public web server so that anyone can access it, not just you on your computer.

But this would also show you how the lowest and kind of easiest form of

delivering a Shiny app to another RStudio user is to just give them the ur.R,

server.r functions and all the other functions that they need to run it.

Just give it to them and they can run it just like you can, but

that's not what we want in the long run.

We want it up and running on a webpage.

So we've done the first step and let's keep moving and

see if we can populate and make our app a little bit more useful.

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