I am trying to use ggplot
inside a function, but I am unable to produce
the plots. Specifically, I would like to determine whether or not the plot
will use facet_grid()
from the function call. This is my data:
mydf <- data.frame(
group = rep(c("g1", "g2"), each = 16, times = 1),
cluster = rep(c("c1", "c2"), each = 8, times = 2),
score1 = c(rnorm(n = 16, mean = 10, sd = 10), rnorm(n = 16, mean = 18, sd = 10)),
score2 = c(rnorm(n = 16, mean = 50, sd = 10), rnorm(n = 16, mean = 33, sd = 10))
)
Here is the function:
myFunc <- function(data, group = NULL, group2, var1, var2) {
# So we don't need quotation marks in function call
arguments <- as.list(match.call())
var1 = eval(arguments$var1, data)
var2 = eval(arguments$var2, data)
group2 = eval(arguments$cluster, data)
grouping = eval(arguments$group, data)
# Make this graph if no faceting needed
if (length(grouping) == 0) {
means <- aggregate(cbind(var1, var2) ~ group2, FUN = mean, data = data)
ggplot(data, aes(x = var1, y = var2, color = group2, label = group2)) +
stat_ellipse(type = "norm", show.legend = FALSE, geom = "polygon", alpha = 0.1) +
geom_text(alpha = 0.5, show.legend = FALSE) +
geom_text(data = means, aes(x = var1, y = var2, color = group2))
# Use faceting
} else if (length(grouping) > 0) {
means <- aggregate(cbind(var1, var2) ~ grouping + group2, FUN = mean, data = data)
# Plot
ggplot(data, aes(x = var1, y = var2, color = group2, label = group2)) +
stat_ellipse(type = "norm", show.legend = FALSE, geom = "polygon", alpha = 0.1) +
geom_text(alpha = 0.5, show.legend = FALSE) +
geom_text(data = means, aes(x = var1, y = var2, color = group2)) +
facet_grid(. ~ grouping)
}
}
I am calling the function like so:
myFunc(data = mydf, group = NULL, group2 = cluster, var1 = score1, var2 = score2)
myFunc(data = mydf, group = group, group2 = cluster, var1 = score1, var2 = score2)
Both calls give the following error respectively:
# Error 1
Error: Aesthetics must be either length 1 or the same as the data (32): x, y, colour, label
# Error 2
Error in combine_vars(data, params$plot_env, cols, drop = params$drop) :
At least one layer must contain all variables used for facetting
The expected output can be acquired by building the plots manually:
means <- aggregate(cbind(score1, score2) ~ group + cluster, FUN = mean, data = mydf)
# without facet
ggplot(mydf, aes(x = score1, y = score2, color = cluster, label = cluster)) +
stat_ellipse(type = "norm", show.legend = FALSE, geom = "polygon", alpha = 0.1) +
geom_text(alpha = 0.5, show.legend = FALSE) +
geom_text(data = means, aes(x = score1, y = score2, color = cluster))
# with facet
ggplot(mydf, aes(x = score1, y = score2, color = cluster, label = cluster)) +
stat_ellipse(type = "norm", show.legend = FALSE, geom = "polygon", alpha = 0.1) +
geom_text(alpha = 0.5, show.legend = FALSE) +
geom_text(data = means, aes(x = score1, y = score2, color = cluster)) +
facet_grid(. ~ group)
Here's the basic stat_ellipse
plots with and without using facet_grid
. I will let you add the frills. Here the column names are kept as strings so aes_string
is used instead of aes
, and formulas are passed to functions using as.formula
.
myFunc <- function(df, var1, var2, group2, group1 = NULL) {
# Make this graph if no faceting needed
if (is.null(group1)) {
means_formula <- as.formula(paste(var1, "+", var2, "~", group2))
means <- aggregate(means_formula, FUN = mean, data = df)
p <- ggplot(df,
aes_string(x = var1, y = var2, color = group2, label = group2)) +
stat_ellipse(type = "norm", show.legend = FALSE,
geom = "polygon", alpha = 0.1)
}else{
means_formula <- as.formula(paste(var1,"+",var2,"~", group2,"+",group1))
means <- aggregate(means_formula, FUN = mean, data = df)
p <- ggplot(df,
aes_string(x = var1, y = var2, color = group2, label = group2)) +
stat_ellipse(type = "norm", show.legend = FALSE,
geom = "polygon", alpha = 0.1) +
facet_grid(as.formula(paste(".~ ",group1)))
}
print(p)
}
myFunc(df = mydf, var1 = "score1", var2 = "score2",
group2 = "cluster", group1 = NULL)
myFunc(df = mydf, var1 = "score1", var2 = "score2",
group2 = "cluster", group1 = "group")