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.

data("gapminder")
head(gapminder)
## # A tibble: 6 × 6
##   country     continent  year lifeExp      pop gdpPercap
##   <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan Asia       1952    28.8  8425333      779.
## 2 Afghanistan Asia       1957    30.3  9240934      821.
## 3 Afghanistan Asia       1962    32.0 10267083      853.
## 4 Afghanistan Asia       1967    34.0 11537966      836.
## 5 Afghanistan Asia       1972    36.1 13079460      740.
## 6 Afghanistan Asia       1977    38.4 14880372      786.
gdp_summary <- gapminder %>%
  group_by(continent) %>%
  summarise(avg_gdp = mean(gdpPercap, na.rm = TRUE), max_gdp = max(gdpPercap, na.rm = TRUE))

gdp_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"))

#Uncomment and modify the line below this one to create your plot!
#static_plot <- plot_ly(...)
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)
## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

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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(...)
animated_plot <- plot_ly(data = gapminder, 
                         x = ~gdpPercap, 
                         y = ~lifeExp, 
                         size = ~pop, 
                         color = ~continent, 
                         frame = ~year,       
                         type = 'scatter', 
                         mode = 'markers',
                         marker = list(sizemode = "diameter", opacity = 0.7)) %>%
  layout(title = "Gapminder Animated Bubble Chart",
         xaxis = list(title = "GDP per Capita"),
         yaxis = list(title = "Life Expectancy"),
         showlegend = TRUE)
animated_plot
## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

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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 controls the duration of each frame in milliseconds. A higher value slows down the animation and a lower value speeds it up. setting it to 100 ms makes each frame play for a tenth of a second.
    redraw = TRUE,      # This option ensures that each frame is redrawn. This can be useful for improving the smoothness of the animation if changes are being made dynamically.
    easing = "linear",  # The easing parameter controls the transition style between frames. Linear creates a consistent animation speed without acceleration or deceleration.
    ) %>%
  layout(
    updatemenus = list(
      list(type = "buttons",
           showactive = FALSE,
           buttons = list(
             list(label = "Play",
                  method = "animate",
                  args = list(NULL, list(frame = list(duration = 100), fromcurrent = TRUE)))
           )
      )
    )
  )
 # Setting the autoplay to TRUE automatically starts the animation without requiring the user to press Play but it kept giving me errors so I made some edits. (would not let me use that function).
animated_chart
## Warning: `line.width` does not currently support multiple values.

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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 = 0.1,
      y = 0.8,
    buttons = list(
      
      list(
        label="Play",
        method = "animate",
        args = list(NULL, list(frame = list(duration = 100, redraw = TRUE), mode="immediate"))),
      
       
      list(
        label = "Pause",
          method = "animate",
        args = list(NULL, list(frame = list(duration = 0, 
                                            redraw = TRUE), 
                                mode = "immediate"))
      )
    )
   )
 )
 )
 interactive_chart
## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

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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.

interactive_chart <- animated_chart %>%
  layout(
    title = "Gapminder Animated Bubble Chart: GDP vs Life Expectancy",
    xaxis = list(
      title = "GDP per Capita",
      tickformat = ",d"
    ),
    yaxis = list(
      title = "Life Expectancy (years)"
    ),
    updatemenus = list(
      list(
        type = "buttons",
        showactive = FALSE,
        x = 0.1,
        y = 0.8,
        buttons = list(
          list(
            label = "Play",
            method = "animate",
            args = list(NULL, list(frame = list(duration = 100, redraw = TRUE), mode = "immediate"))
          ),
          list(
            label = "Pause",
            method = "animate",
            args = list(NULL, list(frame = list(duration = 0, redraw = TRUE), mode = "immediate"))
          )
        )
      )
    )
  ) %>%
  add_annotations(
    text = "Year:",
    x = 0.1,
    y = 1.1,
    xref = "paper",
    yref = "paper",
    showarrow = FALSE,
    font = list(size = 12)
  ) %>%
  style(
    hoverinfo = "text",
    text = ~paste("Country:", country, "<br>GDP per Capita:", gdpPercap, "<br>Life Expectancy:", lifeExp, "<br>Population:", pop)
  )
## Warning: `line.width` does not currently support multiple values.

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## Warning: `line.width` does not currently support multiple values.

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interactive_chart

Q7

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