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)
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.

# Load gapminder data and packages
pacman::p_load(plotly, gapminder, dplyr)

# Summarize GDP by continent
gapminder_summary <- gapminder %>%
  group_by(continent) %>%
  summarize(avg_gdp = mean(gdpPercap, na.rm = TRUE), max_gdp = max(gdpPercap, na.rm = TRUE))
gapminder_summary
## # 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"))

# Static bubble chart
static_plot <- plot_ly(gapminder, 
                       x = ~gdpPercap, 
                       y = ~lifeExp, 
                       size = ~pop, 
                       color = ~continent, 
                       type = 'scatter', 
                       mode = 'markers',
                       marker = list(sizemode = "diameter"))
static_plot
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#Uncomment and modify the line below this one to create your plot!
#static_plot <- plot_ly(...)

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
# Animated bubble chart
animated_plot <- plot_ly(gapminder, 
                         x = ~gdpPercap, 
                         y = ~lifeExp, 
                         size = ~pop, 
                         color = ~continent, 
                         frame = ~year,
                         type = 'scatter', 
                         mode = 'markers',
                         marker = list(sizemode = "diameter"))
animated_plot
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#Uncomment the line below and modify as needed!
#animated_plot <- plot_ly(...)

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,  #What did this do?
#                 redraw = TRUE, # What did this do?
#                 easing = "linear", #What did this do?
#                 autoplay = TRUE #What did this do)
#animated_chart
# Add animation options
# Adjusted animation options without autoplay argument
animated_chart <- animated_plot %>% 
  animation_opts(
    frame = 100,       # Controls frame transition speed
    redraw = TRUE,     # Ensures each frame is redrawn
    easing = "linear"  # Smoothens transition
  )
animated_chart
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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 = 0,  
#       buttons = list(
#         
#         list(
#           label = "Pause",
#           method = "animate",
#           args = list(NULL, list(frame = list(duration = 0, 
#                                               redraw = TRUE), 
#                                  mode = "immediate"))
#         )
#       )
#     )
#   )
# )
# interactive_chart
# Add pause button to control animation
interactive_chart <- animated_chart %>% layout(
  updatemenus = list(
    list(
      type = "buttons",
      showactive = FALSE,
      x = 0.1,  
      y = 0.1,  
      buttons = list(
        list(
          label = "Pause",
          method = "animate",
          args = list(NULL, list(frame = list(duration = 0, redraw = TRUE), mode = "immediate"))
        )
      )
    )
  )
)
interactive_chart
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Q6

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

# Add title, axis labels, and hover info
final_chart <- interactive_chart %>%
  layout(
    title = "Animated Bubble Chart of GDP and Life Expectancy by Continent",
    xaxis = list(title = "GDP per Capita"),
    yaxis = list(title = "Life Expectancy"),
    hovermode = "closest"
  )
final_chart
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Q7

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