2b:null 2c:["$","title",null,{"children":"Plot: Walmart Voronoi | CS 181AP Data Visualization | Observable"}] 31:T451,walmart_voronoi = Plot.plot({ title: "Walmart Store Growth in the U.S.", subtitle: "Each dot represents a store and its color indicates the decade it was opened. Hover over a store to see the opening date!", caption:htl.html`Adding on to fork from Walmart Voronoi. Data source: Holmes, Thomas J. Store Openings Dataset (store_openings.csv). 2010, University of Minnesota, Federal Reserve Bank of Minneapolis, and NBER`, projection: "albers-usa", color: { legend: true, scheme: "GnBu", type: "quantize", domain: [1960, 2010], }, marks: [ Plot.geo(nation, { fill: "#d4d2d2", }), Plot.geo(statemesh, {stroke: "white"}), Plot.dot(walmarts, { x: "longitude", y: "latitude", fill: d => d.date.getFullYear(), r: 1.5, }), Plot.geo(nation), Plot.voronoiMesh(walmarts, {x: "longitude", y: "latitude", stroke: "white", title: d => formatTime(d.date), tip: true}) ] })32:[{"id":"e34d00a1441938da12b88603d3f2f6012369d8f1bec25ed9fb6db16c0d16d5ea4861bd6066275b8de9cc4ea3db735741008c4245e8142cd10c13ffa4c9741873","href":"https://static.observableusercontent.com/files/e34d00a1441938da12b88603d3f2f6012369d8f1bec25ed9fb6db16c0d16d5ea4861bd6066275b8de9cc4ea3db735741008c4245e8142cd10c13ffa4c9741873","name":"us-counties-10m.json","type":"application/json","lastModified":1762498213508.568,"size":842143},{"id":"3711de2a6d1c44df145f2a29f8744771e113672517ed5d84b0fbf76740b423e060d96eb2ae76bc28806b2d3cef37083de88309b3c86baef2807f0e27b2d045f3","href":"https://static.observableusercontent.com/files/3711de2a6d1c44df145f2a29f8744771e113672517ed5d84b0fbf76740b423e060d96eb2ae76bc28806b2d3cef37083de88309b3c86baef2807f0e27b2d045f3","name":"walmarts.tsv","type":"text/tab-separated-values","lastModified":1762498213508.568,"size":99268}] 2f:{"id":"27d6775f9546242e","slug":null,"title":"Plot: Walmart Voronoi","thumbnail":"705260298f5eed2b654722dcbfcc2494cd7e6acf72d66c317e267f85ad5f2b98","access_level":"public","create_time":"$D2025-11-07T06:50:13.508Z","update_time":"$D2025-11-09T04:58:37.188Z","view_time":null,"first_public_time":"$D2025-11-09T05:04:15.228Z","has_unpublished_edits":null,"fork":{"id":"d088e35a41e26627","slug":"plot-walmart-voronoi","title":"Plot: Walmart Voronoi","owner":{"id":"f35c755083683fe5","login":"observablehq","name":"Observable"}},"stars":0,"starred":false,"owner":{"type":"team","id":"e602a4cc91f94fe5","login":"hmc-datavis-fall2025","name":"CS 181AP Data Visualization","avatar_url":"https://avatars-next.observableusercontent.com/24bcc4609d77ce717ddd7dc599710360ba00df258ffd8c54b83a2798539fb4b1","tier":"education_2026"},"version":87,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"eec6a60a348f38d9","login":"kalyani-nair","name":"Kalyani Nair","avatar_url":"https://avatars-next.observableusercontent.com/329b2f596b4e2f805a2337a641ea510987c355936e81cf27a1148c824be18f9e","tier":null}],"members":[{"type":"individual","id":"eec6a60a348f38d9","login":"kalyani-nair","name":"Kalyani Nair","avatar_url":"https://avatars-next.observableusercontent.com/329b2f596b4e2f805a2337a641ea510987c355936e81cf27a1148c824be18f9e","tier":null,"role":"editor"},{"type":"team","id":"e602a4cc91f94fe5","login":"hmc-datavis-fall2025","name":"CS 181AP Data Visualization","avatar_url":"https://avatars-next.observableusercontent.com/24bcc4609d77ce717ddd7dc599710360ba00df258ffd8c54b83a2798539fb4b1","tier":"education_2026","role":"viewer"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Plot: Walmart Voronoi","cells":[{"id":0,"value":"

Plot: Walmart Voronoi

Observable Plot › Gallery

\n\n# Walmart Voronoi\n\nThe [Voronoi](https://observablehq.com/plot/marks/delaunay) diagram of the Walmart stores in the contiguous U.S. shows the catchment area of each point.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":77,"value":"formatTime = d3.utcFormat(\"%B %d, %Y\");","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":8,"value":"us = FileAttachment(\"us-counties-10m.json\").json()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":12,"value":"nation = topojson.feature(us, us.objects.nation)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"walmarts = FileAttachment(\"walmarts.tsv\").tsv({typed: true})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":52,"value":"statemesh = topojson.mesh(us, us.objects.states)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W32","stdlib":"1"}} 30:"$2f:body"