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Description
This sample takes advantage of visual variables to render three related variables in the same map. The goal is to depict the areas in the United States where the adults who never went to collegeoutnumber those who did and vice versa. Color is used to depict the dominant populations in each county; in this case, adults who attended at least some college versus those who did not. Counties where adults who attended at least some college outnumber those who didn't are shaded with green. Counties that have more adults who never attended college are shaded with purple.
Opacity is used to show the strength of the dominance of each of those populations. For example, if more than 70% of the adults in acounty never attended college, then the county will be shaded with a very opaque purple. Counties where there are near even numbers of both groups are shaded with a very transparent color.
Size is then used to depict the overall adult population of each county. This shows the audience or user how the population of the county compares with other counties in the U.S. proportionally. While a county may have a lot more adults who never attended college versus those who did, that same county may not have very many adults compared to the majority of counties in the U.S. Adding these additional variables and visualization techniques helps tell the user a more complete story of the subject of the map.
Code
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<meta name="viewport" content="initial-scale=1, maximum-scale=1,user-scalable=no"/>
<title>U.S. College Attendance (2015)</title>
<link rel="stylesheet" href="https://js.arcgis.com/3.29/dijit/themes/claro/claro.css">
<link rel="stylesheet" href="https://js.arcgis.com/3.29/esri/css/esri.css">
<style>
html, body, #map {
height: 100%;
width: 100%;
margin: 0;
padding: 0;
}
#info {
background-color: #000;
z-index: 92;
left: 0;
bottom: 0;
position: absolute;
padding: 10px;
font-family: Segoe UI;
color: #fff;
width: 200px;
border-top-right-radius: 8px;
opacity: 0.8;
max-height: 80%;
overflow-y: scroll;
}
</style>
<script src="https://js.arcgis.com/3.29/"></script>
<script>
var map, collegeLyr, legend, renderer;
require([
"esri/map",
"esri/layers/FeatureLayer",
"esri/symbols/SimpleMarkerSymbol",
"esri/symbols/SimpleLineSymbol",
"esri/Color",
"esri/renderers/UniqueValueRenderer",
"esri/dijit/Legend",
"esri/dijit/PopupTemplate",
"dojo/domReady!"
], function(Map, FeatureLayer, SimpleMarkerSymbol, SimpleLineSymbol, Color, UniqueValueRenderer, Legend, PopupTemplate
) {
var url = "https://services.arcgis.com/V6ZHFr6zdgNZuVG0/arcgis/rest/services/us_county_educational_attainment_pop/FeatureServer/0";
map = new Map("map", {
zoom: 5,
center: [-100, 40],
basemap: "gray"
});
//Set the PopupTemplate so users can compare the stats by county
var collegePopup = new PopupTemplate({
title: "{COUNTY}, {STATE}",
description: "<b>{ATT_COL}</b> adults (ages 25+) in {COUNTY} have attended at least some college in their lifetime. <b>{NO_COL}</b> adults in the same age group have never attended any college courses.",
fieldInfos: [{
fieldName: "ATE_COL_DOM_PER",
label: "Majority group percentage",
format: { places: 0, digitSeparator: true }
}, {
fieldName: "EDUCBASECY",
label: "Total adult population",
format: { places: 0, digitSeparator: true }
}, {
fieldName: "NO_COL",
label: "Never attended any college",
format: { places: 0, digitSeparator: true }
}, {
fieldName: "ATT_COL",
label: "Adults who attended at least some college",
format: { places: 0, digitSeparator: true }
}],
mediaInfos: [{
title: "Adults who attended college versus those who didn't",
type: "piechart",
value: {
fields: ["ATT_COL", "NO_COL"]
}
}]
});
collegeLyr = new FeatureLayer(url, {
outFields: ["ATT_COL_DOM", "ATE_COL_DOM_PER", "COL_ATT_GAP", "EDUCBASECY", "NO_COL", "ATT_COL", "COUNTY", "STATE"],
infoTemplate: collegePopup
});
//Set the default symbol to a SimpleMarkerSymbol so counties
//are renderered with sizeable circles
var defaultSym = new SimpleMarkerSymbol().setOutline(new SimpleLineSymbol().setWidth(0.3).setColor(new Color([128,128,128,0.5])));
var attColSym = new SimpleMarkerSymbol().setColor(new Color("#4daf4a")).setOutline(new SimpleLineSymbol().setWidth(0.3).setColor(new Color([128,128,128,0.5])));
var noColSym = new SimpleMarkerSymbol().setColor(new Color("#984ea3")).setOutline(new SimpleLineSymbol().setWidth(0.3).setColor(new Color([128,128,128,0.5])));
/********************************************************************************
* Use a UniqueValueRenderer to shade each feature by
* a dominant attribute - one of two competing variables:
*
* - Did the majority of adults in <county name> attend at least some college? (green)
* - Or did the majority not attend any college at all? (purple)
*
* Then set a sizeInfo visual variable to indicate the number of adults in each county
* and an opacityInfo visual variable to indicate the strength of the dominance of the
* dominant attribute. If a high % of adults did not attend college then the feature
* will be shaded with a strong, opaque purple. If most adults didn't attend college, but
* don't comprise a high % of the adult population, then the feature will be shaded with a
* transparent purple.
*****************************************************************************/
renderer = new UniqueValueRenderer(defaultSym, "ATT_COL_DOM");
renderer.addValue({
value: "Population 25+ that attended college",
label: "Majority of adults attended at least some college",
symbol: attColSym
});
renderer.addValue({
value: "Population 25+ that never attended college",
label: "Majority of adults never attended college",
symbol: noColSym
});
/**************************************************************************
*
* The sizeInfo visual variable defines the values of the data that will be
* renderered with the minimum size and the maximum size of the symbols. All
* features with values falling in between those values will be scaled
* proportionally between the min and max sizes.
*
* In this case the total adult population is used to size the symbols.
*
**************************************************************************/
var sizeVisVar = {
type: "sizeInfo",
field: "EDUCBASECY", //total adult population 25 years and older
minDataValue: 10000, //counties with <10,000 adults will be assigned the min size
maxDataValue: 1000000, //counties with >1,000,000 adults will be assigned the max size
valueUnit: "unknown",
minSize: {
type: "sizeInfo",
expression: "view.scale",
//The min size of the symbol varies depending on the map scale
stops: [
{ value: 250000000, size: 6 },
{ value: 6000000, size: 6 }, //at a 1:6,000,000 scale, the min size is 6px
{ value: 1000000, size: 4 },
{ value: 200000, size: 2 },
{ value: 1000, size: 2 }
]
},
maxSize: {
type: "sizeInfo",
expression: "view.scale",
//The max size of the symbol varies depending on the map scale
stops: [
{ value: 250000000, size: 50 },
{ value: 6000000, size: 50 }, //at a 1:6,000,000 scale, the max size is 50px
{ value: 1000000, size: 40 },
{ value: 200000, size: 20 },
{ value: 1000, size: 10 }
]
}
};
/**************************************************************************
*
* The opacityInfo visual variable defines the opacity of the features based
* on a field value. The minimum and maximum values of the data are defined
* along with their respective opacity values.
*
* In this case, opacity of the features is determined based on the
* percentage of the the dominant group's population out of the adult
* population in the feature. Since there are only two competing variables,
* the lowest % a dominant group can have is 50%. So we'll set the minimum value
* at 55% with a very low opacity. Features whose dominant group is very strong
* (70% of total adults or more) will receive full opacity.
*
* This will depict the strength of the dominance in each feature.
*
**************************************************************************/
var opacityVisVar = {
type: "opacityInfo",
field: "ATE_COL_DOM_PER",
stops: [
{ value: 55, opacity: 0.1 },
{ value: 70, opacity: 1 }
]
};
//Set the size and opacity visual variables on the UniqueValueRenderer
renderer.setVisualVariables([sizeVisVar, opacityVisVar]);
//Set the renderer on the layer
collegeLyr.setRenderer(renderer);
map.addLayer(collegeLyr);
map.on("load", function(){
//Add a legend to the map
legend = new Legend({
map: map,
layerInfos: [
{
layer: collegeLyr,
title: "U.S. Counties by adult population (25+) and whether the majority of adults attended college",
defaultSymbol: false
}
]
}, "legendDiv");
legend.startup();
});
});
</script>
</head>
<body class="claro">
<div id="map"></div>
<div id="info"><div id="legendDiv"></div></div>
</body>
</html>