Even the most experienced R users need help creating elegant graphics. The ggplot2 library is a phenomenal tool for creating graphics in R but even after many years of near-daily use we still need to refer to our Cheat Sheet. Up until now, we’ve kept these key tidbits on a local PDF. But for our own benefit (and hopefully yours) we decided to post the most useful bits of code.

We start with the the quick setup and a default plot followed by a range of adjustments below.

• Quick-setup: The dataset
• A default plot in ggplot2
• Working with the title
  • Add a title (ggtitle() or labs())
  • Make title bold and add a little space at the baseline (face, vjust)
  • Use a non-traditional font in your title (family)
  • Change spacing in multi-line text (lineheight)
• Working with axes
  • Add x and y axis labels (labs(), xlab())
  • Get rid of axis tick and labels (theme(), axis.ticks.y)
  • Change size of tick text (axis.text.x)
  • Move the labels away from the plot (and add color) (theme(), axis.title.x)
  • Limit an axis to a range (ylim, scale_x_continuous(), coord_cartesian())
  • If you want the axes to be the same (coord_equal())
• Working with the legend
  • Turn off the legend title (legend.title)
  • Change the styling of the legend title (legend.title)
  • Change the title of the legend (name)
  • Change the background boxes in the legend (legend.key)
  • Change the size of the symbols in the legend only (guides(), guide_legend)
  • Leave a layer off the legend (show_guide)
  • Manually adding legend items (guides(), override.aes)
• Working with the background colors
  • Change the panel color (panel.background)
  • Change the grid lines (panel.grid.major)
  • Change the plot background (not the panel) color (plot.background)
• Working with multi-panel plots
  • Create a single row of plots based on one variable (facet_wrap())
  • Create a matrix of plots based on one variable (facet_wrap())
  • Allow scales to roam free (scales)
  • Create a grid of plots using two variables (facet_grid())
  • Put two (potentially unrelated) plots side by side (pushViewport())
• Working with themes
  • Use a new theme (theme_XX())
  • Tip on creating a custom theme
• Working with colors
  • Categorical variables: manually select the colors (scale_color_manual)
  • Categorical variables: try a built-in palette (based on colorbrewer2.org) (scale_color_brewer):
  • Color choice with continuous variables (scale_color_gradient(), scale_color_gradient2())
• Working with annotation
  • Add text annotation in the top-right, top-left etc. (annotation_custom() and textGrob())
    Working with coordinates
  • Flip a plot on it’s side (coord_flip())
• Working with plot types
  • Alternatives to the box plot (geom_jitter() and geom_violin())
  • Create a ribbon (geom_ribbon())
• Create interactive, online versions of your plots (easier than you think)

扩展链接：

• 博文地址：Beautiful plotting in R: A ggplot2 cheatsheet