I thought long and hard about trying to identify preprocessor usage reliably because that is a super interesting piece of data, but nothing stuck out as a smoking gun. Sequentially increasing selectors
tr
tr td
tr td a
could be LESS unrolling a nested bit:
tr {
td {
a {
OR... could just be how people write CSS.
I mostly ignored by-domain grouping in my queries, but there is a host of analysis you could do that would get into the modeling portion of data science, teasing our correlation and trying to find 'groups' or styles' of CSS that is written on a site. I had only so much time ;-)
I also did a web perf report that is not fully edited or ready for consumption, but does not that 54% of sites I ran Google Page Speed Insights against didn't compress all of their CSS assets. (Same sample of domains)
I mostly ignored by-domain grouping in my queries, but there is a host of analysis you could do that would get into the modeling portion of data science, teasing our correlation and trying to find 'groups' or styles' of CSS that is written on a site. I had only so much time ;-)
I also did a web perf report that is not fully edited or ready for consumption, but does not that 54% of sites I ran Google Page Speed Insights against didn't compress all of their CSS assets. (Same sample of domains)