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$set(echo = T)
knitr::opts_chunk$set(warning = F)
knitr::opts_chunk$set(message = F)
library(pacman)
pacman::p_load(plotly, gapminder)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

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.

data <- gapminder


gdp_summary <- gapminder %>%
  group_by(continent) %>%
  summarise(
    average_gdpPercap = mean(gdpPercap, na.rm = TRUE),
    max_gdpPercap = max(gdpPercap, na.rm = TRUE)
  )
gdp_summary
## # A tibble: 5 × 3
##   continent average_gdpPercap max_gdpPercap
##   <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"))

static_plot <- plot_ly(
  data = gapminder,
  x = ~gdpPercap,
  y = ~lifeExp,
  size = ~pop,
  color = ~continent,
  type = 'scatter',
  mode = 'markers',
  marker = list(sizemode = "diameter")) %>%
  layout(
    title = "Gapminder Bubble Chart",
    xaxis = list(title = "GDP per Capita"),
    yaxis = list(title = "Life Expectancy"),
    showlegend = TRUE
  )

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 variable that should determine the frame.

animated_plot <- plot_ly(
  data = gapminder,
  x = ~gdpPercap,
  y = ~lifeExp,
  size = ~pop,
  color = ~continent,
  frame = ~year, 
  type = 'scatter',
  mode = 'markers',
  marker = list(sizemode = "diameter")
) %>%
  layout(
    title = "Gapminder Animated Bubble Chart",
    xaxis = list(title = "GDP per Capita"),
    yaxis = list(title = "Life Expectancy"),
    showlegend = TRUE
  )
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,  #Duration of each frame in milliseconds
                 redraw = TRUE, # Force redraw for a smoother animation
                 easing = "linear") #Animation easing type for consistent speed
                # autoplay = TRUE) #Should start animation 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 <- 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 %>%
  plotly::style(
    hoverinfo = "text",
    text = ~paste(
      "Country:", gapminder$country,
      "<br>Continent:", gapminder$continent,
      "<br>GDP per Capita:", round(gapminder$gdpPercap, 2),
      "<br>Life Expectancy:", round(gapminder$lifeExp, 1),
      "<br>Population:", gapminder$pop
    )
  )
final_plot

Q7

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