08-leaflet-shiny.Rmd

# Interactive Maps with Shiny

## Learning Objectives

- Create a basic Shiny app using `leaflet`

## Topics Learned

- Shiny (UI vs. server)
- Interactivity

```{block type="rmdinfo"}
Find the Shiny cheatsheet in RStudio under Help > Cheatsheets > Web Applications with shiny
```

## Overview

This workshop teaches how to create a basic Shiny web app using leaflet.

## Interactive Tutorial

```{block type="rmdinfo"}
This workshop's Shiny app code can be found [here](https://github.com/spatialanalysis/workshop-scripts/blob/master/gis-visualization/winter-2019/R/leaflet-example/app.R).
```

```{block type="learncheck"}
**Challenge**
```
1. Create a new Shiny app from a template in R. Run the app. Which parts of the Shiny UI code map to the app? How are `ui` and `server` linked (what are the features that are the same across both?)

2. Change the title of the app.

```{block type="learncheck"}
```

```{block type="learncheck"}
**Challenge**
```
3. In the UI object, add a `leafletOutput("map")` call in the `mainPanel()` function. Then, in the server object, add a `output$map <- renderLeaflet({})` call.

That is, fill in the following script:
```{r eval=FALSE}
ui <- fluidPage(
   
   # Application title
   titlePanel("World Population Over Time"),
   
   # Sidebar with a slider input for number of bins 
   sidebarLayout(
      sidebarPanel(
         # sliderInput("bins",
         #             "Number of bins:",
         #             min = 1,
         #             max = 50,
         #             value = 30),

      ),
      
      # Specifies what to put in the main panel
      mainPanel(
         # Put one line of code here
      )
   )
)



server <- function(input, output) {
  
   # output$distPlot <- renderPlot({
   #    # generate bins based on input$bins from ui.R
   #    x    <- faithful[, 2] 
   #    bins <- seq(min(x), max(x), length.out = input$bins + 1)
   #    
   #    # draw the histogram with the specified number of bins
   #    hist(x, breaks = bins, col = 'darkgray', border = 'white')
   # })

    output$map <- renderLeaflet({
      # Put three lines of leaflet code here
      
      
      
    })

}

```

```{block type="learncheck"}
```

```{block type="learncheck"}
**Challenge**
```
4. In the UI object, add a `sliderInput` of `"year"`. Change the step size to 5, and remove the comma for thousands (hint: do `?sliderInput` to look at the documentation, and options).
    
```{block type="learncheck"}
```

```{block type="learncheck"}
**Challenge**
```
5. Create a new variable called `pop_per_year` that is a subset of city by year, depending on which year you enter (`input$year`). Use the `filter()` command in the `dplyr` package.
    
```{block type="learncheck"}
```


```{block type="learncheck"}
**Challenge**
```
6. Try resizing the marker size depending on population, adding a popup, or doing more to customize your map!

7. Try adding a feature in your app so that you only show cities over a certain population in millions (specified by the user), using `numericInput()` instead of `sliderInput()`.
    
```{block type="learncheck"}
```


```{block type="learncheck"}
**Challenge**
```
8. Add a data table element with `renderDataTable()` and `dataTableOutput()` so you can see the attributes of the points in the map.

```{block type="learncheck"}
```

```{block type="rmdinfo"}
You can share your Shiny apps publicly by creating an account at https://shinyapps.io and clicking Publish in the top of your app script.
```

## R Training Workshop

I will be teaching a day-long "R for Social Scientists" Data Carpentry workshop on April 12 at the Center for Spatial Data Science. 

Topics to be covered include:

- Introduction to R
- Working with data types, strings, and dates in R
- Manipulating data frames in R
- Data visualization in R

...and lunch will be provided!

Please register at [this link](https://www.eventbrite.com/e/r-for-social-scientists-data-carpentry-workshop-tickets-57131487818) if you are interested! 

## Links 

- Leaflet documentation website: https://rstudio.github.io/leaflet/
- Intro to Shiny webinar (45 minutes): https://www.rstudio.com/resources/webinars/introduction-to-shiny/
- Free Shiny online course from Datacamp: https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny
- Shiny examples:
  + Generate random points on a map: https://bhaskarvk.github.io/user2017.geodataviz/presentations/07-Interactive_Maps.html#36
  + Zip code explorer: http://shiny.rstudio.com/gallery/superzip-example.html
  + Twin cities bus dashboard: https://gallery.shinyapps.io/086-bus-dashboard/