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, warning=FALSE)
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, unionlibrary(ggplot2)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.
gapminder<-gapminder
gapminder_summary<-gapminder%>%
group_by(continent)%>%
summarise(
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.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(data=gapminder,
x=~gdpPercap,
y=~lifeExp,
size=~pop,
marker =list(sizemode="diameter"),
color=~continent)
static_plot## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-modeNote 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.
# Code goes here
animated_plot<- plot_ly(data=gapminder,
x=~gdpPercap,
y=~lifeExp,
size=~pop,
marker =list(sizemode="diameter"),
color=~continent,
frame=~year)
animated_plot## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-modeTry 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)
animated_chart## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-modeChanging the frame makes the bubbles move faster. Redraw=TRUE makes it so bubbles that cannot move on their own are redrawn at every frame. Easing=“linear” makes the bubbles move at a constant speed. We tried to use autoplay but it did not work.
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 = -0.4,
buttons = list(
list(
label = "Pause",
method = "animate",
args = list(NULL, list(frame = list(duration = 0,
redraw = TRUE),
mode = "immediate"))
)
)
)
)
)
interactive_chart## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-modeWe moved the button below the play button because it makes more sense there.
Add a title, axis labels, any other important annotations to the plot. This could include adding hover text or other elements.
interactive_chart_2<- interactive_chart%>%
layout(title= "Life Expectancy vs GDP Per Capita by Region Over Time",
xaxis= list(title="GDP Per Capita"),
yaxis= list(title="Life Expectancy"))
interactive_chart_2## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-modePractice publishing your final plot to Rpubs (or another location of your choice) and include the link in your submission.