nested_data_plot | R Documentation |
Creates a plot showing the breakdown of variation within a sample. This function uses ggplot2 internally.
nested_data_plot(
dat,
x,
groups = c(),
stat = "mean",
...,
y_gap = 1,
divider_color = "grey50",
point_args = list(),
dline_args = list(),
vline_args = list(),
hline_args = list(),
label_args = list(),
connector_args = list()
)
dat |
a |
x |
the variable within |
groups |
a vector of variables to group the data by |
stat |
a function for computing the central location for each group. This is normally "mean" but could be "median" or another function. |
... |
extra options. See Details. |
y_gap |
the vertical gap between grouping variables |
divider_color |
the color of the lines between grouping variables.
Or |
point_args |
arguments to pass to ggplot2::geom_point when plotting individual data points. |
dline_args |
arguments to pass to ggplot2::geom_segment when plotting the horizontal lines between data points. |
vline_args |
arguments to pass to ggplot2::geom_segment when plotting vertical lines |
hline_args |
arguments to pass to ggplot2::geom_segment when plotting horizontal lines connecting levels in groups |
label_args |
arguments to pass to ggplot2::geom_label when plotting labels |
connector_args |
arguments to pass to ggplot2::geom_point when plotting the connection between the vertical lines and the horizontal lines connecting levels in groups |
Extra options can be included to control aesthetic options. The following options are supported. Any (or all) can be set to a single variable in the data set.
color
: Controls the color of the data points.
fill
: Controls the fill color of the labels. When a particular label
is associated with data points with more than one level of the supplied
variable, the fill is omitted.
library(dplyr)
carbon.fabric.2 %>%
filter(test == "WT" & condition == "RTD") %>%
nested_data_plot(strength,
groups = c(batch, panel))
# Labels can be filled too
carbon.fabric.2 %>%
filter(test == "WT" & condition == "RTD") %>%
nested_data_plot(strength,
groups = c(batch, panel),
fill = batch)
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