| Title: | Extra Themes, Scales and Geoms for 'ggplot2' |
|---|---|
| Description: | Some extra themes, geoms, and scales for 'ggplot2'. Provides 'ggplot2' themes and scales that replicate the look of plots by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', 'Excel', and 'The Wall Street Journal', among others. Provides 'geoms' for Tufte's box plot and range frame. |
| Authors: | Jeffrey B. Arnold [aut, cre]  ,
Gergely Daroczi [ctb],
Bo Werth [ctb],
Brian Weitzner [ctb],
Joshua Kunst [ctb],
Baptise Auguie [ctb],
Bob Rudis [ctb],
Hadley Wickham [ctb] (Code from the ggplot2 package.),
Justin Talbot [ctb] (Code from the labeling package),
Joshua London [ctb] |
| Maintainer: | Jeffrey B. Arnold <[email protected]> |
| License: | GPL-2 |
| Version: | 5.1.0.9000 |
| Built: | 2024-11-10 04:00:36 UTC |
| Source: | https://github.com/jrnold/ggthemes |
Calculate the optimal aspect ratio of a line graph by banking the slopes to 45 degrees as suggested by W.S. Cleveland. This maximizes the ability to visually differentiate differences in slope. This function will calculate the optimal aspect ratio for a line plot using any of the methods described in Herr and Argwala (2006). In their review of the methods they suggest using median absolute slope banking ('ms'), which produces aspect ratios which are generally the median of the various methods provided here.
bank_slopes(x, y, cull = FALSE, weight = NULL, method = c("ms", "as"), ...)bank_slopes(x, y, cull = FALSE, weight = NULL, method = c("ms", "as"), ...)
x |
x values |
y |
y values |
cull |
|
weight |
No longer used, but kept for backwards compatibility. |
method |
One of 'ms' (Median Absolute Slope) or 'as' (Average Absolute Slope). Other options are no longer supported, and will use 'ms' instead with a warning. |
... |
No longer used, but kept for backwards compatibility. |
numeric The aspect ratio (x , y).
As written, all of these methods calculate the aspect ratio (x
/y), but bank_slopes will return (y / x) to be compatible
with link[ggplot2]{coord_fixed()}.
Median Absolute Slopes Banking
Let the aspect ratio be
then the median absolute slop banking is the
such that,
Let for ,
and . Then,
Average Absolute Slope Banking
Let the aspect ratio be .
then the mean absolute slope banking is the
such that,
Heer and Agrawala (2006) and Cleveland discuss several other methods including average (weighted) orientation, and global and local orientation resolution. These are no longer implemented in this function. In general, either the median or average absolute slopes will produce reasonable results without requiring optimization.
Cleveland, W. S., M. E. McGill, and R. McGill. The Shape Parameter of a Two-Variable Graph. Journal of the American Statistical Association, 83:289-300, 1988
Heer, Jeffrey and Maneesh Agrawala, 2006. 'Multi-Scale Banking to 45' IEEE Transactions On Visualization And Computer Graphics.
Cleveland, W. S. 1993. 'A Model for Studying Display Methods of Statistical Graphs.' Journal of Computational and Statistical Graphics.
Cleveland, W. S. 1994. The Elements of Graphing Data, Revised Edition.
banking()
library("ggplot2") # Use the classic sunspot data from Cleveland's original paper x <- seq_along(sunspot.year) y <- as.numeric(sunspot.year) # Without banking m <- ggplot(data.frame(x = x, y = y), aes(x = x, y = y)) + geom_line() m ## Using the default method, Median Absolute Slope ratio <- bank_slopes(x, y) m + coord_fixed(ratio = ratio) ## Using culling ## Average Absolute Slope bank_slopes(x, y, method = "as")library("ggplot2") # Use the classic sunspot data from Cleveland's original paper x <- seq_along(sunspot.year) y <- as.numeric(sunspot.year) # Without banking m <- ggplot(data.frame(x = x, y = y), aes(x = x, y = y)) + geom_line() m ## Using the default method, Median Absolute Slope ratio <- bank_slopes(x, y) m + coord_fixed(ratio = ratio) ## Using culling ## Average Absolute Slope bank_slopes(x, y, method = "as")
Color palettes from LibreOffice Calc. This palette has 12 values.
calc_pal()calc_pal()
Other colour calc:
scale_fill_calc()
library("scales") show_col(calc_pal()(12))library("scales") show_col(calc_pal()(12))
Shape palette based on the shapes used in LibreOffice Calc.
calc_shape_pal()calc_shape_pal()
Other shapes calc:
scale_shape_calc()
## Not run: library("ggplot2") show_shapes(calc_shape_pal()(13)) ## End(Not run)## Not run: library("ggplot2") show_shapes(calc_shape_pal()(13)) ## End(Not run)
150+ color palettes from canva.com. See canva_palettes().
canva_pal(palette = "Fresh and bright")canva_pal(palette = "Fresh and bright")
palette |
Palette name. See the names of |
A function that takes a single value, the number of colors to use.
require("ggplot2") require("tibble") if (require("purrr") && require("scales") && require("dplyr")) { canva_df <- map2_df( canva_palettes, names(canva_palettes), ~ tibble( colors = .x, .id = seq_along(colors), palette = .y ) ) ggplot(canva_df, aes( y = palette, x = .id, fill = colors )) + geom_raster() + scale_fill_identity(guide = FALSE) + theme_minimal() + theme( panel.grid = element_blank(), axis.text.x = element_blank() ) + labs(x = "", y = "") show_col(canva_pal("Fresh and bright")(4)) show_col(canva_pal("Cool blues")(4)) show_col(canva_pal("Modern and crisp")(4)) }require("ggplot2") require("tibble") if (require("purrr") && require("scales") && require("dplyr")) { canva_df <- map2_df( canva_palettes, names(canva_palettes), ~ tibble( colors = .x, .id = seq_along(colors), palette = .y ) ) ggplot(canva_df, aes( y = palette, x = .id, fill = colors )) + geom_raster() + scale_fill_identity(guide = FALSE) + theme_minimal() + theme( panel.grid = element_blank(), axis.text.x = element_blank() ) + labs(x = "", y = "") show_col(canva_pal("Fresh and bright")(4)) show_col(canva_pal("Cool blues")(4)) show_col(canva_pal("Modern and crisp")(4)) }
150 four-color palettes by the canva.com design school. These palettes were derived from photos and "impactful websites".
canva_palettescanva_palettes
A named list of character vector.
The names are the palette names. The values of the character vectors
are hex colors, e.g. "#f98866".
Janie Kliever, 100 Brilliant Color Combinations and How to Apply Them to Your Designs, Canva.com, June 20, 2015.
Mary Stribley, Website Color Schemes: The Palettes of 50 Visually Impactful Websites to Inspire You, Canva.com, January 26, 2016.
Schwabish, Jonathan. 150+ Color Palettes for Excel, PolicyViz, January 12, 2017.
require("ggplot2") require("tibble") if (require("purrr") && require("scales") && require("dplyr")) { canva_df <- map2_df( canva_palettes, names(canva_palettes), ~ tibble( colors = .x, .id = seq_along(colors), palette = .y ) ) ggplot(canva_df, aes( y = palette, x = .id, fill = colors )) + geom_raster() + scale_fill_identity(guide = FALSE) + theme_minimal() + theme( panel.grid = element_blank(), axis.text.x = element_blank() ) + labs(x = "", y = "") show_col(canva_pal("Fresh and bright")(4)) show_col(canva_pal("Cool blues")(4)) show_col(canva_pal("Modern and crisp")(4)) }require("ggplot2") require("tibble") if (require("purrr") && require("scales") && require("dplyr")) { canva_df <- map2_df( canva_palettes, names(canva_palettes), ~ tibble( colors = .x, .id = seq_along(colors), palette = .y ) ) ggplot(canva_df, aes( y = palette, x = .id, fill = colors )) + geom_raster() + scale_fill_identity(guide = FALSE) + theme_minimal() + theme( panel.grid = element_blank(), axis.text.x = element_blank() ) + labs(x = "", y = "") show_col(canva_pal("Fresh and bright")(4)) show_col(canva_pal("Cool blues")(4)) show_col(canva_pal("Modern and crisp")(4)) }
'r lifecycle::badge("deprecated")'
This function was deprecated because unicode glyphs used for the circles vary in size, making them unusable for plotting.
Shape palette with circles varying by amount of fill. This uses the set of 3 circle fill values in Lewandowsky and Spence (1989): solid, hollow, half-filled, with two additional fill amounts: three-quarters, and one-quarter.
This palette supports up to five values.
circlefill_shape_pal()circlefill_shape_pal()
Lewandowsky, Stephan and Ian Spence (1989) "Discriminating Strata in Scatterplots", Journal of the American Statistical Association, https://www.jstor.org/stable/2289649
Other shapes:
cleveland_shape_pal(),
scale_shape_circlefill(),
scale_shape_cleveland(),
scale_shape_tremmel(),
tremmel_shape_pal()
Shape palettes for overlapping and non-overlapping points.
cleveland_shape_pal(overlap = TRUE)cleveland_shape_pal(overlap = TRUE)
overlap |
|
In the Elements of Graphing Data, W.S. Cleveland suggests two shape palettes for scatter plots: one for overlapping data and another for non-overlapping data. The symbols for overlapping data relies on pattern discrimination, while the symbols for non-overlapping data vary the amount of fill. This palette attempts to create these palettes. However, I found that these were hard to replicate. Using the R shapes and unicode fonts: the symbols can vary in size, they are dependent of the fonts used, and there does not exist a unicode symbol for a circle with a vertical line. If someone can improve this palette, please let me know.
Following Tremmel (1995), I replace the circle with a vertical line with an encircled plus sign.
The palette cleveland_shape_pal() supports up to five values.
Cleveland WS. The Elements of Graphing Data. Revised Edition. Hobart Press, Summit, NJ, 1994, pp. 154-164, 234-239.
Tremmel, Lothar, (1995) "The Visual Separability of Plotting Symbols in Scatterplots", Journal of Computational and Graphical Statistics, https://www.jstor.org/stable/1390760
Other shapes:
circlefill_shape_pal(),
scale_shape_circlefill(),
scale_shape_cleveland(),
scale_shape_tremmel(),
tremmel_shape_pal()
### (discrete). ## Not run: library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) + theme_bw() # overlapping symbol palette p + scale_shape_cleveland() # non-overlapping symbol palette p + scale_shape_cleveland(overlap = FALSE) ## End(Not run)### (discrete). ## Not run: library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) + theme_bw() # overlapping symbol palette p + scale_shape_cleveland() # non-overlapping symbol palette p + scale_shape_cleveland(overlap = FALSE) ## End(Not run)
An eight-color colorblind safe qualitative discrete palette.
colorblind_pal() scale_colour_colorblind(...) scale_color_colorblind(...) scale_fill_colorblind(...)colorblind_pal() scale_colour_colorblind(...) scale_color_colorblind(...) scale_fill_colorblind(...)
... |
Arguments passed on to
|
Chang, W. "Cookbook for R"
https://jfly.iam.u-tokyo.ac.jp/color
The dichromat package, dichromat_pal(),
and scale_color_tableau() for other colorblind palettes.
library("ggplot2") library("scales") show_col(colorblind_pal()(8)) p <- ggplot(mtcars) + geom_point(aes( x = wt, y = mpg, colour = factor(gear) )) + facet_wrap(~am) p + theme_igray() + scale_colour_colorblind()library("ggplot2") library("scales") show_col(colorblind_pal()(8)) p <- ggplot(mtcars) + geom_point(aes( x = wt, y = mpg, colour = factor(gear) )) + facet_wrap(~am) p + theme_igray() + scale_colour_colorblind()
The hues in the palette are blues, grays, and greens. Red is not included in these palettes and should be used to indicate important data.
economist_pal(fill = TRUE)economist_pal(fill = TRUE)
fill |
Use the fill palette. |
Other colour economist:
scale_colour_economist()
library("scales") show_col(economist_pal()(6)) ## fill palette show_col(economist_pal(fill = TRUE)(6))library("scales") show_col(economist_pal()(6)) ## fill palette show_col(economist_pal(fill = TRUE)(6))
Color palettes used by current versions of Microsoft Office and Excel.
excel_new_pal(theme = "Office Theme")excel_new_pal(theme = "Office Theme")
theme |
The name of the Office theme or color theme
(not to be confused with ggplot2 themes) from which to derive the color
palette. Available themes include:
|
Other colour excel:
excel_pal(),
scale_colour_excel_new(),
scale_fill_excel()
library("scales") for (i in names(ggthemes::ggthemes_data$excel$palettes)) { show_col(excel_new_pal(theme = i))(6) }library("scales") for (i in names(ggthemes::ggthemes_data$excel$palettes)) { show_col(excel_new_pal(theme = i))(6) }
The color palettes used in Microsoft Excel 97 (and up until Excel 2007). Use this for that classic ugly look and feel. For ironic purposes only. 3D bars and pies not included. Please never use this color palette.
excel_pal(line = TRUE)excel_pal(line = TRUE)
line |
If |
Other colour excel:
excel_new_pal(),
scale_colour_excel_new(),
scale_fill_excel()
library("scales") show_col(excel_pal()(7)) show_col(excel_pal(line = FALSE)(7))library("scales") show_col(excel_pal()(7)) show_col(excel_pal(line = FALSE)(7))
This function returns pretty axis breaks that always include the extreme values of the data. This works by calling the extended Wilkinson algorithm (Talbot et al., 2010), constrained to solutions interior to the data range. Then, the minimum and maximum labels are moved to the minimum and maximum of the data range.
extended_range_breaks_( dmin, dmax, n = 5, Q = c(1, 5, 2, 2.5, 4, 3), w = c(0.25, 0.2, 0.5, 0.05) ) extended_range_breaks(n = 5, ...)extended_range_breaks_( dmin, dmax, n = 5, Q = c(1, 5, 2, 2.5, 4, 3), w = c(0.25, 0.2, 0.5, 0.05) ) extended_range_breaks(n = 5, ...)
dmin |
minimum of the data range |
dmax |
maximum of the data range |
n |
desired number of breaks |
Q |
set of nice numbers |
w |
weights applied to the four optimization components (simplicity, coverage, density, and legibility) |
... |
other arguments passed to |
extended_range_breaks implements the algorithm and returns the break values.
scales_extended_range_breaks uses the conventions of the scales package, and returns a function.
For extended_range_breaks, the vector of axis label locations.
For scales_extended_range_breaks, a function which takes a single argument, a vector of data, and returns
the vector of axis label locations.
A function which returns breaks given a vector.
Justin Talbot [email protected], Jeffrey B. Arnold, Baptiste Auguie
Talbot, J., Lin, S., Hanrahan, P. (2010) An Extension of Wilkinson's Algorithm for Positioning Tick Labels on Axes, InfoVis 2010.
Qualitative color palettes from Stephen Few (2012)
Show Me the Numbers. There are three palettes:
Light, Medium, and Dark. Each palette comprises nine colors:
gray, blue, orange, green, pink, brown, purple, yellow, red.
For n = 1, gray is used. For n > 1, the eight non-gray
colors are used.
few_pal(palette = "Medium")few_pal(palette = "Medium")
palette |
One of |
Use the light palette for filled areas, such as bar charts. Use the medium palette for points and lines. Use the dark palette for highlighting specific points or for small and thin lines and points.
Few, S. (2012) Show Me the Numbers: Designing Tables and Graphs to Enlighten. 2nd edition. Analytics Press.
"Practical Rules for Using Color in Charts".
Other colour few:
scale_colour_few()
library("scales") show_col(few_pal()(7)) show_col(few_pal("Dark")(7)) show_col(few_pal("Light")(7))library("scales") show_col(few_pal()(7)) show_col(few_pal("Dark")(7)) show_col(few_pal("Light")(7))
Shape palette from Stephen Few's, "Show Me the Numbers". The shape palette consists of five shapes: circle, square, triangle, plus, times.
few_shape_pal()few_shape_pal()
Few, S. (2012) Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, p. 208.
The standard three-color FiveThirtyEight palette for line plots comprises blue, red, and green.
fivethirtyeight_pal()fivethirtyeight_pal()
Other colour fivethirtyeight:
scale_colour_fivethirtyeight()
library("scales") show_col(fivethirtyeight_pal()(3))library("scales") show_col(fivethirtyeight_pal()(3))
Color palettes from Google Docs. This palette includes 20 colors.
gdocs_pal()gdocs_pal()
Other colour gdocs:
scale_fill_gdocs()
library("scales") show_col(gdocs_pal()(24))library("scales") show_col(gdocs_pal()(24))
Axis lines which extend to the maximum and minimum of the plotted data.
geom_rangeframe( mapping = NULL, data = NULL, stat = "identity", position = "identity", ..., sides = "bl", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE )geom_rangeframe( mapping = NULL, data = NULL, stat = "identity", position = "identity", ..., sides = "bl", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE )
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
stat |
The statistical transformation to use on the data for this
layer, either as a |
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
... |
Other arguments passed on to |
sides |
A string that controls which sides of the plot the frames appear on.
It can be set to a string containing any of |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
This should be used with 'coord_cartesian(clip="off")' in order to correctly draw the lines.
colour
size
linetype
alpha
Tufte, Edward R. (2001) The Visual Display of Quantitative Information, Chapter 6.
Other geom tufte:
geom_tufteboxplot()
library("ggplot2") ggplot(mtcars, aes(wt, mpg)) + geom_point() + geom_rangeframe() + coord_cartesian(clip = "off") + theme_tufte() # In the example above, # `coord_cartesian(clip="off")`` ensures that the full width of the line is drawn. # if you know a better way to fix this, # please open an issue or PR on github https://github.com/jrnold/ggthemes/issuelibrary("ggplot2") ggplot(mtcars, aes(wt, mpg)) + geom_point() + geom_rangeframe() + coord_cartesian(clip = "off") + theme_tufte() # In the example above, # `coord_cartesian(clip="off")`` ensures that the full width of the line is drawn. # if you know a better way to fix this, # please open an issue or PR on github https://github.com/jrnold/ggthemes/issue
Edward Tufte's revisions of the box plot as described in The Visual Display of Quantitative Information. This functions provides several box plot variants:
A point indicating the median, a gap indicating the interquartile range, and lines for whiskers.
An offset line indicating the interquartile range and a gap indicating the median.
A line indicating the interquartile range, a gap indicating the median, and points indicating the minimum and maximum values
A wide line indicating the interquartile range, a gap indicating the median, and lines indicating the minimum and maximum.
geom_tufteboxplot( mapping = NULL, data = NULL, stat = "fivenumber", position = "dodge", outlier.colour = "black", outlier.shape = 19, outlier.size = 1.5, outlier.stroke = 0.5, voffset = 0.01, hoffset = 0.005, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, median.type = "point", whisker.type = "line", ... )geom_tufteboxplot( mapping = NULL, data = NULL, stat = "fivenumber", position = "dodge", outlier.colour = "black", outlier.shape = 19, outlier.size = 1.5, outlier.stroke = 0.5, voffset = 0.01, hoffset = 0.005, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, median.type = "point", whisker.type = "line", ... )
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
stat |
The statistical transformation to use on the data for this
layer, as a string. The default ( |
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
outlier.colour |
colour for outlying points |
outlier.shape |
shape of outlying points |
outlier.size |
size of outlying points |
outlier.stroke |
stroke for outlying points |
voffset |
controls the size of the gap in the line representing the
median when |
hoffset |
controls how much the interquartile line is offset from the
whiskers when |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
median.type |
If |
whisker.type |
If |
... |
Other arguments passed on to |
x [required]
y [required]
colour
size
linetype
shape
fill
alpha
Tufte, Edward R. (2001) The Visual Display of Quantitative Information, Chapter 6.
McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 12-16.
Other geom tufte:
geom_rangeframe()
library("ggplot2") p <- ggplot(mtcars, aes(factor(cyl), mpg)) # with a point for the median and lines for whiskers p + geom_tufteboxplot() # with a line for the interquartile range and points for whiskers p + geom_tufteboxplot(median.type = "line", whisker.type = "point", hoffset = 0) # with a wide line for the interquartile range and lines for whiskers p + geom_tufteboxplot(median.type = "line", hoffset = 0, width = 3) # with an offset line for the interquartile range and lines for whiskers p + geom_tufteboxplot(median.type = "line") # combined with theme_tufte p + geom_tufteboxplot() + theme_tufte() + theme(axis.ticks.x = element_blank()) # traditional boxplot with whiskers only out to 1.5 IQR, outlier points p + geom_tufteboxplot(stat = "boxplot", outlier.shape = 5)library("ggplot2") p <- ggplot(mtcars, aes(factor(cyl), mpg)) # with a point for the median and lines for whiskers p + geom_tufteboxplot() # with a line for the interquartile range and points for whiskers p + geom_tufteboxplot(median.type = "line", whisker.type = "point", hoffset = 0) # with a wide line for the interquartile range and lines for whiskers p + geom_tufteboxplot(median.type = "line", hoffset = 0, width = 3) # with an offset line for the interquartile range and lines for whiskers p + geom_tufteboxplot(median.type = "line") # combined with theme_tufte p + geom_tufteboxplot() + theme_tufte() + theme(axis.ticks.x = element_blank()) # traditional boxplot with whiskers only out to 1.5 IQR, outlier points p + geom_tufteboxplot(stat = "boxplot", outlier.shape = 5)
The ggthemes environment contains various values used in
themes and palettes. This is undocumented and subject to change.
ggthemes_dataggthemes_data
A list object.
The Highcharts uses many different color palettes in its plots. This collects a few of them.
hc_pal(palette = "default")hc_pal(palette = "default")
palette |
|
Other colour hc:
scale_colour_hc()
The pander ships with a default colorblind and printer-friendly
color palette borrowed from https://jfly.iam.u-tokyo.ac.jp/color/.
palette_pander(n, random_order = FALSE)palette_pander(n, random_order = FALSE)
n |
number of colors. This palette supports up to eight colors. |
random_order |
if the palette should be reordered randomly before rendering each plot to get colorful images |
Other colour pander:
scale_color_pander()
## Not run: palette_pander(TRUE) ## End(Not run)## Not run: palette_pander(TRUE) ## End(Not run)
Qualitative color palettes from Paul Tol, "Colour Schemes".
ptol_pal()ptol_pal()
Incorporation of the palette into an R package was originally inspired by Peter Carl's [Paul Tol 21 Gun Salute](https://tradeblotter.wordpress.com/2013/02/28/the-paul-tol-21-color-salute/)
Paul Tol. 2012. "Colour Schemes." SRON Technical Note, SRON/EPS/TN/09-002. https://personal.sron.nl/~pault/data/colourschemes.pdf
Other colour ptol:
scale_colour_ptol()
library("scales") show_col(ptol_pal()(6)) show_col(ptol_pal()(4)) show_col(ptol_pal()(12))library("scales") show_col(ptol_pal()(6)) show_col(ptol_pal()(4)) show_col(ptol_pal()(12))
The pander ships with a default colorblind and printer-friendly color
palette borrowed from https://jfly.iam.u-tokyo.ac.jp/color/.
scale_color_pander(...) scale_colour_pander(...) scale_fill_pander(...)scale_color_pander(...) scale_colour_pander(...) scale_fill_pander(...)
... |
Arguments passed on to
|
Other colour pander:
palette_pander()
Color scale for canva.com color palettes described in
canva_palettes().
scale_colour_canva(..., palette = "Fresh and bright") scale_color_canva(..., palette = "Fresh and bright") scale_fill_canva(..., palette = "Fresh and bright")scale_colour_canva(..., palette = "Fresh and bright") scale_color_canva(..., palette = "Fresh and bright") scale_fill_canva(..., palette = "Fresh and bright")
... |
Arguments passed to |
palette |
Palette name. See the names of |
Color scales using the colors in the Economist graphics.
scale_colour_economist(...) scale_color_economist(...) scale_fill_economist(...)scale_colour_economist(...) scale_color_economist(...) scale_fill_economist(...)
... |
Arguments passed on to
|
theme_economist() for examples.
Other colour economist:
economist_pal()
Discrete color scales used in current versions of Microsoft Office and Excel.
scale_colour_excel_new(theme = "Office Theme", ...) scale_color_excel_new(theme = "Office Theme", ...) scale_fill_excel_new(theme = "Office Theme", ...)scale_colour_excel_new(theme = "Office Theme", ...) scale_color_excel_new(theme = "Office Theme", ...) scale_fill_excel_new(theme = "Office Theme", ...)
theme |
The name of the Office theme or color theme
(not to be confused with ggplot2 themes) from which to derive the color
palette. Available themes include:
|
... |
Arguments passed on to
|
Other colour excel:
excel_new_pal(),
excel_pal(),
scale_fill_excel()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel_new() + scale_colour_excel_new()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel_new() + scale_colour_excel_new()
See few_pal().
scale_colour_few(palette = "Medium", ...) scale_color_few(palette = "Medium", ...) scale_fill_few(palette = "Light", ...)scale_colour_few(palette = "Medium", ...) scale_color_few(palette = "Medium", ...) scale_fill_few(palette = "Light", ...)
palette |
One of |
... |
Arguments passed on to
|
Other colour few:
few_pal()
Color scales using the colors in the FiveThirtyEight graphics.
scale_colour_fivethirtyeight(...) scale_color_fivethirtyeight(...) scale_fill_fivethirtyeight(...)scale_colour_fivethirtyeight(...) scale_color_fivethirtyeight(...) scale_fill_fivethirtyeight(...)
... |
Arguments passed on to
|
theme_fivethirtyeight() for examples.
Other colour fivethirtyeight:
fivethirtyeight_pal()
Continuous color scales using the sequential color palettes in Tableau.
See scale_colour_tableau() for Tableau discrete color scales,
and scale_colour_gradient2_tableau() for diverging color
scales.
scale_colour_gradient_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_fill_gradient_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_color_gradient_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_color_continuous_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_fill_continuous_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" )scale_colour_gradient_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_fill_gradient_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_color_gradient_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_color_continuous_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" ) scale_fill_continuous_tableau( palette = "Blue", ..., na.value = "grey50", guide = "colourbar" )
palette |
Palette name.
|
... |
Arguments passed to |
na.value |
Colour to use for missing values |
guide |
Type of legend. Use |
Other colour tableau:
scale_colour_gradient2_tableau(),
scale_colour_tableau(),
tableau_color_pal(),
tableau_gradient_pal()
library("ggplot2") df <- data.frame( x = runif(100), y = runif(100), z1 = rnorm(100), z2 = abs(rnorm(100)) ) p <- ggplot(df, aes(x, y)) + geom_point(aes(colour = z2)) + theme_igray() palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["ordered-sequential"]] for (palette in head(names(palettes))) { print(p + scale_colour_gradient_tableau(palette) + ggtitle(palette)) }library("ggplot2") df <- data.frame( x = runif(100), y = runif(100), z1 = rnorm(100), z2 = abs(rnorm(100)) ) p <- ggplot(df, aes(x, y)) + geom_point(aes(colour = z2)) + theme_igray() palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["ordered-sequential"]] for (palette in head(names(palettes))) { print(p + scale_colour_gradient_tableau(palette) + ggtitle(palette)) }
Continuous color scales using the diverging color scales in Tableau.
See scale_colour_tableau() for Tabaleau discrete color scales,
and scale_colour_gradient_tableau() for sequential color scales.
scale_colour_gradient2_tableau( palette = "Orange-Blue Diverging", ..., na.value = "grey50", guide = "colourbar" ) scale_fill_gradient2_tableau( palette = "Orange-Blue Diverging", ..., na.value = "grey50", guide = "colourbar" ) scale_color_gradient2_tableau( palette = "Orange-Blue Diverging", ..., na.value = "grey50", guide = "colourbar" )scale_colour_gradient2_tableau( palette = "Orange-Blue Diverging", ..., na.value = "grey50", guide = "colourbar" ) scale_fill_gradient2_tableau( palette = "Orange-Blue Diverging", ..., na.value = "grey50", guide = "colourbar" ) scale_color_gradient2_tableau( palette = "Orange-Blue Diverging", ..., na.value = "grey50", guide = "colourbar" )
palette |
Palette name.
|
... |
Arguments passed to |
na.value |
Colour to use for missing values |
guide |
Type of legend. Use |
Other colour tableau:
scale_colour_gradient_tableau(),
scale_colour_tableau(),
tableau_color_pal(),
tableau_gradient_pal()
library("ggplot2") df <- data.frame( x = runif(100), y = runif(100), z1 = rnorm(100), z2 = abs(rnorm(100)) ) p <- ggplot(df, aes(x, y)) + geom_point(aes(colour = z2)) palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["ordered-diverging"]] for (palette in head(names(palettes))) { print(p + scale_colour_gradient2_tableau(palette) + ggtitle(palette)) } # If you need to reverse a palette, use a transformation p + scale_colour_gradient2_tableau(trans = "reverse")library("ggplot2") df <- data.frame( x = runif(100), y = runif(100), z1 = rnorm(100), z2 = abs(rnorm(100)) ) p <- ggplot(df, aes(x, y)) + geom_point(aes(colour = z2)) palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["ordered-diverging"]] for (palette in head(names(palettes))) { print(p + scale_colour_gradient2_tableau(palette) + ggtitle(palette)) } # If you need to reverse a palette, use a transformation p + scale_colour_gradient2_tableau(trans = "reverse")
Colour and fill scales which use the palettes in
hc_pal() and are meant for use with
theme_hc().
scale_colour_hc(palette = "default", ...) scale_color_hc(palette = "default", ...) scale_fill_hc(palette = "default", ...)scale_colour_hc(palette = "default", ...) scale_color_hc(palette = "default", ...) scale_fill_hc(palette = "default", ...)
palette |
|
... |
Arguments passed on to
|
Other colour hc:
hc_pal()
See ptol_pal(). These palettes support up to 12 values.
scale_colour_ptol(...) scale_color_ptol(...) scale_fill_ptol(...)scale_colour_ptol(...) scale_color_ptol(...) scale_fill_ptol(...)
... |
Arguments passed on to
|
Other colour ptol:
ptol_pal()
library("ggplot2") p2 <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(gear))) + geom_point() + geom_smooth(method = "lm", se = FALSE) + scale_color_ptol("cyl") + theme_minimal() + ggtitle("Cars") ggplot(diamonds, aes(x = clarity, fill = cut)) + geom_bar() + scale_fill_ptol() + theme_minimal()library("ggplot2") p2 <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(gear))) + geom_point() + geom_smooth(method = "lm", se = FALSE) + scale_color_ptol("cyl") + theme_minimal() + ggtitle("Cars") ggplot(diamonds, aes(x = clarity, fill = cut)) + geom_bar() + scale_fill_ptol() + theme_minimal()
See stata_pal() for details.
scale_colour_stata(scheme = "s2color", ...) scale_fill_stata(scheme = "s2color", ...) scale_color_stata(scheme = "s2color", ...)scale_colour_stata(scheme = "s2color", ...) scale_fill_stata(scheme = "s2color", ...) scale_color_stata(scheme = "s2color", ...)
scheme |
|
... |
Arguments passed on to
|
Categorical (qualitative) color scales used in Tableau.
Use the function scale_colour_gradient_tableau() for the sequential
and scale_colour_gradient2_tableau() for the diverging continuous
color scales from Tableu.
scale_colour_tableau( palette = "Tableau 10", type = "regular", direction = 1, ... ) scale_fill_tableau( palette = "Tableau 10", type = "regular", direction = 1, ... ) scale_color_tableau( palette = "Tableau 10", type = "regular", direction = 1, ... )scale_colour_tableau( palette = "Tableau 10", type = "regular", direction = 1, ... ) scale_fill_tableau( palette = "Tableau 10", type = "regular", direction = 1, ... ) scale_color_tableau( palette = "Tableau 10", type = "regular", direction = 1, ... )
palette |
Palette name. See |
type |
Palette type. One of |
direction |
If 1, the default, then use the original order of colors. If -1, then reverse the order. |
... |
Other arguments passed on to |
tableau_color_pal() for references.
Other colour tableau:
scale_colour_gradient2_tableau(),
scale_colour_gradient_tableau(),
tableau_color_pal(),
tableau_gradient_pal()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + theme_igray() palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["regular"]] for (palette in head(names(palettes), 3L)) { print(p + scale_colour_tableau(palette) + ggtitle(palette)) } # the order of colour can be reversed p + scale_color_tableau(direction = -1)library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + theme_igray() palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["regular"]] for (palette in head(names(palettes), 3L)) { print(p + scale_colour_tableau(palette) + ggtitle(palette)) } # the order of colour can be reversed p + scale_color_tableau(direction = -1)
Colour and fill scales which use the palettes in wsj_pal().
These scales should be used with theme_wsj().
scale_colour_wsj(palette = "colors6", ...) scale_color_wsj(palette = "colors6", ...) scale_fill_wsj(palette = "colors6", ...)scale_colour_wsj(palette = "colors6", ...) scale_color_wsj(palette = "colors6", ...) scale_fill_wsj(palette = "colors6", ...)
palette |
|
... |
Arguments passed on to
|
Other colour wsj:
wsj_pal()
Color scales from LibreOffice Calc.
scale_fill_calc(...) scale_colour_calc(...) scale_color_calc(...)scale_fill_calc(...) scale_colour_calc(...) scale_color_calc(...)
... |
Arguments passed on to
|
See theme_calc() for examples.
Other colour calc:
calc_pal()
The classic "ugly" color scales from Excel 97.
scale_fill_excel(...) scale_colour_excel(...) scale_color_excel(...)scale_fill_excel(...) scale_colour_excel(...) scale_color_excel(...)
... |
Arguments passed on to
|
Other colour excel:
excel_new_pal(),
excel_pal(),
scale_colour_excel_new()
library("ggplot2") # Line and scatter plot colors p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel() + scale_colour_excel() # Bar plot (area/fill) colors ggplot(mpg, aes(x = class, fill = drv)) + geom_bar() + scale_fill_excel() + theme_excel()library("ggplot2") # Line and scatter plot colors p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel() + scale_colour_excel() # Bar plot (area/fill) colors ggplot(mpg, aes(x = class, fill = drv)) + geom_bar() + scale_fill_excel() + theme_excel()
Color scales from Google Docs.
scale_fill_gdocs(...) scale_colour_gdocs(...) scale_color_gdocs(...)scale_fill_gdocs(...) scale_colour_gdocs(...) scale_color_gdocs(...)
... |
Arguments passed on to
|
See theme_gdocs() for examples.
Other colour gdocs:
gdocs_pal()
See solarized_pal() for details.
scale_fill_solarized(accent = "blue", ...) scale_colour_solarized(accent = "blue", ...) scale_color_solarized(accent = "blue", ...)scale_fill_solarized(accent = "blue", ...) scale_colour_solarized(accent = "blue", ...) scale_color_solarized(accent = "blue", ...)
accent |
|
... |
Arguments passed on to
|
Other solarized colour:
solarized_pal()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_solarized() + scale_colour_solarized()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_solarized() + scale_colour_solarized()
See stata_linetype_pal() for details.
scale_linetype_stata(...)scale_linetype_stata(...)
... |
Arguments passed on to
|
Other linetype stata:
stata_linetype_pal()
require("ggplot2") if (require("tidyr") && require("dplyr")) { rescale01 <- function(x) { (x - min(x)) / diff(range(x)) } gather(economics, variable, value, -date) %>% group_by(variable) %>% mutate(value = rescale01(value)) %>% ggplot(aes(x = date, y = value, linetype = variable)) + geom_line() + scale_linetype_stata() }require("ggplot2") if (require("tidyr") && require("dplyr")) { rescale01 <- function(x) { (x - min(x)) / diff(range(x)) } gather(economics, variable, value, -date) %>% group_by(variable) %>% mutate(value = rescale01(value)) %>% ggplot(aes(x = date, y = value, linetype = variable)) + geom_line() + scale_linetype_stata() }
See calc_shape_pal() for details.
scale_shape_calc(...)scale_shape_calc(...)
... |
Arguments passed on to
|
theme_calc() for examples.
Other shapes calc:
calc_shape_pal()
'r lifecycle::badge("deprecated")'
scale_shape_circlefill(...)scale_shape_circlefill(...)
... |
Arguments passed on to
|
circlefill_shape_pal() for a description of the palette.
Other shapes:
circlefill_shape_pal(),
cleveland_shape_pal(),
scale_shape_cleveland(),
scale_shape_tremmel(),
tremmel_shape_pal()
Shape scales from Cleveland "Elements of Graphing Data"
scale_shape_cleveland(overlap = TRUE, ...)scale_shape_cleveland(overlap = TRUE, ...)
overlap |
|
... |
Arguments passed on to
|
Cleveland WS. The Elements of Graphing Data. Revised Edition. Hobart Press, Summit, NJ, 1994, pp. 154-164, 234-239.
cleveland_shape_pal() for a description of the palette.
Other shapes:
circlefill_shape_pal(),
cleveland_shape_pal(),
scale_shape_circlefill(),
scale_shape_tremmel(),
tremmel_shape_pal()
scale_shape_few() maps discrete variables to up to five easily
discernible shapes. It is based on the shape palette suggested in
Few (2012).
scale_shape_few(...)scale_shape_few(...)
... |
Common |
Few, S. (2012) Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, p. 208.
scale_shape_few() for the shape palette that this
scale uses.
See stata_shape_pal() for details.
scale_shape_stata(...)scale_shape_stata(...)
... |
Arguments passed on to
|
## Not run: library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) p + theme_stata() + scale_shape_stata() ## End(Not run)## Not run: library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) p + theme_stata() + scale_shape_stata() ## End(Not run)
See tableau_shape_pal() for details.
scale_shape_tableau(palette = "default", ...)scale_shape_tableau(palette = "default", ...)
palette |
Palette name. |
... |
Arguments passed on to
|
Other shape tableau:
tableau_shape_pal()
## Not run: library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) p + scale_shape_tableau() ## End(Not run)## Not run: library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) p + scale_shape_tableau() ## End(Not run)
Shape scales from Tremmel (1995)
scale_shape_tremmel(overlap = FALSE, alt = TRUE, ...)scale_shape_tremmel(overlap = FALSE, alt = TRUE, ...)
overlap |
use an empty circle instead of a solid circle when
|
alt |
If |
... |
Arguments passed on to
|
tremmel_shape_pal() for a description of the palette.
Other shapes:
circlefill_shape_pal(),
cleveland_shape_pal(),
scale_shape_circlefill(),
scale_shape_cleveland(),
tremmel_shape_pal()
library("ggplot2") p <- ggplot(mtcars, aes(x = mpg, y = hp, shape = factor(cyl))) + geom_point() p + scale_shape_tremmel() p + scale_shape_tremmel(alt = TRUE) p + scale_shape_tremmel(overlap = TRUE)library("ggplot2") p <- ggplot(mtcars, aes(x = mpg, y = hp, shape = factor(cyl))) + geom_point() p + scale_shape_tremmel() p + scale_shape_tremmel(alt = TRUE) p + scale_shape_tremmel(overlap = TRUE)
A quick and dirty way to show linetypes.
show_linetypes(linetypes, labels = TRUE)show_linetypes(linetypes, labels = TRUE)
linetypes |
A character vector of linetypes. See
|
labels |
Label each line with its linetype (lty) value. |
This function called for the side effect of creating a plot.
It returns linetypes.
show_col(), show_linetypes()
library("scales") show_linetypes(linetype_pal()(3)) show_linetypes(linetype_pal()(3), labels = TRUE)library("scales") show_linetypes(linetype_pal()(3)) show_linetypes(linetype_pal()(3), labels = TRUE)
A quick and dirty way to show shapes.
show_shapes(shapes, labels = TRUE)show_shapes(shapes, labels = TRUE)
shapes |
A numeric or character vector of shapes. See
|
labels |
Include the plotting character value of the symbol. |
This function called for the side effect of creating a plot.
It returns shapes.
show_col(), show_linetypes()
library("scales") show_shapes(shape_pal()(5)) show_shapes(shape_pal()(3), labels = TRUE)library("scales") show_shapes(shape_pal()(5)) show_shapes(shape_pal()(3), labels = TRUE)
Format numbers with automatic number of digits
smart_digits(x, ...) smart_digits_format(x, ...)smart_digits(x, ...) smart_digits_format(x, ...)
x |
A numeric vector to format |
... |
Parameters passed to |
A character vector.
smart_digits_format() returns a function with a single argument
x, a numeric vector, that returns a character vector.
Josh O'Brien, Baptise Auguie, Jeffrey B. Arnold
Josh O'Brien, https://stackoverflow.com/questions/23169938/select-accuracy-to-display-additional-axis-breaks/23171858#23171858.
Qualitative color palate based on the Ethan Schoonover's Solarized palette, https://ethanschoonover.com/solarized/. This palette supports up to seven values.
solarized_pal(accent = "blue")solarized_pal(accent = "blue")
accent |
|
For a given starting color and number of colors in the palette, the other colors are the combination of colors that maximizes the total Euclidean distance between colors in L*a*b space.
Other solarized colour:
scale_fill_solarized()
library("scales") show_col(solarized_pal()(2)) show_col(solarized_pal()(3)) show_col(solarized_pal("red")(4))library("scales") show_col(solarized_pal()(2)) show_col(solarized_pal()(3)) show_col(solarized_pal("red")(4))
The five number summary of a sample is the minimum, first quartile, median, third quartile, and maximum.
stat_fivenumber( mapping = NULL, data = NULL, geom = "boxplot", probs = c(0, 0.25, 0.5, 0.75, 1), na.rm = FALSE, position = "identity", show.legend = NA, inherit.aes = TRUE, ... )stat_fivenumber( mapping = NULL, data = NULL, geom = "boxplot", probs = c(0, 0.25, 0.5, 0.75, 1), na.rm = FALSE, position = "identity", show.legend = NA, inherit.aes = TRUE, ... )
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
geom |
The geometric object to use to display the data, either as a
|
probs |
Quantiles to use for the five number summary. |
na.rm |
If |
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
... |
Other arguments passed on to |
A data frame with additional columns:
width |
width of boxplot |
min |
minimum |
lower |
lower hinge, 25% quantile |
middle |
median, 50% quantile |
upper |
upper hinge, 75% quantile |
max |
maximum |
Linetype palette based on the linepattern scheme in Stata. This palette supports up to 15 values.
stata_linetype_pal()stata_linetype_pal()
Other linetype stata:
scale_linetype_stata()
Stata color palettes. See Stata documentation for a description of the schemes, https://www.stata.com/help.cgi?schemes.
stata_pal(scheme = "s2color")stata_pal(scheme = "s2color")
scheme |
|
All these palettes support up to 15 values.
library("scales") show_col(stata_pal("s2color")(15)) show_col(stata_pal("s1rcolor")(15)) show_col(stata_pal("s1color")(15)) show_col(stata_pal("mono")(15))library("scales") show_col(stata_pal("s2color")(15)) show_col(stata_pal("s1rcolor")(15)) show_col(stata_pal("s1color")(15)) show_col(stata_pal("mono")(15))
Shape palette based on the symbol palette in Stata used in scheme s2mono. This palette supports up to 10 values.
stata_shape_pal()stata_shape_pal()
See scale_shape_stata() for examples.
Color palettes used in Tableau.
tableau_color_pal( palette = "Tableau 10", type = c("regular", "ordered-sequential", "ordered-diverging"), direction = 1 )tableau_color_pal( palette = "Tableau 10", type = c("regular", "ordered-sequential", "ordered-diverging"), direction = 1 )
palette |
Palette name. See Details for available palettes. |
type |
Type of palette. One of |
direction |
If 1, the default, then use the original order of colors. If -1, then reverse the order. |
Tableau provides three types of color palettes:
"regular" (discrete, qualitative categories),
"ordered-sequential", and "ordered-diverging".
"regular""Tableau 10", "Tableau 20", "Color Blind", "Seattle Grays", "Traffic", "Miller Stone", "Superfishel Stone", "Nuriel Stone", "Jewel Bright", "Summer", "Winter", "Green-Orange-Teal", "Red-Blue-Brown", "Purple-Pink-Gray", "Hue Circle", "Classic 10", "Classic 10 Medium", "Classic 10 Light", "Classic 20", "Classic Gray 5", "Classic Color Blind", "Classic Traffic Light", "Classic Purple-Gray 6", "Classic Purple-Gray 12", "Classic Green-Orange 6", "Classic Green-Orange 12", "Classic Blue-Red 6", "Classic Blue-Red 12", "Classic Cyclic"
"ordered-diverging""Orange-Blue Diverging", "Red-Green Diverging", "Green-Blue Diverging", "Red-Blue Diverging", "Red-Black Diverging", "Gold-Purple Diverging", "Red-Green-Gold Diverging", "Sunset-Sunrise Diverging", "Orange-Blue-White Diverging", "Red-Green-White Diverging", "Green-Blue-White Diverging", "Red-Blue-White Diverging", "Red-Black-White Diverging", "Orange-Blue Light Diverging", "Temperature Diverging", "Classic Red-Green", "Classic Red-Blue", "Classic Red-Black", "Classic Area Red-Green", "Classic Orange-Blue", "Classic Green-Blue", "Classic Red-White-Green", "Classic Red-White-Black", "Classic Orange-White-Blue", "Classic Red-White-Black Light", "Classic Orange-White-Blue Light", "Classic Red-White-Green Light", "Classic Red-Green Light"
"ordered-sequential""Blue-Green Sequential", "Blue Light", "Orange Light", "Blue", "Orange", "Green", "Red", "Purple", "Brown", "Gray", "Gray Warm", "Blue-Teal", "Orange-Gold", "Green-Gold", "Red-Gold", "Classic Green", "Classic Gray", "Classic Blue", "Classic Red", "Classic Orange", "Classic Area Red", "Classic Area Green", "Classic Area-Brown"
http://vis.stanford.edu/color-names/analyzer/
Maureen Stone, 'Designing Colors for Data' (slides), at the International Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging, Banff, AB, Canada, June 22, 2007.
Heer, Jeffrey and Maureen Stone, 2012 'Color Naming Models for Color Selection, Image Editing and Palette Design', ACM Human Factors in Computing Systems (CHI) http://vis.stanford.edu/files/2012-ColorNameModels-CHI.pdf.
Other colour tableau:
scale_colour_gradient2_tableau(),
scale_colour_gradient_tableau(),
scale_colour_tableau(),
tableau_gradient_pal()
library("scales") palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["regular"]] for (palname in names(palettes)) { pal <- tableau_color_pal(palname) max_n <- attr(pal, "max_n") show_col(pal(max_n)) title(main = palname) }library("scales") palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["regular"]] for (palname in names(palettes)) { pal <- tableau_color_pal(palname) max_n <- attr(pal, "max_n") show_col(pal(max_n)) title(main = palname) }
Gradient color palettes using the diverging and sequential continous color
palettes in Tableau. See tableau_color_pal() for discrete color
palettes.
tableau_gradient_pal(palette = "Blue", type = "ordered-sequential") tableau_seq_gradient_pal(palette = "Blue", ...) tableau_div_gradient_pal(palette = "Orange-Blue Diverging", ...)tableau_gradient_pal(palette = "Blue", type = "ordered-sequential") tableau_seq_gradient_pal(palette = "Blue", ...) tableau_div_gradient_pal(palette = "Orange-Blue Diverging", ...)
palette |
Palette name.
|
type |
Palette type, either |
... |
Arguments passed to |
Other colour tableau:
scale_colour_gradient2_tableau(),
scale_colour_gradient_tableau(),
scale_colour_tableau(),
tableau_color_pal()
library("scales") x <- seq(0, 1, length = 25) r <- sqrt(outer(x^2, x^2, "+")) palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["ordered-sequential"]] for (palname in names(palettes)) { col <- tableau_seq_gradient_pal(palname)(seq(0, 1, length = 12)) image(r, col = col) title(main = palname) }library("scales") x <- seq(0, 1, length = 25) r <- sqrt(outer(x^2, x^2, "+")) palettes <- ggthemes_data[["tableau"]][["color-palettes"]][["ordered-sequential"]] for (palname in names(palettes)) { col <- tableau_seq_gradient_pal(palname)(seq(0, 1, length = 12)) image(r, col = col) title(main = palname) }
Shape palettes used by Tableau.
tableau_shape_pal(palette = c("default", "filled", "proportions"))tableau_shape_pal(palette = c("default", "filled", "proportions"))
palette |
Palette name. |
Not all shape palettes in Tableau are supported. Additionally, these palettes are not exact, and use the best unicode character for the shape palette.
Since these palettes use unicode characters, their look may depend on the font being used, and not all characters may be available.
Shape palettes in Tableau are used to expose images for use a markers in charts, and thus are sometimes groupings of closely related symbols.
Other shape tableau:
scale_shape_tableau()
## Not run: # need to set a font containing these values show_shapes(tableau_shape_pal()(5)) ## End(Not run)## Not run: # need to set a font containing these values show_shapes(tableau_shape_pal()(5)) ## End(Not run)
Theme similar to the default settings of the ‘base’ R graphics.
theme_base(base_size = 16, base_family = "")theme_base(base_size = 16, base_family = "")
base_size |
base font size, given in pts. |
base_family |
base font family |
Other themes:
theme_clean(),
theme_foundation(),
theme_igray(),
theme_par(),
theme_solid()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes( x = wt, y = mpg, colour = factor(gear) )) + facet_wrap(~am) p + theme_base() # Change values of par par(fg = "blue", bg = "gray", col.lab = "red", font.lab = 3) p + theme_base()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes( x = wt, y = mpg, colour = factor(gear) )) + facet_wrap(~am) p + theme_base() # Change values of par par(fg = "blue", bg = "gray", col.lab = "red", font.lab = 3) p + theme_base()
Theme similar to the default settings of LibreOffice Calc charts.
theme_calc(base_size = 10, base_family = "sans")theme_calc(base_size = 10, base_family = "sans")
base_size |
base font size, given in pts. |
base_family |
base font family |
library("ggplot2") ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + theme_calc() + scale_color_calc() ## Not run: ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) + theme_calc() + scale_shape_calc() ## End(Not run)library("ggplot2") ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + theme_calc() + scale_color_calc() ## Not run: ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + facet_wrap(~am) + theme_calc() + scale_shape_calc() ## End(Not run)
Clean ggplot theme with no panel background, black axis lines and grey fill colour for chart elements.
theme_clean(base_size = 12, base_family = "sans")theme_clean(base_size = 12, base_family = "sans")
base_size |
Base font size. |
base_family |
Base font family. |
Konrad Zdeb [email protected]
Other themes:
theme_base(),
theme_foundation(),
theme_igray(),
theme_par(),
theme_solid()
library("ggplot2") p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(gear))) + geom_point() + facet_wrap(~am) + geom_smooth(method = "lm", se = FALSE) + theme_clean() plibrary("ggplot2") p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(gear))) + geom_point() + facet_wrap(~am) + geom_smooth(method = "lm", se = FALSE) + theme_clean() p
A theme that approximates the style of The Economist.
theme_economist( base_size = 10, base_family = "sans", horizontal = TRUE, dkpanel = FALSE ) theme_economist_white( base_size = 11, base_family = "sans", gray_bg = TRUE, horizontal = TRUE )theme_economist( base_size = 10, base_family = "sans", horizontal = TRUE, dkpanel = FALSE ) theme_economist_white( base_size = 11, base_family = "sans", gray_bg = TRUE, horizontal = TRUE )
base_size |
base font size, given in pts. |
base_family |
base font family |
horizontal |
|
dkpanel |
|
gray_bg |
|
theme_economist implements the standard bluish-gray
background theme in the print The Economist and
economist.com.
theme_economist_white implements a variant with a while
panel and light gray (or white) background often used by The Economist
blog Graphic Detail.
Use scale_color_economist() with this theme.
The x axis should be displayed on the right hand side.
The Economist uses "ITC Officina Sans" as its font for graphs. If you have access to this font, you can use it with the extrafont package. "Verdana" is a good substitute.
An object of class theme().
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + # Economist puts x-axis labels on the right-hand side scale_y_continuous(position = "right") ## Standard p + theme_economist() + scale_colour_economist() # Change axis lines to vertical p + theme_economist(horizontal = FALSE) + scale_colour_economist() + coord_flip() ## White panel/light gray background p + theme_economist_white() + scale_colour_economist() ## All white variant p + theme_economist_white(gray_bg = FALSE) + scale_colour_economist() ## Not run: ## The Economist uses ITC Officina Sans library("extrafont") p + theme_economist(base_family="ITC Officina Sans") + scale_colour_economist() ## Verdana is a widely available substitute p + theme_economist(base_family="Verdana") + scale_colour_economist() ## End(Not run)library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + # Economist puts x-axis labels on the right-hand side scale_y_continuous(position = "right") ## Standard p + theme_economist() + scale_colour_economist() # Change axis lines to vertical p + theme_economist(horizontal = FALSE) + scale_colour_economist() + coord_flip() ## White panel/light gray background p + theme_economist_white() + scale_colour_economist() ## All white variant p + theme_economist_white(gray_bg = FALSE) + scale_colour_economist() ## Not run: ## The Economist uses ITC Officina Sans library("extrafont") p + theme_economist(base_family="ITC Officina Sans") + scale_colour_economist() ## Verdana is a widely available substitute p + theme_economist(base_family="Verdana") + scale_colour_economist() ## End(Not run)
Theme to replicate the ugly monstrosity that was the old
gray-background Excel chart. Please never use this.
This theme should be combined with the scale_colour_excel()
color scale.
theme_excel(base_size = 12, base_family = "", horizontal = TRUE)theme_excel(base_size = 12, base_family = "", horizontal = TRUE)
base_size |
base font size, given in pts. |
base_family |
base font family |
horizontal |
|
An object of class theme().
Other themes excel:
theme_excel_new()
library("ggplot2") # Line and scatter plot colors p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel() + scale_colour_excel() # Bar plot (area/fill) colors ggplot(mpg, aes(x = class, fill = drv)) + geom_bar() + scale_fill_excel() + theme_excel()library("ggplot2") # Line and scatter plot colors p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel() + scale_colour_excel() # Bar plot (area/fill) colors ggplot(mpg, aes(x = class, fill = drv)) + geom_bar() + scale_fill_excel() + theme_excel()
Theme for ggplot2 that is similar to the default style of charts in current versions of Microsoft Excel.
theme_excel_new(base_size = 9, base_family = "sans")theme_excel_new(base_size = 9, base_family = "sans")
base_size |
base font size, given in pts. |
base_family |
base font family |
An object of class theme().
Other themes excel:
theme_excel()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel_new() + scale_colour_excel_new()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_excel_new() + scale_colour_excel_new()
Theme based on the rules and examples from Stephen Few's Show Me the Numbers and "Practical Rules for Using Color in Charts".
theme_few(base_size = 12, base_family = "")theme_few(base_size = 12, base_family = "")
base_size |
base font size, given in pts. |
base_family |
base font family |
Few, S. (2012) Show Me the Numbers: Designing Tables and Graphs to Enlighten. 2nd edition. Analytics Press.
Stephen Few, "Practical Rules for Using Color in Charts", https://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf.
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_few() + scale_colour_few() p + theme_few() + scale_colour_few("Light") p + theme_few() + scale_colour_few("Dark") ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + theme_few() + scale_shape_few()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_few() + scale_colour_few() p + theme_few() + scale_colour_few("Light") p + theme_few() + scale_colour_few("Dark") ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, shape = factor(gear))) + theme_few() + scale_shape_few()
Theme inspired by the plots from FiveThirtyEight.com.
theme_fivethirtyeight(base_size = 12, base_family = "sans")theme_fivethirtyeight(base_size = 12, base_family = "sans")
base_size |
base font size, given in pts. |
base_family |
base font family |
library("ggplot2") p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(gear))) + geom_point() + facet_wrap(~am) + geom_smooth(method = "lm", se = FALSE) + scale_color_fivethirtyeight() + theme_fivethirtyeight() plibrary("ggplot2") p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = factor(gear))) + geom_point() + facet_wrap(~am) + geom_smooth(method = "lm", se = FALSE) + scale_color_fivethirtyeight() + theme_fivethirtyeight() p
This theme is designed to be a foundation from which to build new
themes, and not meant to be used directly. theme_foundation()
is a complete theme with only minimal number of elements defined.
It is easier to create new themes by extending this one rather
than theme_gray() or theme_bw(),
because those themes define elements deep in the hierarchy.
theme_foundation(base_size = 12, base_family = "")theme_foundation(base_size = 12, base_family = "")
base_size |
base font size, given in pts. |
base_family |
base font family |
This theme takes theme_gray() and sets all
colour and fill values to NULL, except for the top-level
elements (line, rect, and title), which have
colour = "black", and fill = "white". This leaves the spacing
and-non colour defaults of the default ggplot2 themes in place.
Other themes:
theme_base(),
theme_clean(),
theme_igray(),
theme_par(),
theme_solid()
Theme similar to the default look of charts in Google Docs.
theme_gdocs(base_size = 12, base_family = "sans")theme_gdocs(base_size = 12, base_family = "sans")
base_size |
base font size, given in pts. |
base_family |
base font family |
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_gdocs() + scale_color_gdocs()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_gdocs() + scale_color_gdocs()
Theme based on Highcharts plots.
theme_hc( base_size = 12, base_family = "sans", style = c("default", "darkunica"), bgcolor = NULL )theme_hc( base_size = 12, base_family = "sans", style = c("default", "darkunica"), bgcolor = NULL )
base_size |
base font size, given in pts. |
base_family |
base font family |
style |
The Highcharts theme to use |
bgcolor |
Deprecated |
https://www.highcharts.com/demo/highcharts/line-chart
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes( x = wt, y = mpg, colour = factor(gear) )) + facet_wrap(~am) p + theme_hc() + scale_colour_hc() p + theme_hc(bgcolor = "darkunica") + scale_colour_hc("darkunica") dtemp <- data.frame( months = factor(rep(substr(month.name, 1, 3), 4), levels = substr(month.name, 1, 3) ), city = rep(c("Tokyo", "New York", "Berlin", "London"), each = 12 ), temp = c( 7.0, 6.9, 9.5, 14.5, 18.2, 21.5, 25.2, 26.5, 23.3, 18.3, 13.9, 9.6, -0.2, 0.8, 5.7, 11.3, 17.0, 22.0, 24.8, 24.1, 20.1, 14.1, 8.6, 2.5, -0.9, 0.6, 3.5, 8.4, 13.5, 17.0, 18.6, 17.9, 14.3, 9.0, 3.9, 1.0, 3.9, 4.2, 5.7, 8.5, 11.9, 15.2, 17.0, 16.6, 14.2, 10.3, 6.6, 4.8 ) ) ggplot(dtemp, aes(x = months, y = temp, group = city, color = city)) + geom_line() + geom_point(size = 1.1) + ggtitle("Monthly Average Temperature") + theme_hc() + scale_colour_hc() ggplot(dtemp, aes(x = months, y = temp, group = city, color = city)) + geom_line() + geom_point(size = 1.1) + ggtitle("Monthly Average Temperature") + theme_hc(bgcolor = "darkunica") + scale_fill_hc("darkunica")library("ggplot2") p <- ggplot(mtcars) + geom_point(aes( x = wt, y = mpg, colour = factor(gear) )) + facet_wrap(~am) p + theme_hc() + scale_colour_hc() p + theme_hc(bgcolor = "darkunica") + scale_colour_hc("darkunica") dtemp <- data.frame( months = factor(rep(substr(month.name, 1, 3), 4), levels = substr(month.name, 1, 3) ), city = rep(c("Tokyo", "New York", "Berlin", "London"), each = 12 ), temp = c( 7.0, 6.9, 9.5, 14.5, 18.2, 21.5, 25.2, 26.5, 23.3, 18.3, 13.9, 9.6, -0.2, 0.8, 5.7, 11.3, 17.0, 22.0, 24.8, 24.1, 20.1, 14.1, 8.6, 2.5, -0.9, 0.6, 3.5, 8.4, 13.5, 17.0, 18.6, 17.9, 14.3, 9.0, 3.9, 1.0, 3.9, 4.2, 5.7, 8.5, 11.9, 15.2, 17.0, 16.6, 14.2, 10.3, 6.6, 4.8 ) ) ggplot(dtemp, aes(x = months, y = temp, group = city, color = city)) + geom_line() + geom_point(size = 1.1) + ggtitle("Monthly Average Temperature") + theme_hc() + scale_colour_hc() ggplot(dtemp, aes(x = months, y = temp, group = city, color = city)) + geom_line() + geom_point(size = 1.1) + ggtitle("Monthly Average Temperature") + theme_hc(bgcolor = "darkunica") + scale_fill_hc("darkunica")
Theme with white panel and gray background.
theme_igray(base_size = 12, base_family = "")theme_igray(base_size = 12, base_family = "")
base_size |
base font size, given in pts. |
base_family |
base font family |
This theme inverts the colors in the theme_gray(), a
white panel and a light gray area around it. This keeps a white
background for the color scales like theme_bw(). But
by using a gray background, the plot is closer to the
typographical color of the document, which is the motivation for
using a gray panel in theme_gray(). This is
similar to the style of plots in Stata and Tableau.
theme_gray(),
theme_bw()
Other themes:
theme_base(),
theme_clean(),
theme_foundation(),
theme_par(),
theme_solid()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_igray()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_igray()
A clean theme that is good for displaying maps from
geom_map().
theme_map(base_size = 9, base_family = "")theme_map(base_size = 9, base_family = "")
base_size |
base font size, given in pts. |
base_family |
base font family |
library("maps") library("ggplot2") us <- fortify(map_data("state"), region = "region") gg <- ggplot() + geom_map( data = us, map = us, aes(x = long, y = lat, map_id = region, group = group), fill = "white", color = "black", size = 0.25 ) + coord_map("albers", lat0 = 39, lat1 = 45) + theme_map() gglibrary("maps") library("ggplot2") us <- fortify(map_data("state"), region = "region") gg <- ggplot() + geom_map( data = us, map = us, aes(x = long, y = lat, map_id = region, group = group), fill = "white", color = "black", size = 0.25 ) + coord_map("albers", lat0 = 39, lat1 = 45) + theme_map() gg
The pander ships with a default theme when the 'unify plots' option is
enabled via panderOptions, which is now also available outside of pander internals, like evals,
eval.msgs or Pandoc.brew.
theme_pander( base_size = 12, base_family = "sans", nomargin = TRUE, ff = NULL, fc = "black", fs = NULL, gM = TRUE, gm = TRUE, gc = "grey", gl = "dashed", boxes = FALSE, bc = "white", pc = "transparent", lp = "right", axis = 1 )theme_pander( base_size = 12, base_family = "sans", nomargin = TRUE, ff = NULL, fc = "black", fs = NULL, gM = TRUE, gm = TRUE, gc = "grey", gl = "dashed", boxes = FALSE, bc = "white", pc = "transparent", lp = "right", axis = 1 )
base_size |
base font size, given in pts. |
base_family |
base font family |
nomargin |
suppress the white space around the plot (boolean) |
ff |
font family, like |
fc |
font color (name or hexa code) |
fs |
font size (integer). Deprecated: use |
gM |
major grid (boolean) |
gm |
minor grid (boolean) |
gc |
grid color (name or hexa code) |
gl |
grid line type ( |
boxes |
to render a border around the plot or not |
bc |
background color (name or hexa code) |
pc |
panel background color (name or hexa code) |
lp |
legend position |
axis |
axis angle as defined in |
require("ggplot2") if (require("pander")) { p <- ggplot(mtcars, aes(x = mpg, y = wt)) + geom_point() p + theme_pander() panderOptions("graph.grid.color", "red") p + theme_pander() p <- ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) + geom_point() p + theme_pander() + scale_color_pander() ggplot(mpg, aes(x = class, fill = drv)) + geom_bar() + scale_fill_pander() + theme_pander() }require("ggplot2") if (require("pander")) { p <- ggplot(mtcars, aes(x = mpg, y = wt)) + geom_point() p + theme_pander() panderOptions("graph.grid.color", "red") p + theme_pander() p <- ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) + geom_point() p + theme_pander() + scale_color_pander() ggplot(mpg, aes(x = class, fill = drv)) + geom_bar() + scale_fill_pander() + theme_pander() }
par().
Not all par() parameters, are supported, and not all are relevant to
ggplot2 themes.Currently this theme uses the values of the parameters:
"code", ""ps"", "code" "family", "fg",
"bg", "adj", "font", "cex.axis",
"cex.lab", "cex.main", "cex.sub", "col.axis",
"col.lab", "col.main", "col.sub", "font",
"font.axis", "font.lab", "font.main",
"font.sub", "las", "lend",
"lheight", "lty", "mar", "ps", "tcl",
"tck", "xaxt", "yaxt".
theme_par(base_size = par()$ps, base_family = par()$family)theme_par(base_size = par()$ps, base_family = par()$family)
base_size |
base font size, given in pts. |
base_family |
base font family |
This theme does not translate the base graphics perfectly, so the graphs produced by it will not be identical to those produced by base graphics, most notably in the spacing of the margins.
Other themes:
theme_base(),
theme_clean(),
theme_foundation(),
theme_igray(),
theme_solid()
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_par() # theme changes with respect to values of par par(font = 2, col.lab = "red", fg = "white", bg = "black") p + theme_par()library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) p + theme_par() # theme changes with respect to values of par par(font = 2, col.lab = "red", fg = "white", bg = "black") p + theme_par()
See https://ethanschoonover.com/solarized/ for a description of the Solarized palette.
theme_solarized(base_size = 12, base_family = "", light = TRUE) theme_solarized_2(base_size = 12, base_family = "", light = TRUE)theme_solarized(base_size = 12, base_family = "", light = TRUE) theme_solarized_2(base_size = 12, base_family = "", light = TRUE)
base_size |
base font size, given in pts. |
base_family |
base font family |
light |
|
Plots made with this theme integrate seamlessly with the Solarized
Beamer color theme.
https://github.com/jrnold/beamercolorthemesolarized.
There are two variations: theme_solarized is similar to
to theme_bw(), while theme_solarized_2() is
similar to theme_gray().
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) # Light version with different main accent colors for (accent in names(ggthemes::ggthemes_data[["solarized"]][["accents"]])) { print(p + theme_solarized() + scale_colour_solarized(accent)) } # Dark version p + theme_solarized(light = FALSE) + scale_colour_solarized("blue") # Alternative theme p + theme_solarized_2(light = FALSE) + scale_colour_solarized("blue")library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) # Light version with different main accent colors for (accent in names(ggthemes::ggthemes_data[["solarized"]][["accents"]])) { print(p + theme_solarized() + scale_colour_solarized(accent)) } # Dark version p + theme_solarized(light = FALSE) + scale_colour_solarized("blue") # Alternative theme p + theme_solarized_2(light = FALSE) + scale_colour_solarized("blue")
Theme that removes all non-geom elements (lines, text, etc), This theme is when only the geometric objects are desired.
theme_solid(base_size = 12, base_family = "", fill = NA)theme_solid(base_size = 12, base_family = "", fill = NA)
base_size |
Base font size. |
base_family |
Ignored, kept for consistency with |
fill |
Background color of the plot. |
Other themes:
theme_base(),
theme_clean(),
theme_foundation(),
theme_igray(),
theme_par()
library("ggplot2") ggplot(mtcars, aes(wt, mpg)) + geom_point() + theme_solid(fill = "white") ggplot(mtcars, aes(wt, mpg)) + geom_point(color = "white") + theme_solid(fill = "black")library("ggplot2") ggplot(mtcars, aes(wt, mpg)) + geom_point() + theme_solid(fill = "white") ggplot(mtcars, aes(wt, mpg)) + geom_point(color = "white") + theme_solid(fill = "black")
Themes based on Stata graph schemes
theme_stata(base_size = 11, base_family = "sans", scheme = "s2color")theme_stata(base_size = 11, base_family = "sans", scheme = "s2color")
base_size |
base font size, given in pts. |
base_family |
base font family |
scheme |
One of "s2color", "s2mono", "s1color", "s1rcolor", or "s1mono", "s2manual", "s1manual", or "sj" |
These themes approximate Stata schemes using the features ggplot2. The graphical models of Stata and ggplot2 differ in various ways that make an exact replication impossible (or more difficult than it is worth). Some features in Stata schemes not in ggplot2: defaults for specific graph types, different levels of titles, captions and notes. These themes also adopt some of the ggplot2 defaults, and more effort was made to match the colors and sizes of major elements than in matching the margins.
https://www.stata.com/help.cgi?schemes
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + labs( title = "Graphs by car type", x = "Weight (lbs.)", y = "MPG" ) # s2color p + theme_stata() + scale_colour_stata("s2color") # s2mono p + theme_stata(scheme = "s2mono") + scale_colour_stata("mono") # s1color p + theme_stata(scheme = "s2color") + scale_colour_stata("s1color") # s1rcolor p + theme_stata(scheme = "s1rcolor") + scale_colour_stata("s1rcolor") # s1mono p + theme_stata(scheme = "s1mono") + scale_colour_stata("mono")library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + labs( title = "Graphs by car type", x = "Weight (lbs.)", y = "MPG" ) # s2color p + theme_stata() + scale_colour_stata("s2color") # s2mono p + theme_stata(scheme = "s2mono") + scale_colour_stata("mono") # s1color p + theme_stata(scheme = "s2color") + scale_colour_stata("s1color") # s1rcolor p + theme_stata(scheme = "s1rcolor") + scale_colour_stata("s1rcolor") # s1mono p + theme_stata(scheme = "s1mono") + scale_colour_stata("mono")
Theme based on Chapter 6 'Data-Ink Maximization and Graphical
Design' of Edward Tufte *The Visual Display of Quantitative
Information*. No border, no axis lines, no grids. This theme works
best in combination with geom_rug() or
geom_rangeframe().
theme_tufte(base_size = 11, base_family = "serif", ticks = TRUE)theme_tufte(base_size = 11, base_family = "serif", ticks = TRUE)
base_size |
base font size, given in pts. |
base_family |
base font family |
ticks |
|
The default font family is set to 'serif' as he uses serif fonts for labels in 'The Visual Display of Quantitative Information'. The serif font used by Tufte in his books is a variant of Bembo, while the sans serif font is Gill Sans. If these fonts are installed on your system, then you can use them with the package extrafont.
Tufte, Edward R. (2001) The Visual Display of Quantitative Information, Chapter 6.
library("ggplot2") p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + scale_x_continuous(breaks = extended_range_breaks()(mtcars$wt)) + scale_y_continuous(breaks = extended_range_breaks()(mtcars$mpg)) + ggtitle("Cars") p + geom_rangeframe() + coord_cartesian(clip = "off") + theme_tufte() p + geom_rug() + theme_tufte(ticks = FALSE)library("ggplot2") p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + scale_x_continuous(breaks = extended_range_breaks()(mtcars$wt)) + scale_y_continuous(breaks = extended_range_breaks()(mtcars$mpg)) + ggtitle("Cars") p + geom_rangeframe() + coord_cartesian(clip = "off") + theme_tufte() p + geom_rug() + theme_tufte(ticks = FALSE)
Theme based on the plots in The Wall Street Journal.
theme_wsj( base_size = 12, color = "brown", base_family = "sans", title_family = "mono" )theme_wsj( base_size = 12, color = "brown", base_family = "sans", title_family = "mono" )
base_size |
base font size, given in pts. |
color |
The background color of plot. One of |
base_family |
base font family |
title_family |
Plot title font family. |
This theme should be used with scale_color_wsj().
https://twitter.com/WSJGraphics
https://pinterest.com/wsjgraphics/wsj-graphics/
library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + ggtitle("Diamond Prices") p + scale_colour_wsj("colors6", "") + theme_wsj() # Use a gray background instead p + scale_colour_wsj("colors6", "") + theme_wsj(color = "gray")library("ggplot2") p <- ggplot(mtcars) + geom_point(aes(x = wt, y = mpg, colour = factor(gear))) + facet_wrap(~am) + ggtitle("Diamond Prices") p + scale_colour_wsj("colors6", "") + theme_wsj() # Use a gray background instead p + scale_colour_wsj("colors6", "") + theme_wsj(color = "gray")
Based on experiments Tremmel (1995) suggests the following shape palettes:
tremmel_shape_pal(overlap = FALSE, alt = FALSE)tremmel_shape_pal(overlap = FALSE, alt = FALSE)
overlap |
use an empty circle instead of a solid circle when
|
alt |
If |
If two symbols, then use a solid circle and plus sign.
If three symbols, then use a solid circle, empty circle, and an empty triangle. However, that set of symbols does not satisfy the requirement that each symbol should differ from the other symbols in the same feature dimension. A set of three symbols that satisfies this is a circle (curvature), plus sign (number of terminators), triangle (line orientation).
This palette supports up to three values. If more than three groups of data, then separate the groups into different plots.
Tremmel, Lothar, (1995) "The Visual Separability of Plotting Symbols in Scatterplots" Journal of Computational and Graphical Statistics, https://www.jstor.org/stable/1390760
Other shapes:
circlefill_shape_pal(),
cleveland_shape_pal(),
scale_shape_circlefill(),
scale_shape_cleveland(),
scale_shape_tremmel()
The Wall Street Journal uses many different color palettes in its plots. This collects a few of them, but is by no means exhaustive. Collections of these plots can be found on the WSJ Graphics Twitter feed and Pinterest.
wsj_pal(palette = "colors6")wsj_pal(palette = "colors6")
palette |
|
The following palettes are defined,
Red/Green/Blue/Yellow theme.
Green/red two-color scale for good/bad.
Black-green 4-color scale for 'Very negative', 'Somewhat negative', 'somewhat positive', 'very positive'.
Democrat/Republican/Undecided blue/red/gray scale.
Red, blue, gold, green, orange, and black palette.
Other colour wsj:
scale_colour_wsj()