Snippet #1: ggplot loops

1. Create an empty list
2. Populate your list with objects (ggplots)
3. Create iteratively names for the objects
4. Rename the objects inside the list using the name list generated previously
5. Show all plots using wrap_plots

Instead of using boring plots we will use our private art collections and items.

One great package to create your art in R is aRtsy Let’s fire it up

require(aRtsy)

Caricamento del pacchetto richiesto: aRtsy

require(patchwork)

Caricamento del pacchetto richiesto: patchwork

#before starting for having a look at the palette 
?colorPalette

avvio in corso del server httpd per la guida ... fatto

Create a Mondrian and save it

set.seed(34)
Composition_10 <- canvas_squares(colors = colorPalette("boogy2"))
saveCanvas(Composition_10 , filename = "Mondrian.png")
Composition_10 

and another one

set.seed(1)
aspect_ratio <- 1
height <- 2
Composition_1 = canvas_segments(colors = colorPalette("blackwhite"))
Composition_1 

or if you want to create a lots of them, create names automatically and then take a look at just one of your artistic composition in your collection use the following code:

n_items <- 3
collection <- list()
name_of_Composition  <- list()
for (i in 1:n_items) {
  seed <-  (sample(1:100000,1)) + 1
  name_of_Composition[[i]] <- paste0("Composition_", i)
  collection[[i]] <- canvas_squares(colors = colorPalette("boogy2"))
  
}
names(collection) <- name_of_Composition

collection

$Composition_1

$Composition_2

$Composition_3

#as you can notice the setting for figure output in this chunk was changed in order to showplots with a rato of 3:1
wrap_plots(collection)

[Wickham (2016)](Derks 2022)(Pedersen 2022)

References

Derks, Koen. 2022. “aRtsy: Generative Art with ’Ggplot2’.” https://CRAN.R-project.org/package=aRtsy.

Pedersen, Thomas Lin. 2022. “Patchwork: The Composer of Plots.” https://CRAN.R-project.org/package=patchwork.

Wickham, Hadley. 2016. “Ggplot2: Elegant Graphics for Data Analysis.” https://ggplot2.tidyverse.org.