2 ms·

Now this is a wild guess on feedback I've read from women. There's currently less of them coding for fun than men for cultural reasons but plenty are willing to

Now this is a wild guess on feedback I've read from women. There's currently less of them coding for fun than men for cultural reasons but plenty are willing to learn a language to make money. Those in the top 10 are all over job ads. That by itself might skew women toward those languages.

fhoffa 9y ago
Interesting guess! Let's see. What if I take all mentions of each language on HN's who's hiring threads, vs % of women interested in each language? There is correlation! Chart: - http://i.imgur.com/mcN6Ghz.png http://i.imgur.com/mcN6Ghz.png If we take out the 2 outliers (r, go) - the correlation is 0.61. SELECT * FROM ( SELECT word, COUNT(*) c FROM ( SELECT SPLIT(REGEXP_REPLACE(LOWER(text), r'[^a-z]', ' '), ' ') words FROM `bigquery-public-data.hacker_news.full` WHERE parent IN ( SELECT id FROM `bigquery-public-data.hacker_news.full` WHERE title LIKE 'Ask HN: Who is hiring?%2017%' ) ), UNNEST(words) word WHERE LENGTH(word)>1 OR (word='r') GROUP BY 1 HAVING c>30 ) a JOIN ( SELECT LOWER(WantWorkLanguage) language, COUNT(*) responses, ROUND(100*COUNTIF(v='Female')/COUNT(*), 2) perc_female FROM ( SELECT SPLIT(WantWorkLanguage , '; ') WantWorkLanguage, Gender v FROM `fh-bigquery.stackoverflow.survey_results_public_2017` WHERE WantWorkLanguage!='NA' AND Gender!='NA' ), UNNEST(WantWorkLanguage) WantWorkLanguage GROUP BY 1 HAVING responses>2000 ) b ON a.word=b.language (caveat: "go" is an overloaded word)
- nickpsecurity 9y ago
  Be even better if you could do it against a summary of appearances in job postings at major job sites. That will represent more of the market women are working in probably. They might have summary data you can use on the languages if not the actual postings.
  - fhoffa 9y ago
    True - but since I couldn't find that on time, I created my own ranking with the data I had on hand.

fhoffa 9y ago

Interesting guess! Let's see. What if I take all mentions of each language on HN's who's hiring threads, vs % of women interested in each language? There is correlation! Chart: - http://i.imgur.com/mcN6Ghz.png http://i.imgur.com/mcN6Ghz.png If we take out the 2 outliers (r, go) - the correlation is 0.61. SELECT * FROM ( SELECT word, COUNT(*) c FROM ( SELECT SPLIT(REGEXP_REPLACE(LOWER(text), r'[^a-z]', ' '), ' ') words FROM `bigquery-public-data.hacker_news.full` WHERE parent IN ( SELECT id FROM `bigquery-public-data.hacker_news.full` WHERE title LIKE 'Ask HN: Who is hiring?%2017%' ) ), UNNEST(words) word WHERE LENGTH(word)>1 OR (word='r') GROUP BY 1 HAVING c>30 ) a JOIN ( SELECT LOWER(WantWorkLanguage) language, COUNT(*) responses, ROUND(100*COUNTIF(v='Female')/COUNT(*), 2) perc_female FROM ( SELECT SPLIT(WantWorkLanguage , '; ') WantWorkLanguage, Gender v FROM `fh-bigquery.stackoverflow.survey_results_public_2017` WHERE WantWorkLanguage!='NA' AND Gender!='NA' ), UNNEST(WantWorkLanguage) WantWorkLanguage GROUP BY 1 HAVING responses>2000 ) b ON a.word=b.language (caveat: "go" is an overloaded word)

nickpsecurity 9y ago
Be even better if you could do it against a summary of appearances in job postings at major job sites. That will represent more of the market women are working in probably. They might have summary data you can use on the languages if not the actual postings.
- fhoffa 9y ago
  True - but since I couldn't find that on time, I created my own ranking with the data I had on hand.