Ever wonder how they make those awesome maps you see in the New York Times?

(Glanz et al., 2020)

Very often the creators use a dataviz software application like Datawrapper.

“Datawrapper is an open source data visualization platform which helps everyone create simple, correct, and embeddable charts in minutes” (Datawrapper in 2020 – Reviews, Features, Pricing, Comparison, 2018).

Datawrapper gives you the ability to create three types of maps:


Since my podcast Choosing Your Reflection is an ongoing passion project of mine, I went in search of some wedding data to create some data maps that might be of interest to our listeners.

Keep reading if you’d like to learn some interesting wedding stats and see the visuals I created using Datawrapper.


Weddings are expensive, and depending on where the couple decides to hold their nuptials, they can be REALLY expensive. To get the breakdown by state I used Chris Moon’s article in ValuePenguin (n.d.). Here’s a snapshot of the data.

This type of data can be visually presented using a choropleth map.

Choropleth maps are popular thematic maps used to represent statistical data through various shading patterns or symbols on predetermined geographic areas (i.e. countries). They are good at utilizing data to easily represent variability of the desired measurement, across a region” (DeLorenzo & Dugger, n.d.).

This choropleth map uses shaded areas of the various intensities of the color green to represent the differences in the data; in this case total cost of a wedding.

Data captured from article by (Moon, n.d.)

In my example the darkest shades show the highest cost, so you can very easily see that California, Alaska, Hawaii, and several states in the New England region top the list.

The image above is a screen shot. I think it’s pretty impressive but you can also make your maps interactive in Datawrapper. You can check out my interactive version here.


Now this may seem like it’s the same data, but it’s not. Since the list is limited to the most expensive places, many states were not included in the data. Take a look.

A symbol map is a better choice for this dataset.

“A proportional symbol map is easy for map readers to understand. Multiple variables can be displayed simultaneously on a proportional symbol map. For example, the symbol’s size, symbols color, and symbols a shape can all represent different variables” (OLD-Cartography Chapter 4 Combined – Types of Maps, n.d.).

You can also check out the interactive version of my symbol map for more details.

The largest (and darkest green) symbol falls in around the New York city range ($66,000 – $96,000 range, yikes!).

But wait, wasn’t Hawaii the most expensive place to get married in the first set of data? Absolutely. Since the first dataset was a state average (rather than region like Manhattan) New York actually fell behind Hawaii, New Jersey, DC, Massachusetts, and Connecticut.

How the data is “sliced” makes a difference.

“How easy it is to forget, and how revealing to recall, that map authors can experiment freely with features, measurements, area of coverage, and symbols and can pick the map that best presents their case or supports their unconscious bias” (Monmonier, 2018, p.2).

Maps are used to deliver a message to the viewer. As the receiver you should employ a healthy skepticism towards the visual to ensure you are not being sold a bad bill of goods.

“Choropleth maps have the ability to represent a large amount of data over any amount of space in a succinct and visually appealing manner. However, this method is not ideal for representing data realistically. Pre-existing boundaries limit the map’s ability to display the true fluctuation in statistics throughout an area” (DeLorenzo & Dugger, n.d.).


So let’s pretend money is no object and a couple wants to have their wedding in Manhattan. There are a lot of hotels in New York City, so the couple might want to create a locator map to indicate which hotels they recommend for their guests. Fire up Datawrapper and within a few minutes voilà!

Locator maps are great to show where something is located or happened, e.g. events within a city” (Maps, 2019) .


Want to try it yourself? Here’s a quick video overview to get you started.

(Kokkelink, 2016)


until nxt time …


Cairo, A. (2016). The Truthful Art: Data, Charts and Maps for Communication. New Riders.

Datawrapper. (2019, September 24). Maps. Create Charts and Maps with Datawrapper.

Datawrapper in 2020—Reviews, Features, Pricing, Comparison. (2018, July 30). PAT RESEARCH: B2B Reviews, Buying Guides & Best Practices.

DatawrapperIntro. (n.d.).

DeLorenzo, N., & Dugger. (n.d.). Story Map Journal.

Glanz, J., Carey, B., Holder, J., Watkins, D., Valentino-DeVries, J., Rojas, R., & Leatherby, L. (2020, April 2). Where America Didn’t Stay Home Even as the Virus Spread. The New York Times.

How to create a choropleth map—Datawrapper Academy. (n.d.).

How to create a locator map—Datawrapper Academy. (n.d.).

How to create a symbol map—Datawrapper Academy. (n.d.).

Kokkelink, D. (2016, April 8). Create a Datawrapper Map in three minutes—YouTube.

Maps. (2019, September 24). Create Charts and Maps with Datawrapper.

Marchese, C. (n.d.). Maps.

Monmonier, M. (2018). How to Lie with Maps. The University of Chicago Press.

Moon. (n.d.). Average Cost of a Wedding: By Feature and State. ValuePenguin.

OLD-Cartography Chapter 4 Combined—Types of Maps. (n.d.). ArcGIS StoryMaps. Retrieved August 2, 2020, from

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