Create a control chart, aka Shewhart chart: https://en.wikipedia.org/wiki/Control_chart.
control_chart(d, measure, x, group1, group2, center_line = mean, sigmas = 3, title = NULL, catpion = NULL, font_size = 11, print = TRUE)
data frame or a path to a csv file that will be read in
variable of interest mapped to y-axis (quoted, ie as a string)
variable to go on the x-axis, often a time variable. If unspecified row indices will be used (quoted)
Optional grouping variable to be panelled horizontally (quoted)
Optional grouping variable to be panelled vertically (quoted)
Function used to calculate central tendency. Defaults to mean
Number of standard deviations above and below the central tendency to call a point influenced by "special cause variation." Defaults to 3
Title in upper-left
Caption in lower-right
Base font size; text elements will be scaled to this
Print the plot? Default = TRUE. Set to FALSE if you want to assign the plot to a variable for further modification, as in the last example.
Generally called for the side effect of printing the control chart. Invisibly, returns a ggplot object for further customization.
d <- tibble::data_frame( day = sample(c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday"), 100, TRUE), person = sample(c("Tom", "Jane", "Alex"), 100, TRUE), count = rbinom(100, 20, ifelse(day == "Friday", .5, .2)), date = Sys.Date() - sample.int(100)) # Minimal arguments are the data and the column to put on the y-axis. # If x is not provided, observations will be plotted in order of the rows control_chart(d, "count")# Specify categorical variables for group1 and/or group2 to get a separate # panel for each category control_chart(d, "count", group1 = "day", group2 = "person")# In addition to printing or writing the plot to file, control_chart # returns the plot as a ggplot2 obejct, which you can then further customize library(ggplot2) my_chart <- control_chart(d, "count", "date")my_chart + ylab("Number of Adverse Events") + scale_x_date(name = "Week of ... ", date_breaks = "week") + theme(axis.text.x = element_text(angle = -90, vjust = 0.5, hjust=1))