How Popular Is Your Name?

Introduction

This story begins in 1987, or maybe 1988 (I cannot be totally sure). Yep, that is 29 or 28 years ago. If you need more accuracy, I’ll have to check my log book from that time.

My buddy, Greg Miller, and I created the NABI that year. The NABI is the Nichole, Ashley, Brittany Index. What is that, you ask?

Well, back then there was a thing called a newspaper. We didn’t have a thing called the internet. For entertainment around the office, we used to read the newspaper. In fact, we used to look at the section that contained the newborn baby names. You can tell that there wasn’t much to do back in the early days, deep in the hollers of Knoxville, TN.

Later on I might share other stories of my escapades with Greg, which included radioactive waste burial grounds, biological waste trenches, radioactive deer, watermelons, soil sampling, heavy rains, and slippery slopes. Until that time, I’ll leave those words within your own imagination.

The NABI

Being the quantitative guys that we were, we noticed that there were a lot of baby girls being born with the names Nichole, Ashley and Brittany. In fact, there were so many of them, that we created the NABI.

Each day we charted the NABI (just like you might do with a stock price) on a whiteboard and were astounded by our finding. We wondered why so many people were giving these three names to these baby girls. Of course, we had no way of knowing if the NABI was just a local phenomenon or a country-wide trend.

Fast Forward Three Decades

Being of sound body and mind (I think), this memory recently popped into my head. I had no control over that event, but I could control what happened next. Well, since I have Alteryx and Tableau at my disposal, I thought I’d do a retrospective study on the NABI.

I wanted to know if Greg and I had actually discovered something significant by simply using the power of observation. Back then, we didn’t have these fancy data mining tools at our disposal and we didn’t have the ability to gather this type of data.

So I did a little data mining recently during my weekend downtime. I collected the annual lists of the top 1000 US baby names from 1880 to 2015. After a quick pass through Alteryx, I fired the results into Tableau and had a great time looking at the data. Some of the insights I identified in this data set are simply fascinating. I am sure more blog posts will be written in this series.

The NABI Results

I must conclude that the NABI was a country-wide phenomenon that we discovered within the little subset of the country called “East Tennesse”. Although I cannot pinpoint why these names came into vogue at that time, Figure 1 assures me that they did. Although the popularity of Nicole existed longer than the other two names, those two names peaked just at the time we recognized the pattern.

Figure 1 – The beautiful coalescence of three girl names that formed the NABI. We were correct, way back in 1987-1988.

Characteristics of The Name Data Set

The data set I assembled (Click here for original data source) contains the following:

272,000 records, spanning 1880 to 2015 (136 years)
the top 1000 male names per year
the top 1000 female names per year
3,566 distinct male names
4,208 distinct female names
the rank of each name per year
a running total for each name by gender
a record counter for each name by gender

If anyone wants the Excel file of this info, just ask.

How Popular is My Name?

Well, my first name happens to be Kenneth. As shown in Figure 2, that name happened to enjoy an 80-year run in the top 50 boy names. I also happened to be born near the peak popularity of Kenneth. At this time, I have no idea why the name of Kenneth started gaining such popularity from 1911 to 1912. A little research is now in order.

Figure 2 – The popularity of my name (Kenneth). It had an amazing 80-year run of being in the top 50 boy names.

The Most Popular Names

Figure 3 shows the top 30 most popular names. To see how their popularity has changed over time, read the next section. Also, the astute observer will notice that there is a bit of a data quality problem in this data set. Can you spot what the problem is?

Figure 3 – The top 30 names by gender. With only 7 girl names in the top 30, it is clear that there is a lot more diversity in girl names than boy names.

The answer to this question is obvious. It is likely that whomever entered the data to create these records made a lot of mistakes in assigning gender to the baby. Either that or a lot of parents mis-named their new babies!

Here is a funny aspect to this data. Although Johnny Cash sang a song about a boy named “Sue”, there are no boys named “Sue” in this database! I know this because I checked it!

Also, in 1895 there were seven boys name “True”. Yes, this is true! Or maybe not!

Lastly, on the data front, if you try to use the date 1/1/1900, you will find that Tableau will map it to 1/1/1899. Yes, this is also true. There was a Y2K problem before Y2K existed. To avoid the problem, change the data from 1/1/1900 to 1/2/1900. This will solve your problem.