@ShawverTech@trying_to_exits Is it not good? Python also does the same. Extending ecosystems should be appreciated, if you dont like using it in other fields then just use it for web
@trying_to_exits JavaScript.
Not because it is bad, but because people keep trying to use it for everything.
Great language for the web. Questionable life choice when it becomes the answer to every problem.
@improvemypage@Taniyatweets_ I see that Python has a lot of ecosystems and data types which are evaluated as runtime as well as magic exceptions and ambigious. How do you all code by Python? There are a lot of things in Python to remember. Did you quickly lookup a cheatsheet or doc while coding?
@stats_feed It is not enough to say anything and its also nonsense if we use this divorce rate statistic to imply other results. If they have less marriages then a little bit divorce can make the proportion surge
Divorce rate:
🇮🇳India: 1%
🇻🇳Vietnam: 7%
🇹🇯Tajikistan: 10%
🇮🇷Iran: 14%
🇲🇽Mexico: 17%
🇪🇬Egypt: 17%
🇿🇦South Africa: 17%
🇧🇷Brazil: 21%
🇹🇷Turkey: 25%
🇨🇴Colombia: 30%
🇵🇱Poland: 33%
🇯🇵Japan: 35%
🇩🇪Germany: 38%
🇬🇧United Kingdom: 41%
🇳🇿New Zealand: 41%
🇦🇺Australia: 43%
🇨🇳China: 44%
🇺🇸United States: 45%
🇰🇷South Korea: 46%
🇩🇰Denmark: 46%
🇮🇹Italy: 46%
🇨🇦Canada: 47%
🇳🇱Netherlands: 48%
🇸🇪Sweden: 50%
🇨🇵France: 51%
🇧🇪Belgium: 53%
🇫🇮Finland: 55%
🇨🇺Cuba: 55%
🇺🇦Ukraine: 70%
🇷🇺Russia: 73%
🇱🇺Luxembourg: 79%
🇪🇦Spain: 85%
🇵🇹Portugal: 94%
Note: This compares the number of divorces in a given year to the number of marriages in that same year (the ratio of the crude divorce rate to the crude marriage rate). For example, if there are 500 divorces and 1,000 marriages in a given year in a given area, the ratio would be one divorce for every two marriages, e.g. a ratio of 0.50 (50%).
Data is from last available year by country. As an example Portugal data is from 2020, Germany is from 2017.