plot_violin: Generate a violin plot.

In bcgov/elucidate: Convenience Functions to Help Researchers Elucidate Patterns in Their Data

Generate a violin plot.

Description

Easily generate violin plots using ggplot2 with a simplified customization interface for common modifications with static (ggplot) and interactive (plotly) output options. The static output is useful for producing static reports (e.g. for manuscripts) and is readily customized further using ggplot2 syntax. The interactive output is helpful for exploring the data and producing dynamic html reports. See this blog post for an introduction to ggplot2.

Usage

plot_violin(
  data,
  y,
  x = NULL,
  ...,
  fill_var = NULL,
  colour_var = NULL,
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  title_hjust = 0.5,
  caption = NULL,
  caption_hjust = 0,
  fill_var_title = NULL,
  colour_var_title = NULL,
  ylim = c(NA, NA),
  ybreaks = ggplot2::waiver(),
  transform_y = FALSE,
  y_transformation = "log10",
  y_var_labs = ggplot2::waiver(),
  x_var_order = NULL,
  x_var_labs = NULL,
  fill_var_order = NULL,
  colour_var_order = NULL,
  fill_var_labs = NULL,
  colour_var_labs = NULL,
  fill_var_values = NULL,
  colour_var_values = NULL,
  palette = c("plasma", "C", "magma", "A", "inferno", "B", "viridis", "D", "cividis",
    "E"),
  palette_direction = c("d2l", "l2d"),
  palette_begin = 0,
  palette_end = 1,
  alpha = 0.75,
  greyscale = FALSE,
  line_size = 1,
  theme = c("bw", "classic", "grey", "light", "dark", "minimal"),
  text_size = 14,
  font = c("sans", "serif", "mono"),
  facet_var = NULL,
  facet_var_order = NULL,
  facet_var_labs = NULL,
  facet_var_strip_position = c("top", "bottom"),
  facet_var_text_bold = TRUE,
  legend_position = c("right", "left", "top", "bottom"),
  omit_legend = FALSE,
  interactive = FALSE,
  aesthetic_options = FALSE
)

Arguments

data	A data frame or tibble containing the dependent measure "y" and any grouping variables.
y	A numeric variable you want to obtain violin plots for (quoted or unquoted), e.g. y = "variable" or y = variable.
x	A categorical variable you want to obtain separate violin plots of y for (quoted or unquoted), e.g. x = "variable" or x = variable.
...	graphical parameters (not associated with variables) to be passed to geom_violin, e.g. colour or fill, to be applied to all bars. To see some of the available options in a web browser, set the aesthetic_options argument to TRUE. An option unique to geom_violin is draw_quantiles, which adds horizontal lines for the specified quantiles, e.g. draw_quantiles = c(0.25, 0.5, 0.75) would add lines for the 25th, 50th, and 75th percentiles (similar to a boxplot).
fill_var	Use if you want to assign a variable to the violin fill colour, e.g. fill_var = "grouping_variable" or fill_var = grouping_variable. Produces separate sets of bars for each level of the fill variable. See aes for details.
colour_var	Use if you want to assign a variable to the violin outline colour, e.g. colour_var = "grouping_variable" or colour_var = grouping_variable. Produces separate sets of bars for each level of the colour variable. See aes for details.
xlab	Specify/overwrite the x-axis label using a character string, e.g. "x-axis label"
ylab	Specify/overwrite the y-axis label using a character string, e.g. "y-axis label"
title	Add a main title to the plot using a character string, e.g. "Violin graph of X"
title_hjust	Left-to-right/horizontal justification (alignment) of the main plot title. Accepts values from 0 (far left) to 1 (far right). Default is 0.5 (centre).
caption	Add a figure caption to the bottom of the plot using a character string.
caption_hjust	Left-to-right/horizontal justification (alignment) of the caption. Accepts values from 0 (far left) to 1 (far right). Default is 0 (left).
fill_var_title	If a variable has been assigned to fill using fill_var, this allows you to modify the variable label in the plot legend.
colour_var_title	If a variable has been assigned to colour using colour_var, this allows you to modify the variable label in the plot legend.
ylim	specify the y-axis limits, e.g. ylim = c(lower_limit, upper_limit). Use NA for the existing minimum or maximum value of y, e.g. the default is ylim = c(NA, NA)
ybreaks	This allows you to change the break points to use for tick marks on the y-axis. seq is particularly useful here. See scale_y_continuous for details. If ybreaks is specified, then ylim should be also.
transform_y	Would you like to transform the y axis? (TRUE or FALSE)
y_transformation	If transform_y = TRUE, this determines the transformation to be applied. Common choices include "log10" (the default), "log2", "sqrt", or "exp". See scale_continuous for details.
y_var_labs	Allows you to modify the labels displayed with the y-axis tick marks. See scale_continuous for details.
x_var_order	If a variable has been assigned to x, this allows you to modify the order of the variable groups, e.g. x = grouping_variable, x_var_order = c("group_2", "group_1"). See fct_relevel for details.
x_var_labs	If a variable has been assigned to x, this allows you to modify the labels of the variable groups, e.g. x = grouping_variable, x_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
fill_var_order	If a variable has been assigned to fill using fill_var, this allows you to modify the order of the variable groups, e.g. fill_var = grouping_variable, fill_var_order = c("group_2", "group_1"). See fct_relevel for details.
colour_var_order	If a variable has been assigned to colour using colour_var, this allows you to modify the order of the variable groups, e.g. colour_var = grouping_variable, fill_var_order = c("group_2", "group_1"). See fct_relevel for details.
fill_var_labs	If a variable has been assigned to fill using fill_var, this allows you to modify the labels of the variable groups, e.g. fill_var = grouping_variable, fill_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
colour_var_labs	If a variable has been assigned to colour using colour_var, this allows you to modify the labels of the variable groups, e.g. colour_var = grouping_variable, colour_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
fill_var_values	If a variable has been assigned to fill using fill_var, this allows you to modify the colours assigned to the fill of each of the variable groups, e.g. fill_var = grouping_variable, fill_var_values = c("blue", "red"). See scale_fill_manual for details. For the colour options available in base R, see colour_options.
colour_var_values	If a variable has been assigned to colour using colour_var, this allows you to modify the colours assigned to the outline of each of the variable groups, e.g. colour_var = grouping_variable, colour_var_values = c("blue", "red"). See scale_fill_manual for details. For the colour options available in base R, see colour_options.
palette	If a variable is assigned to fill_var or colour_var, this determines which viridis colour palette to use. Options include "plasma" or "C" (default), "magma" or "A", "inferno" or "B", "viridis" or "D", and "cividis" or "E". See this link for examples. You can override these colour palettes with fill_var_values or colour_var_values.
palette_direction	Choose "d2l" for dark to light (default) or "l2d" for light to dark.
palette_begin	Value between 0 and 1 that determines where along the full range of the chosen colour palette's spectrum to begin sampling colours. See scale_fill_viridis_d for details.
palette_end	Value between 0 and 1 that determines where along the full range of the chosen colour palette's spectrum to end sampling colours. See scale_fill_viridis_d for details.
alpha	This adjusts the transparency/opacity of the graphical components of the plot, ranging from 0 = 100% transparent to 1 = 100% opaque.
greyscale	Set to TRUE if you want the plot converted to greyscale.
line_size	Controls the thickness of the violin outlines.
theme	Adjusts the theme using 1 of 6 predefined "complete" theme templates provided by ggplot2. Currently supported options are: "classic", "bw" (the elucidate default), "grey" (the ggplot2 default), "light", "dark", & "minimal". See theme_bw for more information.
text_size	This controls the size of all plot text. Default = 14.
font	This controls the font of all plot text. Default = "sans" (Arial). Other options include "serif" (Times New Roman) and "mono" (Courier New).
facet_var	Use if you want separate plots for each level of a grouping variable (i.e. a faceted plot), e.g. facet_var = "grouping_variable" or facet_var = grouping_variable. See facet_wrap for details.
facet_var_order	If a variable has been assigned for faceting using facet_var, this allows you to modify the order of the variable groups, e.g. facet_var = grouping_variable, facet_var_order = c("group_2", "group_1"). See fct_relevel for details.
facet_var_labs	If a variable has been assigned for faceting using facet_var, this allows you to modify the labels of the variable groups which will appear in the facet strips, e.g. facet_var = grouping_variable, facet_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
facet_var_strip_position	If a variable has been assigned for faceting using facet_var, this allows you to modify the position of the facet strip labels. Sensible options include "top" (the default) or "bottom".
facet_var_text_bold	If a variable has been assigned for faceting using facet_var, this allows you to use boldface (TRUE/default or FALSE) for the facet strip label text.
legend_position	This allows you to modify the legend position. Options include "right" (the default), "left", "top", & "bottom".
omit_legend	Set to TRUE if you want to remove/omit the legends.
interactive	Determines whether a static ggplot object or an interactive html plotly object is returned. See ggplotly for details.
aesthetic_options	If set to TRUE, opens a web browser to the tidyverse online aesthetic options vignette.

Value

A ggplot object or plotly object depending on whether static or interactive output was requested.

Author(s)

Craig P. Hutton, [e-mail]

References

Wickham, H. (2016). ggplot2: elegant graphics for data analysis. New York, N.Y.: Springer-Verlag.

See Also

geom_violin, ggplotly

Examples

data(mtcars) #load the mtcars data

plot_violin(mtcars, y = mpg, x = cyl, fill = "blue")

plot_violin(mtcars, y = mpg, x = cyl,
            fill = "blue", draw_quantiles = c(0.25, 0.5, 0.75))


plot_violin(mtcars, x = cyl, y = hp,
           xlab = "# of cylinders",
           ylab = "horsepower",
           fill_var = am,
           fill_var_title = "transmission",
           fill_var_labs = c("manual" = "0", "automatic" = "1"),
           fill_var_values = c("blue", "red"),
           theme = "bw")

#modifying fill doesn't work as well for the interactive version of a boxplot
plot_violin(mtcars, x = cyl, y = hp,
           xlab = "# of cylinders",
           ylab = "horsepower",
           fill_var = am,
           fill_var_title = "transmission",
           fill_var_labs = c("manual" = "0", "automatic" = "1"),
           fill_var_values = c("blue", "red"),
           theme = "bw",
           interactive = TRUE)

#using colour works better for the interactive version
plot_violin(mtcars, x = cyl, y = hp,
           xlab = "# of cylinders",
           ylab = "horsepower",
           colour_var = am,
           colour_var_title = "transmission",
           colour_var_labs = c("manual" = "0", "automatic" = "1"),
           colour_var_values = c("blue", "red"),
           theme = "bw", interactive = TRUE)

bcgov/elucidate documentation built on Sept. 3, 2022, 7:16 p.m.