tidyplots (version 0.2.2)

add_mean_bar: Add mean

Description

Add mean

Usage

add_mean_bar(
  plot,
  dodge_width = NULL,
  width = 0.6,
  saturation = 1,
  preserve = "total",
  ...
)
add_mean_dash(
  plot,
  dodge_width = NULL,
  width = 0.6,
  linewidth = 0.25,
  preserve = "total",
  ...
)
add_mean_dot(plot, dodge_width = NULL, size = 2, preserve = "total", ...)
add_mean_value(
  plot,
  dodge_width = NULL,
  accuracy = 0.1,
  scale_cut = NULL,
  fontsize = 7,
  extra_padding = 0.15,
  vjust = NULL,
  hjust = NULL,
  preserve = "total",
  ...
)
add_mean_line(
  plot,
  group,
  dodge_width = NULL,
  linewidth = 0.25,
  preserve = "total",
  ...
)
add_mean_area(
  plot,
  group,
  dodge_width = NULL,
  linewidth = 0.25,
  preserve = "total",
  ...
)

Value

A tidyplot object.

Arguments

plot

A tidyplot generated with the function tidyplot().

dodge_width

For adjusting the distance between grouped objects. Defaults to 0.8 for plots with at least one discrete axis and 0 for plots with two continuous axes.

width

Width of the plot area. Defaults to 50.

saturation

A number between 0 and 1 for the color saturation of an object. A value of 0 is completely desaturated (white), 1 is the original color.

preserve

Should dodging preserve the "total" width of all elements at a position, or the width of a "single" element?

...

Arguments passed on to the geom function.

linewidth

Thickness of the line in points (pt). Typical values range between 0.25 and 1.

size

A number representing the size of the plot symbol. Typical values range between 1 and 3.

accuracy

A number to round to. Use (e.g.) 0.01 to show 2 decimal places of precision. If NULL, the default, uses a heuristic that should ensure breaks have the minimum number of digits needed to show the difference between adjacent values.

Applied to rescaled data.

scale_cut

Scale cut function to be applied. See scales::cut_short_scale() and friends.

fontsize

Font size in points. Defaults to 7.

extra_padding

Extra padding to create space for the value label.

vjust

Vertical position adjustment of the value label.

hjust

Horizontal position adjustment of the value label.

group

Variable in the dataset to be used for grouping.

Examples

study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_bar()

study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_dash()

study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_dot()

study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_value()

study |>
  tidyplot(x = treatment, y = score) |>
  add_mean_line()

study |>
  tidyplot(x = treatment, y = score) |>
  add_mean_area()

# Combination
study |>
  tidyplot(x = treatment, y = score) |>
  add_mean_bar(alpha = 0.4) |>
  add_mean_dash() |>
  add_mean_dot() |>
  add_mean_value() |>
  add_mean_line()

# Changing arguments: alpha
# Makes objects transparent
study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  theme_minimal_y() |>
  add_mean_bar(alpha = 0.4)

# Changing arguments: saturation
# Reduces fill color saturation without making the object transparent
study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  theme_minimal_y() |>
  add_mean_bar(saturation = 0.3)

# Changing arguments: accuracy
study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_value(accuracy = 0.01)

# Changing arguments: fontsize
study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_value(fontsize = 10)

# Changing arguments: color
study |>
  tidyplot(x = treatment, y = score, color = treatment) |>
  add_mean_value(color = "black")