Maps

In this practical, you will in different ways animate a plot showing the link between wealth and income in Basel in the year 2017.

0 - Preliminaries

1. If you haven’t done so already, load the tidyverse and the taxation.csv data.

library(tidyverse)
basel <- read_csv('1_data/taxation.csv')

2. Load the gganimate and plotly packages.

library(gganimate)

1 - Base plot

1. Use the code below to generate the base plot for this practical. It shows the relationship between wealth and income for every year, with points colored according to the wealth in 2017.

plot <- basel %>% 
  arrange(year, desc(wealth_mean)) %>% 
  mutate(quarter = as_factor(quarter)) %>% 
  ggplot(aes(x = wealth_mean, 
             y = income_mean, 
             col = quarter)) +
  geom_point(show.legend = F, 
             size=4) + 
  labs(x = "Wealth", 
       y = "Income") +
  theme_minimal() +
  scale_color_viridis_d() 

2 - Animate

1. To animate the base plot, that is, to show the data for each year in an iterative fashion, simply add transition_states(year) to the plot. This will start a process during which first all individual images are created and then the images are joined in a single .gif file, which will be displayed in the Plots tab. Know that this may take a few seconds to a minute.

plot + 
  XX

2. Add ggtitle(label = "XX", subtitle = "XX") to add a title and subtitle to the plot. In either title or subtitle, add {closest_state} directly inside the character string, so that the changing states will be shown.

plot + 
  XX +
  XX

3. Change the speed and focus of the animation by setting transition_length = 10 and state_length = 0. As a result, you should get a smoother, more fluid animation.

plot + 
  XX(XX, XX) +
  XX

4. Add shadow_wake() to add wakes to your animation.

plot + 
  XX(XX, XX) +
  XX +
  XX

5. Use anim_save(), to save your animation as a .gif to your harddrive. To do this, first store the animation in an object. Make sure to add the extension .gif to your filename. If you don’t specify a folder, you should find your animation inside of your project folder.

anim <- plot + 
          XX(XX, XX) +
          XX +
          XX

anim_save(filename = XX, animation = XX)

3 - Plotly

1. Use ggplotly, to turn the base plot into a plotly package and then run it. Inspect the plot and observe whether the hover information includes all relevant information.

p <- XX(XX)
p

2. Adjust the base plot to include text = paste0("Quarter: ", quarter,"<br>Year: ", year,"<br>Income: ", income_mean)) in the aes() function. Save the plot again as plot.

3. Use the updated plot in ggplotly and verify that the hover information has been updated.

p <- XX(XX)
p

4 - Project work

1. Try to use what you have learned in this section to either create an animated or interactive version of your plot.