Set up

Make sure to run this code once to load our items

Create a new data set

Let’s make a filtered data set that includes only two years, 2002 and 2007. Note how we save it to an object, gapminder_filtered

# Make sure you ran the chunk above to load your libraries

gapminder_filtered <- gapminder %>% 
  filter(year > 2000)

Make a base plot

## Start by making a facted plot 

base_plot <- ggplot(data = gapminder_filtered,
                    mapping = aes(x = gdpPercap, y = lifeExp, 
                                  color = continent, size = pop)) +
  geom_point() + 
  facet_wrap(vars(year))

base_plot

Now, fix the x-axis so it is logged gdpPercap. You will need a type of scale() function. Note that if you paste labels = dollar_format(accuracy = 1) inside the parentheses of your scale function, you can change how the dollar values are presented!

# base_plot <- base_plot + CODE HERE

base_plot

What does this modification do?

base_plot <- base_plot + 
  
  scale_size_continuous(labels = comma)
  
base_plot

Let’s adjust the color scale. Oceania is really hard to see! What can we do? We can exclude the top-most value of the range by adding end = 0.9 to the scale_color_viridis_d option. Because it’s a new option, make sure to separate by a comma.

Fix the color scale now:

base_plot <- base_plot + 
  # Use viridis
  scale_color_viridis_d(option = "plasma") 

base_plot

Now, let’s add some labels:

Remember the generic form:

labs(x = "XTITLE", y = "YTITLE",
       `color = "COLOR LEGEND TITLE", size = "SIZE LEGENDTITLE",
       `title = "TITLE",
       `subtitle = "SUBTITLE",
       caption = "CAPTION)
#base_plot <- base_plot + 
#  labs(STUFFF)

base_plot

Optional - play with ggThemeAssist

If you’re feeling adventurous, you can mess more with ggThemeAssist:

#install.packages("ggThemeAssist")
library(ggThemeAssist)

base_plot

# First, run this chunk to load the library 
# Then, highlight base_plot. 
# Then click on "Addins" and select "ggplot Theme Assistant"
# Play! 
# When you're done, check out the code you've created.

Export

Finally, let’s export it as a png file!

Remember the generic form :

ggsave(filename = "NAME.png", plot = TITLE, width = 6, height = 4.5, units = "in")
# Export to a png file

Upload your png file to blackboard, and you’re done!