4 ms·
Top level domains by popularity: grep -oP '\.[a-z]+(?=,)' current.csv | sort | uniq -c | sort -n ... 15840 .pl 17914 .it 20182 .de 21690 .in 2
by mg 4y ago
Top level domains by popularity:
grep -oP '\.[a-z]+(?=,)' current.csv | sort | uniq -c | sort -n
...
15840 .pl
17914 .it
20182 .de
21690 .in
27812 .ru
29194 .jp
30359 .org
35741 .br
36675 .net
406052 .com
.com domains by popularity:
grep -oP '[a-z0-9-]+\.com(?=,)' current.csv | sort | uniq -c | sort -n
...
365 tistory.com
370 fc2.com
408 skipthegames.com
489 online.com
515 wordpress.com
707 uptodown.com
880 schoology.com
2570 fandom.com
2651 instructure.com
3244 blogspot.com
- deleted 4y ago[deleted]
- voytec 4y agosort -r will reverse the order from most to less popular.
- layer8 4y ago.
- codetrotter 4y agouniq -c is in the pipeline because it counts the number of uniques
- layer8 4y agoAh, right, missed that.
- egman_ekki 4y agoRather amazing seeing almost abandoned blogspot.com there at the top. Also interesting I haven’t heard about half of them. Some are nsfw, apparently.
- mometsi 4y agoThese aren't sorted by number of visits, but by the number of rows in the list of most visited sites. Essentially which sites have the greatest number of frequently visited subdomains.
- slim 4y agoit's amazing that fandom is number 3 and wikipedia is not even there
- csande17 4y agoWikipedia uses a .org domain, so it won't show up on "most popular .com domains" lists. (And I think the parent comment is searching for domains with lots of subdomains, which is why providers like Blogspot and Fandom show up.)
- deleted 4y ago[deleted]
- kristianp 4y agoLoading the data into the duckdb cli [0] and doing the first query: create table current as select * from '202211.csv'; select * from current; ┌────────────────────────────────────┬─────────┐ │ origin │ rank │ │ varchar │ int32 │ ├────────────────────────────────────┼─────────┤ │ https://hochi.news │ 1000 │ │ https://www.xnxx.xxx │ 1000 │ │ https://www.wordreference.com │ 1000 │ │ https://finance.naver.com │ 1000 │ │ https://www.macys.com │ 1000 │ │ https://www.xv-videos1.com │ 1000 │ │ https://fr.xhamster.com │ 1000 │ │ https://poki.com │ 1000 │ │ https://salonboard.com │ 1000 │ │ https://clgt.one │ 1000 │ select tld, count(*) from (select reverse(substr(reverse(origin),1, position('.' in reverse(origin))-1)) tld from current) group by tld order by count(*) desc; ┌───────────┬──────────────┐ │ tld │ count_star() │ │ varchar │ int64 │ ├───────────┼──────────────┤ │ com │ 406052 │ │ net │ 36675 │ │ br │ 35741 │ │ org │ 30359 │ │ jp │ 29194 │ │ ru │ 27812 │ │ in │ 21690 │ │ de │ 20182 │ │ it │ 17914 │ │ pl │ 15840 │ │ · │ · │ │ · │ · │ │ · │ · │ │ za:5002 │ 1 │ │ lk:8090 │ 1 │ │ org:1445 │ 1 │ │ co:14443 │ 1 │ │ ar:3016 │ 1 │ │ net:8001 │ 1 │ │ care:9624 │ 1 │ │ au:8443 │ 1 │ │ com:333 │ 1 │ │ edu:9016 │ 1 │ ├───────────┴──────────────┤ │ 2076 rows (20 shown) │ └──────────────────────────┘ [0] https://duckdb.org/docs/installation/ https://duckdb.org/docs/installation/
- Llamamoe 4y agoAre the bottom entries domain:port? I feel like the table would be more interesting excluding those.
- azeemba 4y agoIt might be worth updating this comment and explaining your second query. People seem to think it is somehow measuring visits to those origins. But it's measuring how many unique subdomains are listed for those domains