Best Data Viz
Geospatial

Dot Map

One dot per occurrence, showing density and distribution of point events.

Business Locations

60 coffee shops, restaurants, and bars across the US

View data (62 rows)
Chart data table: Business Locations
TypeLocation
CoffeeNew York
BarBrooklyn
RestaurantJersey City
CoffeeNewark
RestaurantBoston
CoffeeCambridge
BarProvidence
RestaurantHartford
BarPhiladelphia
RestaurantBaltimore
CoffeeWashington DC
BarArlington
RestaurantRichmond
CoffeeCharlotte
BarRaleigh
RestaurantAtlanta
CoffeeCharleston
RestaurantJacksonville
CoffeeOrlando
BarMiami
RestaurantTampa
BarNashville
RestaurantMemphis
CoffeeLouisville
RestaurantIndianapolis
BarCincinnati
CoffeeColumbus
RestaurantCleveland
BarPittsburgh
RestaurantDetroit
RestaurantChicago
BarMilwaukee
CoffeeMadison
RestaurantMinneapolis
CoffeeSt. Paul
BarSt. Louis
RestaurantKansas City
CoffeeOmaha
BarDes Moines
RestaurantDallas
CoffeeFort Worth
CoffeeAustin
RestaurantSan Antonio
RestaurantHouston
BarNew Orleans
CoffeeOklahoma City
BarDenver
CoffeeBoulder
RestaurantSalt Lake City
CoffeePhoenix
RestaurantTucson
BarLas Vegas
CoffeeAlbuquerque
CoffeeSan Diego
CoffeeLos Angeles
BarLong Beach
CoffeeSan Jose
RestaurantSan Francisco
BarOakland
CoffeeSacramento
CoffeePortland
CoffeeSeattle
Make a dot map with your data

Use a dot map when…

  • Individual event locations
  • Crime maps, store locations, species sightings

Avoid when…

  • Aggregated regional data (use choropleth)
  • Very dense data (overlapping dots)

Data it needs

PropertyValue
Min Rows5
Min Columns3
Column Types
stringnumbernumber
NotesTwo of the columns are longitude and latitude (or a place-name string the renderer geocodes); the third is an optional category.

Visual anatomy

Marks
circle
Channels
position (lat/lon)color-hue
Axes
geographic coordinates

Guiding principles

Consider instead

Common mistakes

  • Overplotting in dense areas

  • No basemap context

History

John Snow's 1854 cholera map is the most famous early dot map.

Accessibility notes

Pair category color with shape or label so readers who can't distinguish hues still get the encoding. Provide a sorted location/category text list as alternative.

Related reading

Got data? Let's see what works.

Drop your CSV. You'll get a Dot Map plus four alternatives - ranked by which one actually fits your data best.