Page last updated: 04 May, 2019

Examples

One variable

##### scatter plot
ggplot(data = movies, 
       aes(x = votes, y = rating)) +
  geom_point(aes(x = votes, y = rating),
             color = discrete_wes_pal[1]) +
  my_theme()

One variable shown by colour

##### scatter plot - with multiple groups
ggplot(data = movies, 
       aes(x = votes, y = rating)) +
  geom_point(aes(colour = Genre))  +
  scale_color_manual(values = discrete_wes_pal) +
  guides(colour = guide_legend(override.aes = list(size = 5),
                               title = "",
                               label.hjust = 0,
                               label.vjust = 0.5)) +
    my_theme()

One variable shown by size

##### scatter plot - with groups defined by size
ggplot(data = movies, 
       aes(x = votes, y = rating)) +
  geom_point(aes(size = Genre),
             color = discrete_wes_pal[1]) +
  guides(size = guide_legend(title = "",
                               label.hjust = 0,
                               label.vjust = 0.5)) +
  my_theme()

Scatter plot with line of fit and ci

##### scatter plot - with stat_smooth function with lines of fit and CI
ggplot(data = movies, 
       aes(x = votes, y = rating)) +
  geom_point(aes(colour = Genre)) +
  scale_color_manual(values = discrete_wes_pal) +
  stat_smooth(aes(colour = Genre),
              alpha = 0.2,
              show.legend = FALSE) +
  guides(colour = guide_legend(override.aes = list(size = 5),
                               title = "",
                               label.hjust = 0,
                               label.vjust = 0.5)) +
  my_theme()

Grouped plots - facet_grid()

##### scatter plot - individual plots for each group horizontal
ggplot(data = movies, 
       aes(x = votes, y = rating)) +
  geom_point(aes(colour = Genre)) +
  scale_color_manual(values = discrete_wes_pal) +
  facet_grid(Genre ~ .) + # facet_grid makes horizontal grids
  guides(colour = guide_legend(override.aes = list(size = 5),
                               title = "",
                               label.hjust = 0,
                               label.vjust = 0.5)) +
  my_theme() +
  theme(
    strip.text.y = element_blank()
    )

Grouped plots - facet_wrap()

##### scatter plot - individual plots for each group in defined number of columns
ggplot(data = movies, 
       aes(x = votes, y = rating)) +
  geom_point(aes(colour = Genre)) +
  scale_color_manual(values = discrete_wes_pal) +
  facet_wrap(~Genre, ncol=4) + # facet_wrap makes columns of n length
  guides(colour = guide_legend(override.aes = list(size = 5),
                               title = "",
                               label.hjust = 0,
                               label.vjust = 0.5)) +
  coord_flip() + # flips the x and y axis
  my_theme() +
  theme(
    strip.text.x = element_blank()
  )

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