Dotplot Chart

According to William S. Cleveland dotplots are an alternative to the bar chart, in which dots are used to depict the quantitative values (e.g. counts) associated with categorical variables.


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Example Fonts



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Tools

<!-- Include the CanvasXpress library in your HTML file -->
<link rel="stylesheet" href="https://www.canvasxpress.org/dist/canvasXpress.css" type="text/css"/>
<script src="https://www.canvasxpress.org/canvasXpress.min.js"></script>


<!-- Create a canvas element for the chart with the desired dimensions -->
<div>
  <canvas id="canvasId" width="600" height="600"</canvas>
</div>


<!-- Create a script to initialize the chart -->
<script>

  <!-- Create the data for the graph -->
  var data = {
     "m" : {
        "Description" : "The data set consists of 50 Ss from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). Four features were measured from each S :  the length and the width of the sepals and petals, in centimetres.",
        "Name" : "Anderson's Iris data set",
        "Reference" : "R. A. Fisher (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics 7 (2) :  179-188."
     },
     "x" : {
        "Species" : ["setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","versicolor","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica","virginica"]
     },
     "y" : {
        "data" : [
          [5.1,4.9,4.7,4.6,5,5.4,4.6,5,4.4,4.9,5.4,4.8,4.8,4.3,5.8,5.7,5.4,5.1,5.7,5.1,5.4,5.1,4.6,5.1,4.8,5,5,5.2,5.2,4.7,4.8,5.4,5.2,5.5,4.9,5,5.5,4.9,4.4,5.1,5,4.5,4.4,5,5.1,4.8,5.1,4.6,5.3,5,7,6.4,6.9,5.5,6.5,5.7,6.3,4.9,6.6,5.2,5,5.9,6,6.1,5.6,6.7,5.6,5.8,6.2,5.6,5.9,6.1,6.3,6.1,6.4,6.6,6.8,6.7,6,5.7,5.5,5.5,5.8,6,5.4,6,6.7,6.3,5.6,5.5,5.5,6.1,5.8,5,5.6,5.7,5.7,6.2,5.1,5.7,6.3,5.8,7.1,6.3,6.5,7.6,4.9,7.3,6.7,7.2,6.5,6.4,6.8,5.7,5.8,6.4,6.5,7.7,7.7,6,6.9,5.6,7.7,6.3,6.7,7.2,6.2,6.1,6.4,7.2,7.4,7.9,6.4,6.3,6.1,7.7,6.3,6.4,6,6.9,6.7,6.9,5.8,6.8,6.7,6.7,6.3,6.5,6.2,5.9],
          [3.5,3,3.2,3.1,3.6,3.9,3.4,3.4,2.9,3.1,3.7,3.4,3,3,4,4.4,3.9,3.5,3.8,3.8,3.4,3.7,3.6,3.3,3.4,3,3.4,3.5,3.4,3.2,3.1,3.4,4.1,4.2,3.1,3.2,3.5,3.6,3,3.4,3.5,2.3,3.2,3.5,3.8,3,3.8,3.2,3.7,3.3,3.2,3.2,3.1,2.3,2.8,2.8,3.3,2.4,2.9,2.7,2,3,2.2,2.9,2.9,3.1,3,2.7,2.2,2.5,3.2,2.8,2.5,2.8,2.9,3,2.8,3,2.9,2.6,2.4,2.4,2.7,2.7,3,3.4,3.1,2.3,3,2.5,2.6,3,2.6,2.3,2.7,3,2.9,2.9,2.5,2.8,3.3,2.7,3,2.9,3,3,2.5,2.9,2.5,3.6,3.2,2.7,3,2.5,2.8,3.2,3,3.8,2.6,2.2,3.2,2.8,2.8,2.7,3.3,3.2,2.8,3,2.8,3,2.8,3.8,2.8,2.8,2.6,3,3.4,3.1,3,3.1,3.1,3.1,2.7,3.2,3.3,3,2.5,3,3.4,3],
          [1.4,1.4,1.3,1.5,1.4,1.7,1.4,1.5,1.4,1.5,1.5,1.6,1.4,1.1,1.2,1.5,1.3,1.4,1.7,1.5,1.7,1.5,1,1.7,1.9,1.6,1.6,1.5,1.4,1.6,1.6,1.5,1.5,1.4,1.5,1.2,1.3,1.4,1.3,1.5,1.3,1.3,1.3,1.6,1.9,1.4,1.6,1.4,1.5,1.4,4.7,4.5,4.9,4,4.6,4.5,4.7,3.3,4.6,3.9,3.5,4.2,4,4.7,3.6,4.4,4.5,4.1,4.5,3.9,4.8,4,4.9,4.7,4.3,4.4,4.8,5,4.5,3.5,3.8,3.7,3.9,5.1,4.5,4.5,4.7,4.4,4.1,4,4.4,4.6,4,3.3,4.2,4.2,4.2,4.3,3,4.1,6,5.1,5.9,5.6,5.8,6.6,4.5,6.3,5.8,6.1,5.1,5.3,5.5,5,5.1,5.3,5.5,6.7,6.9,5,5.7,4.9,6.7,4.9,5.7,6,4.8,4.9,5.6,5.8,6.1,6.4,5.6,5.1,5.6,6.1,5.6,5.5,4.8,5.4,5.6,5.1,5.1,5.9,5.7,5.2,5,5.2,5.4,5.1],
          [0.2,0.2,0.2,0.2,0.2,0.4,0.3,0.2,0.2,0.1,0.2,0.2,0.1,0.1,0.2,0.4,0.4,0.3,0.3,0.3,0.2,0.4,0.2,0.5,0.2,0.2,0.4,0.2,0.2,0.2,0.2,0.4,0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.2,0.3,0.3,0.2,0.6,0.4,0.3,0.2,0.2,0.2,0.2,1.4,1.5,1.5,1.3,1.5,1.3,1.6,1,1.3,1.4,1,1.5,1,1.4,1.3,1.4,1.5,1,1.5,1.1,1.8,1.3,1.5,1.2,1.3,1.4,1.4,1.7,1.5,1,1.1,1,1.2,1.6,1.5,1.6,1.5,1.3,1.3,1.3,1.2,1.4,1.2,1,1.3,1.2,1.3,1.3,1.1,1.3,2.5,1.9,2.1,1.8,2.2,2.1,1.7,1.8,1.8,2.5,2,1.9,2.1,2,2.4,2.3,1.8,2.2,2.3,1.5,2.3,2,2,1.8,2.1,1.8,1.8,1.8,2.1,1.6,1.9,2,2.2,1.5,1.4,2.3,2.4,1.8,1.8,2.1,2.4,2.3,1.9,2.3,2.5,2.3,1.9,2,2.3,1.8]
        ],
        "desc" : ["centimeters"],
        "smps" : ["s1","s2","s3","s4","s5","s6","s7","s8","s9","s10","s11","s12","s13","s14","s15","s16","s17","s18","s19","s20","s21","s22","s23","s24","s25","s26","s27","s28","s29","s30","s31","s32","s33","s34","s35","s36","s37","s38","s39","s40","s41","s42","s43","s44","s45","s46","s47","s48","s49","s50","s51","s52","s53","s54","s55","s56","s57","s58","s59","s60","s61","s62","s63","s64","s65","s66","s67","s68","s69","s70","s71","s72","s73","s74","s75","s76","s77","s78","s79","s80","s81","s82","s83","s84","s85","s86","s87","s88","s89","s90","s91","s92","s93","s94","s95","s96","s97","s98","s99","s100","s101","s102","s103","s104","s105","s106","s107","s108","s109","s110","s111","s112","s113","s114","s115","s116","s117","s118","s119","s120","s121","s122","s123","s124","s125","s126","s127","s128","s129","s130","s131","s132","s133","s134","s135","s136","s137","s138","s139","s140","s141","s142","s143","s144","s145","s146","s147","s148","s149","s150"],
        "vars" : ["Sepal.Length","Sepal.Width","Petal.Length","Petal.Width"]
     }
  }
  
  
  <-- Create the configuration for the graph -->
  var config = {
     "axisTickFontStyle":"bold",
     "axisTitleFontStyle":"italic",
     "citation":"R. A. Fisher (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics 7 (2) => 179-188.",
     "citationFontStyle":"italic",
     "fontStyle":"italic",
     "graphOrientation":"vertical",
     "graphType":"Dotplot",
     "jitter":"true",
     "marginBottom":"30",
     "smpLabelFontStyle":"italic",
     "smpLabelRotate":"90",
     "smpTitle":"Species",
     "theme":"CanvasXpress",
     "title":"Iris flower data set",
     "xAxis2Show":"false"
  }
  

  <!-- Call the CanvasXpress function to create the graph -->
  var cX = new CanvasXpress("canvasId", data, config);


  
  <-- Functions after rendering graph -->
  cX.groupSamples(["Species"]);
  
</script>
library(canvasXpress)
y=read.table("https://www.canvasxpress.org/data/cX-iris-dat.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE)
x=read.table("https://www.canvasxpress.org/data/cX-iris-smp.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE)
canvasXpress(
  data=y,
  smpAnnot=x,
  axisTickFontStyle="bold",
  axisTitleFontStyle="italic",
  citation="R. A. Fisher (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics 7 (2) => 179-188.",
  citationFontStyle="italic",
  fontStyle="italic",
  graphOrientation="vertical",
  graphType="Dotplot",
  jitter=TRUE,
  marginBottom=30,
  smpLabelFontStyle="italic",
  smpLabelRotate=90,
  smpTitle="Species",
  theme="CanvasXpress",
  title="Iris flower data set",
  xAxis2Show=FALSE,
  afterRender=list(list("groupSamples", list("Species")))
)