strip: plot categorical x quantitative data jittered
In lukereding/redingPlot: Collection of plotting functions

Description Usage Arguments Value Examples

plots each vector in your list as a group with the data jittered, draws a point at the mean. very similar to simple()

strip(data, lab = rep(c(), length(data)), type = "se", jitter = T,
  points = 16, xlab = "", ymin = "determine", ymax = "determine",
  point_size = 1.2, mean_col = "red", cols = viridis(length(data) +
  2)[1:length(data)], ...)

`data`	list of vectors you want to plot
`lab`	labels for each group
`type`	what kind of uncertainty do you want to show around the mean? options are "se" for standard error, "sd" for standard deviation, or "ci" for a 95 percent confidence interval
`jitter`	logical. should the data be jittered?
`points`	type of plotting character. defaults to solid point, i.e., 16
`xlab`	label for x axis
`ymin`	minimum y value.
`ymax`	maximum y value
`point_size`	size of the plotting characters. defaults to 1.2
`mean_col`	color of the point for the mean. defaults to "red"
`cols`	vector of colors for the groups. defaults to viridis colors
`...`	other arguments to pass to be par()

None

strip(list(rnorm(50,5),rnorm(20,10)))
strip(list(rpois(50,5),rpois(20,3),rnorm(100,7)),type="ci",lab=c("a","b","c"),xlab="group",ylab="response")
strip(list(rpois(50,5),rpois(20,3),rnorm(100,7),rnorm(45,2),rnorm(90,9)),type="ci",lab=c("a","b","c","d","e"),xlab="group",ylab="value",mean_col="black",col=viridis(7)[1:5] %>% addAlpha(0.5))
strip(list(iris %>% filter(Species=="setosa") %>% .$Sepal.Length, iris %>% filter(Species=="versicolor") %>% .$Sepal.Length, iris %>% filter(Species=="virginica") %>% .$Sepal.Length),lab=c("setosa","versicolor","virginica"),ylab="sepal length",main="strip()",xlab="species",mean_col="black",point_size=1.4,type="ci")