To pass specifications, you need to complete all questions, especially the final couple questions. You should have a functional animation with a working “play” button and some customized options. The animated line document on Canvas may be useful as another reference for animations using Plotly in R.

Note the use of the p_load() function from the pacman package!

library(pacman)
knitr::opts_chunk$set(echo = TRUE)
pacman::p_load(plotly, gapminder)

Q1

Load the gapminder dataset into your R environment and take a look at it. Note the location of different variables and include a summary of the average and maximum GDP by continent.

gapminder %>%
  group_by(continent) %>%
  summarise(
    avg_gdp = mean(gdpPercap, na.rm = TRUE),
    max_gdp = max(gdpPercap, na.rm = TRUE)
  )
## # A tibble: 5 × 3
##   continent avg_gdp max_gdp
##   <fct>       <dbl>   <dbl>
## 1 Africa      2194.  21951.
## 2 Americas    7136.  42952.
## 3 Asia        7902. 113523.
## 4 Europe     14469.  49357.
## 5 Oceania    18622.  34435.

Q2

Using plotly, create a static bubble chart of the gapminder data. Map GDP to the x axis, life expectancy to the Y axis, and population to the size of the bubbles. Each bubble’s color should be based on the region of that nation. Hint: If size is not working properly for you, you may want to use: marker = list(sizemode = "diameter"))

#Uncomment and modify the line below this one to create your plot!
static_plot <- plot_ly(data = gapminder, 
        x = ~gdpPercap, 
        y = ~lifeExp,
        size = ~pop,
        color = ~continent, 
        marker = list(sizemode = "diameter"))

static_plot
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode

Note here that the plot looks pretty messy because all the years are present on the plot. It would be nice to see the dots by country one year at a time, right?

Q3

Create a new plotly object that is similar to the previous one, but includes animation. This is as easy as adding frame to your plot_ly command and specifying the variable that should determine the frame.

# Code goes here

#Uncomment the line below and modify as needed!
animated_plot <- plot_ly(data = gapminder, 
        x = ~gdpPercap, 
        y = ~lifeExp,
        size = ~pop,
        color = ~continent, 
        marker = list(sizemode = "diameter"),
        frame = ~year)

animated_plot
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode

Q4

Try adding a few options to alter your animation lightly. As long as you’ve created your plot correctly, all you need to do here is uncomment the code, run the chunk, and explain what each part did.

#Uncomment the lines below to see the updated animation. 
animated_chart <- animated_plot %>% 
  animation_opts(frame = 100,  #Speeds up auto-play of the graph
                 redraw = TRUE, #Redraws entire plot elements
                 easing = "linear",) #Constant speed when playing
animated_chart
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode
#autoplay is not working but typically it would allow the animation to play when running code

Q5

Now, let’s add a button to pause the animation. You should spend a bit of time looking at this code and understanding what it does, then try to move the button to a place that makes more sense.

 interactive_chart <- animated_chart %>% layout(
   updatemenus = list(
     list(
       type = "buttons",
       showactive = FALSE,
       x = 0,  
       y = -.5,  
       buttons = list(
         
         list(
           label = "Pause",
           method = "animate",
           args = list(NULL, list(frame = list(duration = 0, 
                                               redraw = TRUE), 
                                  mode = "immediate"))
         )
       )
     )
   )
 )
 interactive_chart
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode

Q6

Add a title, axis labels, any other important annotations to the plot. This could include adding hover text or other elements.

annotated_chart = interactive_chart %>% 
add_trace(
    hoverinfo = 'text',  # Show custom text when hovering
    text = ~paste("Country: ", country, 
                  "<br>GDP per Capita: $", gdpPercap, 
                  "<br>Life Expectancy: ", lifeExp, 
                  "<br>Population: ", pop)
  ) %>%
  layout(
    title = 'GDP vs Life Expectancy by Continent over Time',
    xaxis = list(title = 'GDP per Capita'),
    yaxis = list(title = 'Life Expectancy'),
    showlegend = TRUE
  )

annotated_chart
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No scatter mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode

Q7

Practice publishing your final plot to Rpubs (or another location of your choice) and include the link in your submission.