92, being a "lot", if you will
49130| 49291| 49416| 51033| 51164| 51509| 51511| 51512| 52337| 52626| 52694| 53850| 53899| 53901| 53935| 53936| 53938| 53943| 53944| 53946| 53947| 53949| 54206| 54498| 54500| 54501| 54502| 54503| 54511| 54516| 54655| 54655| 54656| 54867| 54987| 54990| 55034| 55084| 55286| 55336| 55337| 55465| 55468| 55469| 55599| 55676| 57100| 57102| 57104| 57105| 57126| 57143| 57161| 57167| 57169| 57170| 57181| 57183| 57184| 57189| 57196| 57198| 57199| 57202| 57205| 57216| 57217| 57221| 57224| 57225| 57226| 57229| 57231| 57239| 57240| 59085| 95532| 95613| 95706| 96186| 96195| 96199| 96200| 96201| 96209| 96213| 96229| 96303| 96425| 96429| 96432| 96750
original names were like:
> 49130.332.286.256
& i wanted to find matches of the 1st. "word", so "49130"
& i wanted to find
> 49130.332.286.256 & 49130
so i %s/\..*// & %s/$/|/ & Joined the lines
(& pasted that single line in as my search)
not particularly concerned
but i imagine there is a more efficient method ?
if it's not too much trouble...
(& that said, doing what i did is doable, & i can do it, at least with said data set
& the more efficient method i'm likely to not remember
(heh. & shortly after i came across the 92 lot grouping, i then found a 44 lot grouping.
44 was quicker then 92
the 92 happened to be a more fruitful endeavor.)