Color Coded Zip Codes

I started with a US ZIP code database which provides a .csv for every ZIP code in the US. I dusted off Google Colab, and imported the file. By mapping ZIP code numbers to a continuous color gradient from red to purple, we can create a full spectrum of data points where the color corresponds to the magnitude of the ZIP code, and we can treat longitude and latitude values as x and y coordinates. See for yourself below:

Note that I am only including the Contiguous US (sorry Guam). I added the code I used to the end of this project so feel free to tinker with it yourself. I would love to hear what other trends I missed in this brief analysis.

I have not been able to find a map like this of its kind online. Essentially what we have created is a ZIP code heat map. It is interesting to me how the pattern zig zags through the US, starting in the Northeast, but not following a precise East to West movement. It is also interesting how this map indirectly shows high population areas, as there are more ZIP codes in those areas. Of course the East coast, California, Texan cities, etc. are all well-illuminated. 

In case it is not clear, there is no actual map of the US in this image, just individual points. Still, we can make out patterns, cities, and even some state lines (Montana/Idaho is especially clear). My mind is tricking me into seeing land marks such as the Mississippi River, perhaps because there are simply more people who settled close to the river. I marked up the map for some of these trends below):

Based on the above realization of population centers, I created another map where each dot size is proportional to the number of people in each ZIP code. Interestingly, while this did further illuminate population density, it also illuminated ZIP codes with a large area, since in less populous areas, the ZIP codes span a much larger distance. Boise, the blue dot below at (-116, 43), is a good example of this. Boise has just north of 200,000 inhabitants, but appears as bright as cities with 500,000+. Here is the population-normalized graph:

The main differences I see here is that the big cities are far brighter, but areas like Denver, Salt Lake City, and Las Vegas appear as massive anomalies in otherwise barren areas. In the first map I could not really make these areas out. 

It turns out the largest ZIP codes by population are 08701 in New Jersey and 92336 in California. A little further down that list, the 23rd largest ZIP code by population was 73099 in Oklahoma. In fact, combing through the first 100 largest, many of the ZIP codes are not in large Metro areas. This shows that size of ZIP code does not necessarily correspond to population density.

However, the ZIP code population distribution is skewed heavily right, with a mean of 28,103 people, a median of 2,799 people, and a standard deviation of 16,047 people. Here is the distribution:

I do not know how this is possible and did not dig down the rabbit hole, but apparently there are a few ZIP codes currently with zero people, including 19716, 29423, and 44901 in Deleware, South Carolina, and Ohio respectively. Feel free to verify that and let me know if I am missing something.

Next, I wanted to look at population on a 3D plot. Keeping x and y axes the same, and making z correspond to population, we can check if this provides any additional insights. Plot below:

Admittedly, the sheer number of lines makes this a little confusing and unhelpful. The color still corresponds to the ZIP code magnitude, and thus looks like a bit of a mess. To clear it up a bit, we can reduce the number of data points to 1,000. See below.