ggplot2 v3.1.0


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Create Elegant Data Visualisations Using the Grammar of Graphics

A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.



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ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.


# The easiest way to get ggplot2 is to install the whole tidyverse:

# Alternatively, install just ggplot2:

# Or the the development version from GitHub:
# install.packages("devtools")



It’s hard to succinctly describe how ggplot2 works because it embodies a deep philosophy of visualisation. However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), faceting specifications (like facet_wrap()) and coordinate systems (like coord_flip()).


ggplot(mpg, aes(displ, hwy, colour = class)) + 



ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behaviour of existing functions, and if we do make changes to existing behaviour we will do them for compelling reasons.

If you are looking for innovation, look to ggplot2’s rich ecosystem of extensions. See a community maintained list at

Learning ggplot2

If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages. Currently, there are three good places to start:

  1. The data visualisation and graphics for communication chapters in R for data science. R for data science is designed to give you a comprehensive introduction to the tidyverse, and these two chapters will you get up to speed with the essentials of ggplot2 as quickly as possible.

  2. If you’d like to take an interactive online course, try Data visualisation with ggplot2 by Rick Scavetta on DataCamp.

  3. If you want to dive into making common graphics as quickly as possible, I recommend The R Graphics Cookbook by Winston Chang. It provides a set of recipes to solve common graphics problems. A 2nd edition is due out in 2018.

If you’ve mastered the basics and want to learn more, read ggplot2: Elegant Graphics for Data Analysis. It describes the theoretical underpinnings of ggplot2 and shows you how all the pieces fit together. This book helps you understand the theory that underpins ggplot2, and will help you create new types of graphics specifically tailored to your needs. The book is not available for free, but you can find the complete source for the book at

Getting help

There are two main places to get help with ggplot2:

  1. The RStudio community is a friendly place to ask any questions about ggplot2.

  2. Stack Overflow is a great source of answers to common ggplot2 questions. It is also a great place to get help, once you have created a reproducible example that illustrates your problem.

Functions in ggplot2

Name Description
autoplot Create a complete ggplot appropriate to a particular data type
annotation_custom Annotation: Custom grob
facet_grid Lay out panels in a grid
benchplot Benchmark plot creation time. Broken down into construct, build, render and draw times.
annotate Create an annotation layer
combine_vars Take input data and define a mapping between faceting variables and ROW, COL and PANEL keys
continuous_scale Continuous scale constructor.
draw_key Key drawing functions
facet_null Facet specification: a single panel.
economics US economic time series
annotation_raster Annotation: high-performance rectangular tiling
annotation_logticks Annotation: log tick marks
coord_cartesian Cartesian coordinates
coord_fixed Cartesian coordinates with fixed "aspect ratio"
borders Create a layer of map borders
margin Theme elements
as.list.ggproto Convert a ggproto object to a list
find_panel Find panels in a gtable
element_grob Generate grid grob from theme element
fortify-multcomp Fortify methods for objects produced by multcomp
geom_count Count overlapping points
calc_element Calculate the element properties, by inheriting properties from its parents
add_theme Modify properties of an element in a theme object
as_labeller Coerce to labeller function
geom_boxplot A box and whiskers plot (in the style of Tukey)
coord_munch Munch coordinates data
geom_contour 2d contours of a 3d surface
geom_density Smoothed density estimates
annotation_map Annotation: a maps
diamonds Prices of 50,000 round cut diamonds
geom_path Connect observations
coord_polar Polar coordinates
facet_wrap Wrap a 1d ribbon of panels into 2d
discrete_scale Discrete scale constructor.
autolayer Create a ggplot layer appropriate to a particular data type
geom_crossbar Vertical intervals: lines, crossbars & errorbars
geom_map Polygons from a reference map
geom_label Text
expand_limits Expand the plot limits, using data
faithfuld 2d density estimate of Old Faithful data
geom_point Points
is.Coord Is this object a coordinate system?
coord_flip Cartesian coordinates with x and y flipped Fortify method for map objects
fortify.sp Fortify method for classes from the sp package.
coord_map Map projections
coord_trans Transformed Cartesian coordinate system
geom_abline Reference lines: horizontal, vertical, and diagonal
is.facet Is this object a faceting specification?
cut_interval Discretise numeric data into categorical
geom_density_2d Contours of a 2d density estimate
labeller Construct labelling specification
geom_bin2d Heatmap of 2d bin counts
geom_blank Draw nothing
expand_scale Generate expansion vector for scales.
fortify Fortify a model with data.
geom_dotplot Dot plot
geom_bar Bar charts
fortify.lm Supplement the data fitted to a linear model with model fit statistics.
geom_raster Rectangles
labellers Useful labeller functions
geom_quantile Quantile regression
geom_polygon Polygons
ggplot_build Build ggplot for rendering.
ggplot_gtable Build a plot with all the usual bits and pieces.
geom_freqpoly Histograms and frequency polygons
geom_errorbarh Horizontal error bars
geom_qq_line A quantile-quantile plot
guide_colourbar Continuous colour bar guide
msleep An updated and expanded version of the mammals sleep dataset
ggproto Create a new ggproto object
geom_ribbon Ribbons and area plots
position_dodge Dodge overlapping objects side-to-side
position_stack Stack overlapping objects on top of each another
presidential Terms of 11 presidents from Eisenhower to Obama
geom_jitter Jittered points
geom_hex Hexagonal heatmap of 2d bin counts
guide_legend Legend guide
scale_date Position scales for date/time data
scale_x_discrete Position scales for discrete data
geom_violin Violin plot
geom_rug Rug plots in the margins
scale_type Determine default scale type
ggsave Save a ggplot (or other grid object) with sensible defaults
geom_segment Line segments and curves
scale_colour_viridis_d Viridis colour scales from viridisLite
ggplot2-ggproto Base ggproto classes for ggplot2
guide-exts S3 generics for guides.
graphical-units Graphical units
geom_smooth Smoothed conditional means Add components to a plot
ggplot2-package ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics
labs Modify axis, legend, and plot labels
ggplotGrob Generate a ggplot2 plot grob.
guides Set guides for each scale
geom_spoke Line segments parameterised by location, direction and distance
is.theme Reports whether x is a theme object
tidyeval Tidy eval helpers
ggplot_add Add custom objects to ggplot
ggsf Visualise sf objects
label_bquote Label with mathematical expressions
gg_dep Give a deprecation error, warning, or message, depending on version number.
hmisc A selection of summary functions from Hmisc
ggtheme Complete themes
mean_se Calculate mean and standard error
transform_position Convenience function to transform all position variables.
translate_qplot_ggplot Translating between qplot and ggplot
translate_qplot_lattice Translating between qplot and lattice
is.ggplot Reports whether x is a ggplot object
ggplot Create a new ggplot
is.rel Reports whether x is a rel object
position_jitterdodge Simultaneously dodge and jitter
merge_element Merge a parent element into a child element
layer Create a new layer
position_nudge Nudge points a fixed distance
lims Set scale limits
luv_colours colors() in Luv space
print.ggplot Explicitly draw plot
last_plot Retrieve the last plot to be modified or created.
print.ggproto Format or print a ggproto object
remove_missing Convenience function to remove missing values from a data.frame
qplot Quick plot
reexports Objects exported from other packages
render_axes Render panel axes
scale_colour_hue Evenly spaced colours for discrete data
scale_linetype Scale for line patterns
limits Generate correct scale type for specified limits
scale_manual Create your own discrete scale
map_data Create a data frame of map data
max_height Get the maximal width/length of a list of grobs
position_identity Don't adjust position
position_jitter Jitter points to avoid overplotting
scale_colour_continuous Continuous colour scales
seals Vector field of seal movements
scale_identity Use values without scaling
midwest Midwest demographics
mpg Fuel economy data from 1999 and 2008 for 38 popular models of car
sec_axis Specify a secondary axis
scale_alpha Alpha transparency scales
render_strips Render panel strips
scale_continuous Position scales for continuous data (x & y)
stat_identity Leave data as is
stat_function Compute function for each x value
set_last_plot Set the last plot to be fetched by lastplot()
summarise_plot Summarise built plot objects
stat_sf_coordinates Extract coordinates from 'sf' objects
stat_summary_bin Summarise y values at unique/binned x
summary.ggplot Displays a useful description of a ggplot object
should_stop Used in examples to illustrate when errors should occur.
waiver A waiver object.
theme Modify components of a theme
txhousing Housing sales in TX
theme_get Get, set, and modify the active theme
wrap_dims Arrange 1d structure into a grid
resolution Compute the "resolution" of a numeric vector
scale_shape Scales for shapes, aka glyphs
zeroGrob The zero grob draws nothing and has zero size.
scale_size Scales for area or radius
update_geom_defaults Modify geom/stat aesthetic defaults for future plots
scale_colour_gradient Gradient colour scales
scale_colour_brewer Sequential, diverging and qualitative colour scales from
scale_colour_grey Sequential grey colour scales
standardise_aes_names Standardise aesthetic names
stat Calculated aesthetics
stat_ecdf Compute empirical cumulative distribution
stat_ellipse Compute normal confidence ellipses
stat_summary_2d Bin and summarise in 2d (rectangle & hexagons)
stat_unique Remove duplicates
update_labels Update axis/legend labels
vars Quote faceting variables
aes Construct aesthetic mappings
aes_all Given a character vector, create a set of identity mappings
aes_colour_fill_alpha Colour related aesthetics: colour, fill and alpha
aes_auto Automatic aesthetic mapping
aes_group_order Aesthetics: grouping
absoluteGrob Absolute grob
aes_linetype_size_shape Differentiation related aesthetics: linetype, size, shape
aes_position Position related aesthetics: x, y, xmin, xmax, ymin, ymax, xend, yend
aes_ Define aesthetic mappings programmatically
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License GPL-2 | file LICENSE
LazyData true
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VignetteBuilder knitr
RoxygenNote 6.1.0
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Packaged 2018-10-24 18:49:13 UTC; hadley
Repository CRAN
Date/Publication 2018-10-25 04:30:25 UTC

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