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!

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(warning = FALSE)
knitr::opts_chunk$set(message = FALSE)
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.

library(tidyverse)
library(gapminder)
gapminder = gapminder
gapminder %>%
  group_by(continent) %>%
  summarize(avg_GDP = mean(gdpPercap),
            max_GDP = max(gdpPercap))
## # 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(gapminder,x=~gdpPercap,y=~lifeExp,size=~pop,
                       color=~continent, 
                       type = 'scatter', mode="markers",
                       marker = list(sizemode = "diameter")) %>%
  layout(title = "Life Expectancy vs. GDP per Capita",
         xaxis = list(title = "GDP per Capita"),
         yaxis = list(title = "Life Expectancy"))
static_plot

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 varable that should determine the frame.

# Code goes here

#Uncomment the line below and modify as needed!
animated_plot <- plot_ly(gapminder,x=~gdpPercap,y=~lifeExp,size=~pop,
                       color=~continent, frame = ~year,
                       type = 'scatter', mode = "markers",
                       marker = list(sizemode = "diameter")) %>%
  layout(title = "Life Expectancy vs. GDP per Capita",
         xaxis = list(title = "GDP per Capita"),
         yaxis = list(title = "Life Expectancy"))
animated_plot

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,  # this changes the speed of the animation
                 redraw = TRUE, # every frame redraws the plot 
                 easing = "linear") # this changes how the animations 
                                    # moves between years (less smooth than default)
                 #autoplay = TRUE ) this would make it play automatically
animated_chart

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 = -0.02,  
     y = -0.285,  
     buttons = list(
       
       list(
         label = "Pause",
         method = "animate",
         args = list(NULL, list(frame = list(duration = 0, 
                                             redraw = TRUE), 
                                mode = "immediate"))
       )
     )
   )
 )
)
interactive_chart

Q6

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

final_plot = plot_ly(gapminder,x=~gdpPercap,y=~lifeExp,size=~pop, text=~country,
                       color=~continent, frame = ~year, hoverinfo="text",
                       type = 'scatter', mode = "markers",
                     marker = list(sizemode = "diameter")) %>%
  layout(title = "Life Expectancy vs. GDP per Capita by Year",
         xaxis = list(title = "GDP per Capita"),
         yaxis = list(title = "Life Expectancy")) %>% 
  animation_opts(frame = 100, 
                 redraw = TRUE, 
                 easing = "linear") %>% layout(
 updatemenus = list(
   list(
     type = "buttons",
     showactive = FALSE,
     x = -0.02,  
     y = -0.285,  
     buttons = list(
       
       list(
         label = "Pause",
         method = "animate",
         args = list(NULL, list(frame = list(duration = 0, 
                                             redraw = TRUE), 
                                mode = "immediate"))
       )
     )
   )
 )
)

final_plot

Q7

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