In jr-packages/jrShiny: R Shiny Exercises

```r setnicepar = function(mar=c(3,3,2,1), mgp=c(2,0.4,0), tck=-.01, cex.axis=0.9, las=1, mfrow=c(1,1),...) { par(mar=mar, mgp=mgp, tck=tck, cex.axis=cex.axis, las=las,mfrow=mfrow,...) }

```r
library(shiny)
library(flexdashboard)
#library(jrShiny)
library("ggplot2movies")
library(ggplot2)
library(flexdashboard)
data(movies, package="ggplot2movies")
movies = movies[!is.na(movies$budget) & movies$budget > 0,]
top_movies = movies[order(-movies$rating), c("title", "year", "budget", "rating", "Romance", "Action", "Animation"), ]
colnames(top_movies)  = c("Title", "Year", "Budget", "Rating","Romance", "Action", "Animation")
theme_set(theme_bw())


t_m = reactive(top_movies[top_movies[input$movie_type]==1,])
years = reactive(movies[movies$year > 1929 & movies[input$movie_type]==1,])
an = reactive(movies[movies[input$movie_type]==1,])

Selections {.sidebar}

Select the movie genre to display

selectInput("movie_type", label = "Movie genre", c("Romance", "Action", "Animation"))
selectInput("mpaa", label = "MPAA", c("R", "PG-13", "PG", "NC-17"))
actionButton("replot", "Plot")

Note I've used a global side-bar here.

Tables

Column {.tabset .tabset-fade}

Top 10 movies (static)

renderTable({
t_m_isolate = isolate(t_m())
input$replot
t_m_isolate[1:10, 1:4]
})

Top 10 movies (dynamic)

DT::renderDataTable({
t_m_isolate = isolate(t_m())
input$replot
DT::datatable(t_m_isolate[,1:4], rownames = FALSE)})

Base graphics

Rating vs Length

renderPlot({
setnicepar()
plot(an()$rating, an()$length, ylab="Length", xlab="Rating", 
pch=21, bg="steelblue", ylim=c(0, max(an()$length)), 
xlim=c(1, 10), main=paste0(input$movie_type, " movies"))
grid()
})

Movie Length

renderPlot({
setnicepar()
hist(an()$length, breaks="fd", col="steelblue", xlab="Movie Length", 
main="Histogram of movie length", xlim=c(0, max(an()$length)))
grid()
})

htmlwidget and value boxes

Column 1 {data-width=200}

Length vs rating

This example makes use of the plotly and ggplot2. There is also a valuebox showing the number of terrible movies.

library(plotly)
renderPlotly({
g = ggplot(an(), aes(length, rating)) + 
geom_point(size=0.5, aes(text=paste("Film: ", title))) + 
xlab("Length") + ylab("Rating") + 
ylim(c(0, 10)) 
ggplotly(g)
})

Value boxes

renderValueBox({
valueBox(sum(an()$rating <3), icon = "ion-videocamera", caption="Movies Rated less than 3", 
color="red")
})

Column 2 {data-width=300}

Movie ratings over number

This example makes use of the dygraphs R package. The dygraphs package provides rich facilities for charting time-series data in R.

library(dygraphs)
renderDygraph({
rat_by_year = tapply(years()$rating, years()$year, mean)
x = ts(as.vector(rat_by_year), start=1930)
y = cbind(Rating=x)
dygraph(y, main = "Ratings over the years", 
ylab = "Ratings", group="Ratings") %>% 
dyRangeSelector() %>%
dyOptions(stepPlot = TRUE) %>%
dySeries("V1", label = "Rating")
})

Number of movies made

library(dygraphs)
renderDygraph({
num_by_year = tapply(years()$rating, years()$year, sum)
x = ts(as.vector(num_by_year), start=1930)
y = cbind(Rating=x)
dygraph(y, main = "Number of movies over the years", 
ylab = "No. of movies",group="Ratings") %>% 
dyRangeSelector() %>%
dyOptions(stepPlot = TRUE) %>%
dySeries("V1", label = "No. of Movies made")
})

jr-packages/jrShiny documentation built on Feb. 16, 2020, 9:13 p.m.