At first I found this fascinating -- &quot;data shows that CEOs marry assistants&quot; is a good narrative about gender attitudes towards marrying.  But as I played with it, I was kind of bummed to learn: most male professions tend to marry assistants, since there are a lot of married female assistants (second only to teachers for females).<p>I did a quick search for who male Programmers, Executives, and Janitors marry (tried to pick a diverse set), and then filtered out the top five female occupations in this data (Teachers, Assistants, Nurses, Misc Managers, Salespersons).  The remaining results were: male Programmers marry female Programmers, male Executives marry female Executives, male Janitors marry female Janitors or female Maids.<p>So I whipped up a script that, instead of measuring the absolute frequency, normalizes the data set against how often the target occupation gets married to.  ie instead of just counting common pairings, it measures &quot;how much more likely is profession X (compared to the general population) to marry profession Y?&quot;.<p>For male CEOs, the result is: they marry other CEOs.  Male CEOs are 12x more likely to marry a female CEO than males in other professions are.  They are also 12.6x more likely to marry embalmers!  7x more likely to marry Announcers, 5.3x more likely to marry &quot;Dancers and Choreographers&quot;, and 4.9x more likely to marry &quot;Public Relations and Fundraising Managers&quot;.  They are only 1.2x more likely to marry a Secretary than other males are.<p>For male programmers, it is similar: male programmers are 20x more likely to marry female programmers than other male occupations are.  This is because only 0.2% of men marry female computer programmers, but 3.4% of male programmers do.  Male programmers also marry female Materials Engineers (20x more likely), Information Security Analysts (13x), &quot;Surveyors, Cartographers, and Photogrammetrists&quot; (10x), and &quot;Architects, Except Naval&quot; (8x).<p>I also picked one final way of slicing it: &quot;how many more of these marriages did we see than expected&quot; (expected based on the relation frequencies of the two occupations).  This is another way of removing &quot;well we would expect a lot of these marriages&quot;, but in a way that is less geared towards low-occurrence matches like CEO-Embalmer.  For CEOs, the results are: CEOs, Misc Managers, Elementary and Middle School Teachers, Secretaries, Accountants and Auditors.  For Programmers, it&#x27;s: Programmers, Misc Managers, Other Teachers and Instructors, Software Developers, Accountants and Auditors.<p>Anyway, this isn&#x27;t to say that these other ways of looking at the data are any &quot;better&quot;, they&#x27;re just answers to different questions.<p>I threw up the code in a gist -- sorry it&#x27;s messy <a href="https:&#x2F;&#x2F;gist.github.com&#x2F;kmod&#x2F;ee6ac3c029641b39d0b6" rel="nofollow">https:&#x2F;&#x2F;gist.github.com&#x2F;kmod&#x2F;ee6ac3c029641b39d0b6</a>