COVID-19 United States Data Visualizations Using Heat Maps
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About Page

Hello! This is a web app I made using python and Django. The maps found on this site show covid spread by county, state, and country. Additionally, there is a US map that shows Rt values. I made the maps using plotly.

Dataset Info

I used covid data from the repo found at kaggle. The dataset is the NYT's historic covid data per county that is kept updated. I used census data from the US Census Bureau. I used covid Rt data from the website found at rt.live, which is a great resource for historic Rt data. For the global total case map I used one of the John Hopkins datasets found at The Humanitarian Data Exchange website. For the global cases per 100k population map I used the same John Hopkins dataset above but also the population dataset found at kaggle. The population dataset is taken from Worldometers.

GIFs Page Info

This page has all the GIFs for each type of map. I am not planning to do a GIF or historic maps for the state cases map. I think the county maps are more interesting and hold better data.

Covid County Scale Info

The covid by county maps are scaled to log10 when looking at infections per 100k population. The reason for using per 100k population is to scale the infection rate to the actual population size of a county. The reason for using log10 is to better show the difference between areas of infection. A log10 scale means that the value is a "1" with trailing zeros equal to the value. For example, on the log10 scale the number "5" translates to 100,000 and the number "2" translates to 100. As the log10 numbers increase on the scale, the growth of covid grows exponentially.

Covid State Scale Info

The covid by state maps are scaled to log10 when looking at infections per 100k population. The reason for using per 100k population is to scale the infection rate to the actual population size of a county. The reason for using log10 is to better show the difference between areas of infection. A log10 scale means that the value is a "1" with trailing zeros equal to the value. For example, on the log10 scale the number "5" translates to 100,000 and the number "2" translates to 100. As the log10 numbers increase on the scale, the growth of covid grows exponentially.

Covid Rt Scale Info

The site I was pulling Rt data from, rt.live, has since shutdown. I am keeping the historic data as a GIF. As previously described on the rt.live site, "Rt represents the effective reproduction rate of the virus calculated for each locale. It lets us estimate how many secondary infections are likely to occur from a single infection in a specific area. Values over 1.0 mean we should expect more cases in that area, values under 1.0 mean we should expect fewer."

Per Capita Info

I was using the rt.live site to pull the per capita info. As rt.live has shutdown, I am only keeping the historic data as a GIF. At the request of some friends, I have added in per capita maps. These include both a raw per capita value but are graphed based on the per capita per 100k population in each state. The scale I used is 0 - 80 to account for the variance in the current per capita numbers. This scale might have to be adjusted if many states show higher per capita rates.

Global Maps Info

There is a current global map with total cases by country/region to get a good perspective on how the US stands compared to other countries. The scale is log10 to better show the difference among countries. See the Covid County Scale Info section above for details on how to read this kind of scale. Currently Somaliland, Turkmenistan, North Korea, and Antarctica have no reported data, which is why they are grey/blank on the map.

There is also a current global map with cases per 100k population. The scale for this is a 1og10 scale. See the Covid County Scale Info section above for details on how to read this kind of scale. This map is missing a chunk of countries as the population data I am using is less than the data on countries with covid.

Code To Make Your Own

Here is my github for the code that generated these maps. The code allows you to both save images and make gifs of the data.