SLCU R Course

Data Visualization with R - exercise solutions

Challenge: can you make a violin plot instead? (hint: ?geom_violin)

ggplot(expt1, aes(genotype, days.to.flower)) +
  geom_boxplot()
## Warning: Removed 83 rows containing non-finite values (stat_boxplot).

Challenge: can you modify this plot so that the points appear on top of the boxplots rather than behind them?

ggplot(expt1, aes(genotype, rosette.leaf.num)) +
  geom_boxplot() + 
  geom_jitter()
## Warning: Removed 95 rows containing non-finite values (stat_boxplot).
## Warning: Removed 95 rows containing missing values (geom_point).

Challenge: say we are particularly interested in the relationship between number of rosette leafs and blade length in mm per genotype.

Visualize this relationship with a scatter plot (geom_point()) between blade.length.mm and rosette.leaf.num and colour the points by genotype.

What happens if you colour the points by days.to.bolt?

ggplot(expt1, aes(blade.length.mm, rosette.leaf.num, colour = genotype)) +
  geom_point()
## Warning: Removed 333 rows containing missing values (geom_point).

If we colour the points by days.to.bolt the colour scale is continuous rather than discrete (because days.to.bolt is a numeric variable):

ggplot(expt1, aes(blade.length.mm, rosette.leaf.num, colour = days.to.bolt)) +
  geom_point()
## Warning: Removed 333 rows containing missing values (geom_point).

Challenge: In the previous graph, colouring the genotype is redundant with the facetting. Can you think of a more useful way to colour the points?

ggplot(expt1, aes(blade.length.mm, rosette.leaf.num, colour = fluctuation)) +
    geom_point() +
    facet_wrap( ~ genotype)
## Warning: Removed 333 rows containing missing values (geom_point).

Challenge: Can you modify the previous graph to facet the data by the fluctuation treatment (as rows) and day.length (as columns) and colour the points by genotype.

ggplot(expt1, aes(blade.length.mm, rosette.leaf.num, colour = genotype)) +
    geom_point() +
    facet_grid(day.length ~ fluctuation)
## Warning: Removed 333 rows containing missing values (geom_point).

Challenge: Can you produce a graph similar to Fig. 2B-C of Burghard et al 2015.

Hint: facet the plot by day.length and temperature and fill the boxplots by fluctuation.

ggplot(expt1, aes(genotype, days.to.bolt, fill = fluctuation)) +
    geom_boxplot() +
    facet_grid(day.length ~ temperature)