Creating a Demographic Map – The Mystery of Trinity County

Last week I created a new Map Gallery posting for www.mapBusinessOnline.com .  The process, as usual, was quite easy and interesting. I thought I’d share my business mapping work flow and link to the map for people to see how I did it.  Demographic data is used in business mapping software to reveal business trends and tendencies in selected areas of interest.

First, I combed through the latest demographic data update in Map Business Online. This update was released during the last week of July, 2016.  There’s a whole group of new categories available and the existing categories were updated.

I noticed a set of new US Census Bureau categories that seemed interesting:

  • Families (2014) Male households, no wife present (Families/Male)
  • Families (2014) Female households, no husband present (Families/Female)

I wanted to explore this new category a little. So, I decided to create a ratio for Families/Male (dividend) to Families/Female (divisor), figuring the ratio would likely be a decimal quotient in most cases and thus easy to display on the map. I was right, for the most part, but interestingly there actually where areas where the males headed families outnumber the female headed families by a wide margin.

Calculate Data Columns

To build my ratio for color shading I needed to first calculate data columns. I did this in Map & Data, selecting the zip code layer and choosing Manage Calculated Data Columns.  I named my resultant layer and chose the Families/Male category of Census Data over the Families/Female category, select the “divide” option in between them.

Next I choose the Color Code Map option along the master toolbar and selected the zip code option. In the top drop down I selected Calculated Data and the Male/Female Fams option I had just created in the above step.  To keep things simple, I chose a range of 3 color groups:

  • Orange – for ratio result 0 to .75
  • Red – for ratio result .75 to .99
  • Blue – for result 1.0 to 21

As I applied the color code options Map Business Online presents the low and high numeric range by zip code. I found it odd that 21 was shown as the top numeric range in the data. This means that based on the data and the selected map layer the zip code with the largest ration number across the nation holds 21 Families/Male over Families/Female.  But we’ll look at that more in a minute.

With my color coding processed I decided to edit my Map Legend a bit. You just click the little Edit Gear in the upper right of the Map Legend to edit. I took out all legend layers except the zip code layer. Why leave superfluous layers in there? I also removed the “Other” color group category. Always keep your map focused. Never give the “I always ask a lot of questions” person, the opportunity to interrupt your presentation.

Finally, I decided it might be useful to include some additional demographic data for reference in the Zip Code label – both on the Zip Code label itself and in the pop-up balloon which occurs upon cursor hover. So I appended the zip code label with population, Families/Male and Families/Female totals, and I included the calculated ratio results for each zip as well.  References like this do add clutter to the map, but they also provide an immediate reference that might answer questions in the map viewer’s mind.

The actual Male Families no wife present – Map

Investigating the Odd

Getting back to that 21 number in the color coding range. When Map Business Online presents the expected range it is saying to the user (in this case), “The largest number I see across the entire USA Zip Code layer for your ratio per zip code is 21.” And this was true for a zip code in the County of Trinity in Northern California.

I could tell this was true because I used the Data Window as an investigation tool. Selecting the Zip Code layer in the Data Window, I clicked More Data. I then added all the pertinent data layers I’d been working with to my Zip Code layer, including the Calculate Data Ratio – Male/Female Single Parent Families. Once the data was set, I simply clicked the Heading in that Calculated Data column to arrange the data in descending order. There were a bunch of blanks because the Female Single Parent households showed as Zero and we all know anything divided by Zero freaks gives a null answer. But after the nulls,  the first number to come up was in fact the 21 associated with the town of Hyampom in Trinity County, CA.

Hyampom

That “21” means, as you can see in the row of data, for that zip code Male Headed Single Parent Families with no wife present, out number Female Single Parent Families with no husband present, by 21 to 1. And the next level is 13.5, in just one zip code over! That’s just weird to me.  You can see on the map the across the nation most zip ratio results are between 1 and 2.

I tried calling Trinity County but they could not justify my number for me. On http://www.countyhealthrankings.org I found an interesting statistic. Trinity county leads California in premature lives lost before the age of 75 with a rate of 10,300 per 100,000 people. That’s a lot.

I’m wondering if, based on the family stats we were working with, those deaths may be disproportionately affecting women?  Or perhaps the Census Bureau data for those two zip codes are simply wrong? If you follow the Wiki link above to the Hyampom town write-up there’s a discrepancy in the Census data.

No answer yet, but this entire mapping exercise serves to show that maps expose trends. And the moral of the story, check your data. Question your results before you submit your map.

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