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)
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## check out the dataset
data <- gapminder
head(gapminder, 5)## # A tibble: 5 × 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.## calculate the summary of the average and max GDP by continent
gdp_summary_by_country <- gapminder %>%
group_by(continent) %>%
summarise(
avg_gdp = mean(gdpPercap, na.rm = TRUE),
max_gdp = max(gdpPercap, na.rm = TRUE)
)
gdp_summary_by_country## # 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"))
#Uncomment and modify the line below this one to create your plot!
colnames(gapminder)## [1] "country" "continent" "year" "lifeExp" "pop" "gdpPercap"static_plot <- plot_ly(
data = gapminder,
x = ~gdpPercap,
y = ~lifeExp,
size = ~pop,
color = ~continent,
type = "scatter",
mode = "markers",
marker = list(sizemode = "diameter")
) %>%
layout(
xaxis = list(title = "GDP per Capita"),
yaxis = list(title = "Life Expectancy"),
title = "GDP, Life Expectancy, and Population by Continent"
)
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?
It’s painful to move it (my computer lags haha).
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(
data = gapminder,
x = ~gdpPercap,
y = ~lifeExp,
size = ~pop,
color = ~continent,
type = "scatter",
mode = "markers",
marker = list(sizemode = "diameter"),
frame = ~year ## animate by year
) %>%
layout(
xaxis = list(title = "GDP per Capita"),
yaxis = list(title = "Life Expectancy"),
title = "GDP, Life Expectancy, and Population by Continent"
)
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.
#Uncomment the lines below to see the updated animation.
animated_chart <- animated_plot %>%
animation_opts(frame = 100, ## divides the animation into 100 frames
redraw = TRUE, ## redraws the entire plot
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 = 1.15,
y = -0.25,
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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gapminder$pop <- as.numeric(gapminder$pop)
animated_chart <- plot_ly(
data = gapminder,
x = ~gdpPercap,
y = ~lifeExp,
size = ~pop,
color = ~continent,
type = "scatter",
mode = "markers",
marker = list(sizemode = "diameter"),
frame = ~year,
hoverinfo = "text", # Add hover text
text = ~paste("Country:", country,
"<br>Year:", year,
"<br>GDP Per Capita:", gdpPercap,
"<br>Population:", pop), # Customize hover text
legendgroup = ~continent
) %>%
layout(
xaxis = list(title = "GDP per Capita"),
yaxis = list(title = "Life Expectancy"),
title = "Global Development Over Time",
legend = list(title = list(text = "Continent"))
) %>%
animation_opts(
frame = 100,
transition = 0,
redraw = FALSE
)
interactive_chart## Warning: `line.width` does not currently support multiple values.
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## Warning: `line.width` does not currently support multiple values.I added a title called ‘Global Development Over Time’ to reflect the various variables that are being tracked throughout the visualization. First, we labaled the specific points by adding hover text that provides descriptions for the Country, Year, Gdp Per Capita, and Population. In addition, the x-axis has been labeled to reflect GDP per Capita and the Y-axis to reflect Life Expectancy. Then the actual legend label is now continent to reflect the color organization of the points.
Practice publishing your final plot to Rpubs (or another location of your choice) and include the link in your submission.