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)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(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.continent_summary <- gapminder %>%
group_by(continent) %>%
summarise(
avg_gdp = mean(gdpPercap),
max_gdp = max(gdpPercap)
)
print(continent_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.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")
)
static_plot## Warning: `line.width` does not currently support multiple values.
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## Warning: `line.width` does not currently support multiple values.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?
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.
animated_plot <- plot_ly(
data = gapminder,
x = ~gdpPercap,
y = ~lifeExp,
size = ~pop,
color = ~continent,
frame = ~year,
type = 'scatter',
mode = 'markers',
marker = list(sizemode = "diameter")
)
animated_plot## Warning: `line.width` does not currently support multiple values.
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## Warning: `line.width` does not currently support multiple values.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.
Setting frame equal to 100 means that each frame will last for 100 milliseconds. Setting redraw equal to true tells the plot to redraw with each frame. Setting easing to linear provides a steady, constant rate of change between frames. Setting this to something like lastic would reuslt in dynamic animations during frame changes. Setting autoplay to true starts the plot on its own.
animated_chart <- animated_plot %>%
animation_opts(frame = 100,
redraw = TRUE,
easing = "linear")
animated_chart## Warning: `line.width` does not currently support multiple values.
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## Warning: `line.width` does not currently support multiple values.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,
xanchor = "left",
yanchor = "bottom",
buttons = list(
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.
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## Warning: `line.width` does not currently support multiple values.Add a title, axis labels, any other important annotations to the plot. This could include adding hover text or other elements.
interactive_chart <- interactive_chart %>%
layout(
title = "GDP vs Life Expectancy Over Time",
xaxis = list(title = "GDP per Capita"),
yaxis = list(title = "Life Expectancy"),
updatemenus = list(
list(
type = "buttons",
showactive = FALSE,
x = 0,
y = 0,
xanchor = "left",
yanchor = "bottom",
buttons = list(
list(
label = "Pause",
method = "animate",
args = list(NULL, list(
frame = list(duration = 0, redraw = TRUE),
mode = "immediate"
))
)
)
)
)
) %>%
style(
text = ~paste(
"Country:", country,
"<br>GDP per Capita:", round(gdpPercap, 2),
"<br>Life Expectancy:", round(lifeExp, 1),
"<br>Population:", round(pop)
),
hoverinfo = "text"
)## Warning: `line.width` does not currently support multiple values.
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