R version 4.5.0 beta (2025-03-31 r88079 ucrt) -- "How About a Twenty-Six"
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Platform: x86_64-w64-mingw32/x64

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> #####
> ## Tests for plot interface
> 
> require("papeR")
Loading required package: papeR
Loading required package: car
Loading required package: carData
Loading required package: xtable
Registered S3 method overwritten by 'papeR':
  method    from
  Anova.lme car 

Attaching package: 'papeR'

The following object is masked from 'package:utils':

    toLatex

> 
> ## make sure other plot functions work
> example("plot.data.frame", package = "graphics", ask = FALSE)

plt.d.> plot(OrchardSprays[1], method = "jitter")

plt.d.> plot(OrchardSprays[c(4,1)])

plt.d.> plot(OrchardSprays)

plt.d.> plot(iris)

plt.d.> plot(iris[5:4])

plt.d.> plot(women)
> example("plot.formula", package = "graphics", ask = FALSE)

plt.fr> op <- par(mfrow = c(2,1))

plt.fr> plot(Ozone ~ Wind, data = airquality, pch = as.character(Month))

plt.fr> plot(Ozone ~ Wind, data = airquality, pch = as.character(Month),
plt.fr+      subset = Month != 7)

plt.fr> par(op)

plt.fr> ## text.formula() can be very natural:
plt.fr> wb <- within(warpbreaks, {
plt.fr+     time <- seq_along(breaks); W.T <- wool:tension })

plt.fr> plot(breaks ~ time, data = wb, type = "b")

plt.fr> text(breaks ~ time, data = wb, labels = W.T, col = 1+as.integer(wool))
> 
> ####
> ## check plot.ldf
> 
> data <- data.frame(a = 1:10, b = 10:1, c = rep(1:2, 5))
> data$z <- as.factor(rep(2:3, each = 5))
> data <- as.ldf(data)
> 
> ## plot the data auto"magically"; numerics as boxplot, factors as barplots
> par(mfrow = c(2,2))
> plot(data)
> 
> ## a single plot
> plot(data, variables = "a")
> ## grouped plot
> plot(data, variables = "a", by = "z")
> ## make "c" a factor and plot "c" vs. "z"
> data$c <- as.factor(data$c)
> plot(data, variables = "c", by = "z")
> ## the same
> plot(data, variables = 3, by = 4)
> 
> ## plot everithing against "b"
> ## (grouped boxplots, stacked barplots or scatterplots)
> plot(data, with = "b")
> 
> proc.time()
   user  system elapsed 
   0.57    0.17    0.68