nice_density {rempsyc} | R Documentation |
Easy density plots
Description
Make nice density plots easily. Internally, uses na.rm = TRUE
.
Usage
nice_density(
data,
variable,
group = NULL,
colours,
ytitle = "Density",
xtitle = variable,
groups.labels = NULL,
grid = TRUE,
shapiro = FALSE,
title = variable,
histogram = FALSE,
breaks.auto = FALSE,
bins = 30
)
Arguments
data |
The data frame |
variable |
The dependent variable to be plotted. |
group |
The group by which to plot the variable. |
colours |
Desired colours for the plot, if desired. |
ytitle |
An optional y-axis label, if desired. |
xtitle |
An optional x-axis label, if desired. |
groups.labels |
The groups.labels (might rename to
|
grid |
Logical, whether to keep the default background grid or not. APA style suggests not using a grid in the background, though in this case some may find it useful to more easily estimate the slopes of the different groups. |
shapiro |
Logical, whether to include the p-value from the Shapiro-Wilk test on the plot. |
title |
The desired title of the plot. Can be put to |
histogram |
Logical, whether to add an histogram |
breaks.auto |
If histogram = TRUE, then option to set bins/breaks
automatically, mimicking the default behaviour of base
R |
bins |
If |
Value
A density plot of class ggplot
, by group (if provided), along a
reference line representing a matched normal distribution.
See Also
Other functions useful in assumption testing:
nice_assumptions
, nice_normality
,
nice_qq
, nice_varplot
,
nice_var
. Tutorial:
https://rempsyc.remi-theriault.com/articles/assumptions
Examples
# Make the basic plot
nice_density(
data = iris,
variable = "Sepal.Length",
group = "Species"
)
# Further customization
nice_density(
data = iris,
variable = "Sepal.Length",
group = "Species",
colours = c("#00BA38", "#619CFF", "#F8766D"),
xtitle = "Sepal Length",
ytitle = "Density (vs. Normal Distribution)",
groups.labels = c(
"(a) Setosa",
"(b) Versicolor",
"(c) Virginica"
),
grid = FALSE,
shapiro = TRUE,
title = "Density (Sepal Length)",
histogram = TRUE
)