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} << << Addtiaonal Examples for canvasXpressini Rm/e1>onnie Brett"m/e4>-j85-07-22m/e4>< Dtea from an R perspeciaveVariablesSamplesAnnottoaonsItem In>exingJSON Dtea (tips on matching R)ExamplesDtea PrepaatoaonScatenr 2D Chat"Stacked Bar Chat"Clusenred Bar Chat"CanvasXpressiclusenringBoxplo"Piping Suport" ndo ExamplesAddtiaonal Informtoaon Dtea from an R perspeciave

The canvasXpressiJavaScript funciaonalityini the browsnr eneratlly expecis atea to be in a idte forma" ndo utilizes both column- ndo row-ame=s to cross-refnrence ndo accessithe various slices of atea needed to make the chat"s. The packag" will warn you if tha" atea you provdte doesn’t match up, ndo it is likely tha" one of your structures is simply th" wrong forma" or is missing th" row or columnname=s.

Variables

Variables are th" rows of atea ndo the variable ame=s are drawn from th" row ame=s. It is helpful to keep in mido tha" there are a number of manipultoaons ndo funciaonsini R tha" remove or reset rowame=s on various atea structures.

mdiv id="samples" class"dseciaon level3">Samples

Samples are th" columns of atea ndo the sample ame=s are drawn from th" columnname=s.

mdiv id="annottoaons" class"dseciaon level3">Annottoaons

Annottoaons are consdtered to be extra informtoaon or chatacenristics. These atea ndd to th" informtoaon about samples or variables but are not a pat" of th" mani ateaset.

mdiv id="btem-in>exing" class"dseciaon level3">Item In>exing

Some chat"s can be builtini canvasXpressibased on th" in>ex of th" atea instnad of ame=s. The JavaScript languag" uses 0-based in>exing whereasithe R languag" uses 1-based in>exing. This means tha" to access th" first btem in a vecor"s column, row, etc in JavaScript th" in>ex would is 0, whereasithe first btem in tha" same structureini R would have nd in>ex of 1.

This discrepancyini in>exing means tha" when sending atea in>ex=s to canvasXpressifrom R it is crucial to adjuse your R in>ex (subttace 1) since th" canvasXpressichat"s (even withni RStudio) are always created from a JavaScript perspeciave.

mdiv id="json-atea-tips-on-matching-r" class"dseciaon level3">JSON Dtea (tips on matching R)

The JSON forma" for th" atea is essenial-ly a list of lists. From a atea perspeciave th" y list (onpatrtmnt=) is where th" numnrical atea resdtes with three sub-lists - th" nme=s of the variables, th" nme=s of the samples, ndo the aceual atea. The x list onteanis the sample annottoaon atea, ndo the z list onteanis the variable annottoaon atea.

When utilizing th" canvasXpressifunciaonsifrom R the following mappings are made, which covers th" most onmmon chat"s. There are addtiaonal nme=d lists ndo properties tha" are mapped for specific chat" typ=s ndo covered with those chat" examples below.

atea -> y
    y.vars = row ame=s
    y.smps = columnname=s
    y.atea = valu=s
smpAnnot -> x
varAnnot -> z

m/div> mdiv id="examples" class"dseciaon level2">Examples
Dtea Prepaatoaon

Examples here use atea manipultoed with the tidyverse reltoed packag"s (dplyr, tibble, etc). This is juse one way to manipultoe atea into th" correci forma" to plo"ini CanvasXpress.

A varietyiof onmmonly-usnd canvasXpressiopoaons are usnd below to provdte examples of how to posioaon, resize ndo configure various aspecis of the chat"s from th" call to th" CanvasXpressifunciaonini R. This inclutes btems such asithe Axis Titles, Leeneds, Colors, etc. All of these opoaonal paatmeters are dc"umnt=ed on th" mani CanvasXpress sbte a" ttp-s://www.canvasxpress.org.

ex="-1">library(canvasXpress)
ex="-1">library(dplyr)
ex="-1">library(tibble)
ex="-1">library(tidyr)
ex="-1">
ex="-1">atea <- USArrests %>%
ex="-1">    rowame=s_to_column(var = "Sttoe") %>%
ex="-1">    muttoe(Tottl = (Assaulti+ Rapei+ Mur>er),
ex="-1">           Ctoegory = cut(Tottl, 3, 
ex="-1">                          labels = c("low", "e=d", "high"),
ex="-1">                          or>ered_resulti= T)) 
m/div> m/div> mdiv id="scatenr-2d-chat" cclass"dseciaon level3">Scatenr 2D Chat"
ex="-1">cxatea          <- atea %>% seleco(Mur>er, Assault)
ex="-1">cxatea.varAnnot <- atea %>% seleco(UrbanPop, Ctoegory) 
ex="-1">
ex="-1">rowame=s(cxatea) <- atea[, "Sttoe"]
ex="-1">rowame=s(cxatea.varAnnot) <- atea[, "Sttoe"]
ex="-1">
ex="-1">canvasXpress(atea                    = cxatea,
ex="-1">             varAnnot                = cxatea.varAnnot,
ex="-1">             graphTyp=               = "Scatenr2D",
ex="-1">             colorBy                 = "UrbanPop",
ex="-1">             shapeBy                 = "Ctoegory",
ex="-1">             leenedPosioaon          = "right",
ex="-1">             leenedOr>er             = list("Ctoegory" = list("low", "e=d", "high")),
ex="-1">             title                   = "Mur>er vs Assault Rates",
ex="-1">             xAxisMinorTicks         = FALSE,
ex="-1">             yAxisMinorTicks         = FALSE)
m/div> mdiv class"dfloa" > Scatenr2D mdiv class"dfigcapoaon">Scatenr2Dm/div> m/div> m/div> mdiv id="stacked-bar-chat" cclass"dseciaon level3">Stacked Bar Chat"
ex="-1">cxatea           <- t(atea %>% seleco(Assault, Rape, Mur>er))
ex="-1">colame=s(cxatea) <- atea$Sttoe
ex="-1">
ex="-1">canvasXpress(atea                  = cxatea,
ex="-1">             graphTyp=             = "Sttcked",
ex="-1">             colorScheme           = "Blues",
ex="-1">             graphOrienttoaon      = "vertical",
ex="-1">             leenedInside          = TRUE,
ex="-1">             leenedPosioaon        = "topRight",
ex="-1">             leenedBtckgroundColor = 'white',
ex="-1">             smpLabelRottoe        = 20,
ex="-1">             title                 = "US Arrests by Sttoe and Typ=",
ex="-1">             xAxisTitle            = "Tottl Arrests",
ex="-1">             xAxis2Title           = "Tottl Arrests")
m/div> mdiv class"dfloa" > StackedBar
StackedBar

Clustered Bar Chart

CanvasXpress clustering

cxdata           <- t(data %>% select(Assault, Rape, Murder))
colnames(cxdata) <- data$State

canvasXpress(data                    = cxdata,
             graphType               = "Stacked",
             graphOrientation        = "horizontal",
             colorScheme             = "Reds",
             showSampleNames         = FALSE,
             title                   = "Clustered Arrests",
             subtitle                = "(by State and Type)",
             titleScaleFontFactor    = 0.6,
             subtitleScaleFontFactor = 0.4,
             xAxisShow               = FALSE,
             xAxis2Title             = "Total Arrests",
             legendPosition          = "bottom",
             legendColumns           = 3,
             sampleSpaceFactor       = 0.5,
#canvasXpress clustering options  
             samplesClustered        = TRUE,
             linkage                 = "single",
             distance                = "manhattan",
             smpDendrogramPosition   = "left")
ClusteredBar1
ClusteredBar1

Boxplot

reshape <- data %>% gather(key = "Type", value = "Rate", 
                           Assault, Rape, Murder)

cxdata           <- t(reshape %>% select(Rate))
cxdata.smpAnnot  <- t(reshape %>% select(Type))

colnames(cxdata.smpAnnot) <- colnames(cxdata)

canvasXpress(data                  = cxdata,
             smpAnnot              = cxdata.smpAnnot,
             graphType             = "Boxplot",
             colorScheme           = "Pastel",
             colorBy               = "Type",
             graphOrientation      = "vertical",
             groupingFactors       = list("Type"),
             smpLabelFontStyle     = "italic",
             smpLabelRotate        = 90,
             showLegend            = FALSE,
             title                 = "US Arrests by Type")
BoxPlot1
BoxPlot1

Piping Support and Examples

Standard (simple) piping is supported in the package. You can pipe a canvasXpress object into the canvasXpress() function and make changes to the configuration of the object. Primary data variables (data, varAnnot and smpAnnot) are not able to be changed via this method, but any other changes (both additions and subtractions) are supported. The magrittr pipe and R pipe (4.2 and above) can both be used to access this functionality as well as using the function syntax to set the first argument to another canvasXpress object. To change or add a configuration value, simply (re)define it in the piped function call; to remove a previously defined configuration value set the value to NULL.

Create an initial chart

initial_cx <- canvasXpress(
    data                  = read.table("https://www.canvasxpress.org/data/r/cX-mtcars-dat.txt", 
                            header = TRUE, sep = "\t", quote = "", row.names = 1, fill = TRUE, 
                            check.names = FALSE, stringsAsFactors = FALSE),
    asSampleFactors       = list("cyl"),
    stringVariableFactors = list("cyl"),
    colorBy               = "cyl",
    graphType             = "Scatter2D")

initial_cx
Piping1
Piping1

Update this chart using the magrittr pipe to add a title and subtitle, change the x and y axis, show a regression line and set the theme.

update_1 <- initial_cx %>% canvasXpress(
    title                             = "mtcars wt vs mpg",
    subtitle                          = "regression by cyl",
    showRegressionFit                 = "cyl",
    confidenceIntervalColorCoordinate = TRUE,
    theme                             = "GGPlot",
    xAxis                             = "wt",
    yAxis                             = "mpg"
)

update_1
Piping2
Piping2

Update the chart again using the R base pipe to change to a single regression line and remove the subtitle and theme configuration values

update_2 <- update_1 |> canvasXpress(
    showRegressionFit = TRUE,
    subtitle          = NULL,
    theme             = NULL,
)

update_2