# Archive for the ‘Maps’ Category:

### Tracking US Coronavirus Cases by State

Posted In: Maps

The coronavirus (SARS-CoV-2) is literally affecting the entire globe right now and changing the way we live our lives here in the US and all over the world.

There are quite a number of different coronavirus-related dataviz out there, but as we shelter-in-place I wanted to add a map that looked at a number of different metrics that tell us about the coronavirus pandemic by US states and look at those metrics on a population basis.

There are a number of data sources that I’ve found that publish data about the coronavirus and the resulting disease (Covid-19) in the United States:

This map is based on the data compiled from covidtracking.com, partly because it has a good API and also lists testing, cases and deaths. The data I’ve included on the map is:

• Numbers of coronavirus cases – i.e. tested positive for virus
• Numbers of coronavirus tests administered
• Numbers of deaths due to coronavirus

Each of these is also calculated per 100,000 population in the state:

• Numbers of coronavirus cases per 100k people- i.e. tested positive for virus
• Numbers of coronavirus tests administered per 100k people
• Numbers of deaths due to coronavirus per 100k people

These latter metrics are important because numbers of cases or deaths can be obscured by small or large populations but per capita data (or per 100k capita data) can point out interesting outliers.

It is important to note that the data is far from perfect. There is probably significant underreporting of tests, cases and deaths. The data is a collection for the various local and state agencies that are working hard to deal with the medical, social and political ramifications of the pandemic, while also collecting data. We don’t know how many Americans have coronavirus because of lack of testing.

Also important is that the number of positive cases is a function of how much testing is taking place so cases does not necessarily represent the exact prevalence of the virus, though there will probably be good correlation between cases and actual coronavirus infections. Luckily it sounds like tests are becoming more widely available so hopefully those numbers will go up sharply.

For more information about the virus and the disease and data collection, you can find good information on the CDC website.

Sources and Tools:

Coronavirus cases are obtained from covidtracking.com. And the visualization was created using javascript and the open source leaflet javascript mapping library.

### Mapping US Cities By Name

Posted In: Geography | Maps

This map of the United States visualizes over 28,000 cities in the 50 states. The interactive visualization lets you type in a name (or part of a name) and see all of the cities that contain those string of letters. The points on the map show the geographic center of each city.

For example, if you type in “N”, you will highlight all cities that start with an N in the US. As you type in another letter (e.g. “e”, it will narrow down the cities that begin with those two letters (“Ne”). It will progressively narrow down the number of cities as you type in more letters. You can see an scrollable list of the cities (ordered by city population) that contain the string of letter that you have typed.

If you hover over a highlighted city, you can see the name of the city.

You can click on the check box to show or hide the outlines of the states.

You can “Show City List” to show the list of cities that contain the string of letters you have typed.

Sources and Tools:

City name and location data was downloaded from simplemaps.com. And the visualization was created using javascript and the open source leaflet javascript mapping library.

### US County Electoral Map – Land Area vs Population

Posted In: Maps | Uncategorized | Voting

#### County-level Election Results from 2016

This interactive map shows the election results by county and you can display the size of counties based on their land area or population size.

A little while ago, I made a map (cartogram) that showed the state by state electoral results from the 2016 Presidential Election by scaling the size of the states based on their electoral votes. The idea for that map was that by portraying a state as Red or Blue, your eye naturally attempts to determine which color has a greater share of the total. On a normal election map of the 2016 Election, Red states dominate, especially because a number of larger, less populated states happen to vote Republican. That cartogram changed the size of the states so that large states with low population, and thus low electoral votes tended to shrink in size, while smaller states with moderate to larger populations tended to grow in size. Thus, when your eyes attempt to discern which color prevails, the comparison is more accurate and attempts to replicate the relative ratio of electoral votes for each side.

This map looks at the election results, county by county. An interesting thing to note is that this view is even more heavily dominated by the color red, for the same reasons. Less densely populated counties tend to vote republican, while higher density, typically smaller counties tend to vote for democrats. As a result, the blue counties tend to be the smaller ones so blue is visually less represented than it should be based on vote totals. More than 75% of the land area is red, when looking at the map based on land areas, while shifting to the population view only about 46% of the map is red. Neither of these percentages is exactly correct because each county is colored fully red or blue and don’t take into account that some counties are won by a large percentage and some are essentially tied. However, the population number is certainly closer to reality as Trump won about 48.8% of the votes that went to either Trump or Clinton.

#### Instructions

This tool should be relatively straightforward to use. Just click around and play with it.
The map has a few different options for display:

• Hide Circles – just shows the county map
• Show land circles – where the area of the circle matches the area of the county itself, though obviously shaped like a circle. The counties are colored red or blue depending on whether Trump or Clinton won more votes in that county.
• Show population circles – where the area of the circle matches the relative population of the county itself. More populated counties will grow larger while less populated counties will shrink. The counties are colored red or blue depending on whether Trump or Clinton won more votes in that county.
• Selecting the No County Overlap checkbox will spread out all of the circles so you can see them all. The total displayed area of the county circles is the same in either land and population view, though if the circles are overlapping, you may see less total colors.

#### Visualization notes

This was my second attempt at using d3 to generate visualizations. I typically use leaflet to do web-based mapping but I wanted the power of d3 which has functions for the circles to prevent overlapping. This map was inspired by Karim Douieb’s cool visualization of 2016 election results. I modified it in a number of different ways to try to make it more interactive and useful.

This visualization does not actually simulate the collisions between the circles on your browser. It is a bit computationally taxing and causes my computer fan to turn on after awhile. So instead I ran the simulation on my computer and recorded the coordinates for where each circle ended up for each category. Then your browser is simply using d3 transitions to shift positions and sizes of the circles between each of the maps, which is simpler, though with 3142 counties, it can still tax the computer occasionally.

Data and Tools
County level election data is from MIT Election Lab. Population data used is for 2018. The visualization was created using d3 javascript visualization library.

### National Park Service Voronoi Map

Posted In: Maps

This map divides up the Continental United States into different regions depending on which National Park (or other National Park Service site) is closest to it. It is based on a straight-line (‘as the crow flies’) distance between locations rather than along road networks. It is an example of a Voronoi Diagram, which is subdivided into different regions based upon the distance between points of interest. Everything within a subregion is closer to the point defining the region than any other point.

Hover over the circle points to see the name of the park. The map has a dropdown menu that lets you choose between the following types of locations in the National Park Service:

• National Parks
• National Historic Sites
• National Memorial Sites
• National Monuments
• National Seashores/Lakeshores
• National Recreation Areas
• National Battlefields
• National Military Sites
• National Scenic Areas

For National Parks, there is a high concentration of National Parks in the Western US, especially around the Southwestern US and running up the Pacific Coast. As a result, in these areas, the Voronoi regions are fairly small. The Southwest is also home to a high concentration of National Monuments. There are only few parks in the Eastern US and so the Voronoi regions are correspondingly large. Looking at National Historic Sites, the situation is flipped somewhat, with a high concentration of historic sites in the eastern US, and specifically the Northeast.

Let me know in the comments which park you are closest to and which park you last visited.

Tools and Data Sources
Locations of each of the National Park Service sites comes from the National Park Service. The map was created using the Leaflet javascript mapping library and the Voronoi diagram using the Turfjs javascript, geospatial analysis library.

### Zip Code Map of the United States

Posted In: Maps

This zip code map of the United States visualizes over 42,000 zip codes in the 50 states. Zip codes are five digit postal codes used for mail delivery in the US. The points on the map show the geographic center of each zip code. The interactive visualization lets you type in a zip code and will show you where that zip code lies on the map. As you begin to type in the zip code, the map will highlight all the zip codes that begin with those numbers.

For example, if you type in “0”, you will highlight all zip codes that start with the zero in the Northeastern US. This will represent about 10% of the zip codes in the US. When you type in another number, it will narrow down the zip codes that begin with those two digits (approximately 1% of zip codes). It will progressively narrow down the number of zip codes as you type in more numbers, until you get to a full 5 digit zip code that represents 1 out of almost 43,000 zip codes (0.002% of zip codes). The map will then tell you the name of the city that that zip code is in.

You can explore how zip codes are distributed across the US by typing in different 1 and 2 digit numbers. You can also click on the check box to show or hide the outlines of the states.

Sources and Tools:

Zip code data was downloaded from opendatasoft.com. And the visualization was created using javascript and the open source leaflet javascript mapping library.

### Assembling the USA state-by-state with state-level statistics

Posted In: Maps

#### Watch the United States assemble state by state based on statistics of interest

Based on earlier popularity of the country-by-country animation, this map lets you watch as the world is built-up one state at a time. This can be done along a large range of statistical dimensions:

• Name (alphabetical)
• abbreviation
• Date of entry to the United States
• State Population (2018)
• Population per Electoral Vote (2018)
• Population per House Seat (2018)
• Land Area (square miles)
• Population Density (ppl per sq mi) (2018)
• State’s Highest Point
• Highest Elevation (ft)
• Mean Elevation (ft)
• State’s Lowest Point
• Lowest Point (ft)
• Life Expectancy at Birth (yrs)
• Median Age (yrs)
• Percent with High School Education
• Percent with Bachelor’s Degree
• Residential Electricity Price (cents per kWh) (2018)
• Gasoline Price ($/gal) Regular unleaded (2019) • State Gross Domestic Product GDP ($Million) (2018)
• GDP per capita (\$/capita)
• Number of Counties (or subdivisions)
• Average Daily Solar Radiation (kWh/m2)
• Birth rate (per thousand population)
• Avg Age of Mother at Birth
• Annual Precipitation (in/yr)
• Average Temperature (deg F)
• These statistics can be sorted from small to large or vice versa to get a view of the US and its constituent states plus DC in a unique and interesting way. It’s a bit hypnotic to watch as the states appear and add to the country one by one.

You can use this map to display all the states that have higher life expectancy than the Texas:
select “Life expectancy”, sort from “high to low” and use the scroll bar to move to the Texax and you’ll get a picture like this:

or this map to display all the states that have higher population density than California:
select “Population density, sort from “high to low” and use the scroll bar to move to the United States and you’ll get a picture like this:

I hope you enjoy exploring the United States through a number of different demographic, economic and physical characteristics through this data viz tool. And if you have ideas for other statistics to add, I will try to do so.

• Population https://en.wikipedia.org/wiki/List_of_states_and_territories_of_the_United_States_by_population
• Educational attainment https://nces.ed.gov/programs/digest/d18/tables/dt18_104.88.asp
• Highest points https://geology.com/state-high-points.shtml
• Life expectancy https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_life_expectancy
• Median Age http://www.statemaster.com/graph/peo_med_age-people-median-age
• Land area https://statesymbolsusa.org/symbol-official-item/national-us/uncategorized/states-size
• Mean elevation https://www.census.gov/library/publications/2011/compendia/statab/131ed/geography-environment.html
• Electricity price https://www.chooseenergy.com/electricity-rates-by-state/
• Gasoline price https://gasprices.aaa.com/state-gas-price-averages/
• GDP https://www.bea.gov/data/gdp/gdp-state
• Sunlight North America Land Data Assimilation System (NLDAS) Daily Sunlight (insolation) for years 1979-2011 on CDC WONDER Online Database, released 2013. Accessed at http://wonder.cdc.gov/NASA-INSOLAR.html on Jun 14, 2019 1:37:15 PM
• Births United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), Division of Vital Statistics, Natality public-use data 2007-2017, on CDC WONDER Online Database, October 2018. Accessed at http://wonder.cdc.gov/natality-current.html on Jun 14, 2019 1:53:58 PM
• Precipitation North America Land Data Assimilation System (NLDAS) Daily Precipitation for years 1979-2011 on CDC WONDER Online Database, released 2013. Accessed at http://wonder.cdc.gov/NASA-Precipitation.html on Jun 26, 2019 3:30:40 PM
• Temperature http://www.usa.com/rank/us–average-temperature–state-rank.htm

The map was created with the help of the open source leaflet javascript mapping library