gganimate: A Lesson with Avocados

transition_reveal()

This type of transition is the simplest and acts like a piece of paper is being removed from left to right over the top of the graph to slowly reveal the result. That’s how I think about it, at least. This assume that your x axis is also what is included inside your statement transition_reveal().

For this, let’s first build a static line plot that has date on the x-axis. Looking through the data, we could use AveragePrice or Total Volume on the y axis, and we could disaggregate by region, size of avocado, or type (organic versus conventional).

Let’s stick to the totalUS aggregation dataset we made (avocado_us) and look at the average price of conventional and organic avocados over time.

ggplot(data = avocado_us, 
       mapping = aes(x = Date, y = AveragePrice, color = type)) +
  geom_line()

If we feel good on time, we can make a few adjustments to the plot before animating it.

ggplot(data = avocado_us, 
       mapping = aes(x = Date, y = AveragePrice, color = type)) +
  geom_line() +
  scale_y_continuous(labels = scales::dollar_format()) +  # format that y axis! 
  scale_color_manual(values= c("darkgreen", "darkolivegreen3")) +
  theme_minimal() +
  labs(title = "Average Price of US Avocados",
       caption = "Source: Kaggle")

This looks a lot better. I one what happened the summer of 2015! Now let’s animate this. The key to this animation is transition_reveal(). Inside of the function, we can write out x axis variable. While it will take a few moments to render, you should see an animated plot in your plots pane.

ggplot(data = avocado_us, 
       mapping = aes(x = Date, y = AveragePrice, color = type)) +
  geom_line() +
  scale_y_continuous(labels = scales::dollar_format()) +  # format that y axis! 
  scale_color_manual(values= c("darkgreen", "darkolivegreen3")) +
  theme_minimal() +
  labs(title = "Average Price of US Avocados",
       caption = "Source: Kaggle") +
  transition_reveal(Date)

Let’s also save this, since each time we run the code it takes some time.

anim_save(filename = "type_reveal.gif")

transition_time()

Transition time creates new “layers” of the animation over a continous variable, usually time (i’ve never seen an exception to that). While this works best with geom_point, there’s many other options you can play around with.

Let’s use two continous variables to plot this. Let’s see how well price explains the volume sold of avocados for non-organic avocados (though, it’s been awhile since I took Econ101). Let’s do this for the different cities in the US, omitting states and regions.

avocado_cities_filtered <- avocado_cities %>% 
  filter(type == "conventional",
         Date > as.Date("2018-01-01"))
ggplot(data = avocado_cities_filtered,
       mapping = aes(x = AveragePrice, y = `Total Volume`, color = region)) +
  geom_point()

That legend is really going to get in the way. Let’s remove it and customize the circles before animating.

ggplot(data = avocado_cities_filtered,
       mapping = aes(x = AveragePrice, y = `Total Volume`, color = region)) +
  scale_y_continuous(labels = scales::comma_format()) +
  scale_x_continuous(labels = scales::dollar_format()) +
  geom_point(aes(size = `Total Volume`), alpha = .6) +  
  theme_minimal() +
  theme(legend.position = "none") +
  labs(title = "Avocados sold by price and city") 

In practice, the animation is basically layering a bunch of plots on top of each other, as if they were facet_wraps. When I’m planning out an animation, I often use facet_wrap like you learned this morning to see the different layers before I “assemble” them.

ggplot(data = avocado_cities_filtered,
       mapping = aes(x = AveragePrice, y = `Total Volume`, color = region)) +
  scale_y_continuous(labels = scales::comma_format()) +
  scale_x_continuous(labels = scales::dollar_format()) +
  geom_point(aes(size = `Total Volume`), alpha = .6) +  
  theme_minimal() +
  theme(legend.position = "none") +
  labs(title = "Avocados sold by price and city") +
  facet_wrap(~Date)

Now we can move on to animating this. transition_time() will replace the previous dot, making it hard to see any trends. Let’s add shadow_wake so we can see the direction between points.

One really cool trick I like to employ is writing in the subtitle what point in time we’re currently animating. Before it didn’t really matter because the date was on the x axis, but not its hidden. For that, we need to add some {} in the subtitle argument of labs.

ggplot(data = avocado_cities_filtered,
       mapping = aes(x = AveragePrice, y = `Total Volume`, color = region)) +
  scale_y_continuous(labels = scales::comma_format()) +
  scale_x_continuous(labels = scales::dollar_format()) +
  geom_point(aes(size = `Total Volume`), alpha = .6) +  
  theme_minimal() +
  theme(legend.position = "none") +
  labs(title = "Avocados sold by price and city",
       subtitle = "Date: {frame_time}") +
  transition_time(Date) +
  shadow_wake(wake_length = 0.2)    

Let’s also save this, since each time we run the code it takes some time.

anim_save(filename = "type_time.gif")

transition_state()

Transition_state() creates a new animation layer across a categorical variable instead of over time.

avocado_region_long <- avocado_region %>% 
  pivot_longer(cols = c(`4046`,`4225`,`4770`),
               names_to = "size",
               values_to = "volume")
ggplot(data = avocado_region_long,
       mapping = aes(x = size, y = volume, color = size)) +
  geom_boxplot() 

Let’s customize this a little to make it look nicer.

ggplot(data = avocado_region_long,
       mapping = aes(x = size, y = volume, color = size)) +
  geom_boxplot() +
  theme_classic() +
  scale_y_continuous(labels = scales::comma_format()) +
  labs(title = "Boxplot of volume sold by Avocado Size")

It isn’t particularly helpful that the previous view completely dissappears as in transition_time. Instead of using shadow_wake(), let’s use shadow_mark() to the animated plot to keep the past views visible.

ggplot(data = avocado_region_long,
       mapping = aes(x = size, y = volume, color = size)) +
  geom_boxplot() +
  theme_classic() +
  scale_y_continuous(labels = scales::comma_format()) +
  labs(title = "Boxplot of volume sold by Avocado Size") +
  transition_states(size, state_length = 1, transition_length = 1) +
  shadow_mark(alpha = 0.3, size = 0.5)    

Let’s also save this, since each time we run the code it takes some time.

anim_save(filename = "type_state.gif")

ggplot(data = filter(avocado_region, type == "organic"), 
       aes(x = Date, y = `Total Volume`, color = region)) +
  geom_line() +
  theme_minimal() +
  labs(title = "Average Price of US Avocados",
       caption = "Source: Kaggle",
       subtitle = "Date: {frame_along}") +
  transition_reveal(Date)
anim_save("challenge_1.gif")

ggplot(data = filter(avocado_CA, type == "organic"),
       mapping = aes(x = Date, y = AveragePrice)) +
  scale_y_continuous(labels = scales::dollar_format()) +
  geom_point(alpha = .6) +  
  theme_minimal() +
  theme(legend.position = "none") +
  labs(title = "The fluctuating price of organic avocados in California",
       subtitle = "Date: {frame_time}") +
  transition_time(Date) +
  shadow_wake(wake_length = 0.2)    
anim_save("challenge_2.gif")