24 4월 55.dos.cuatro Where & Whenever Did My Swiping Activities Transform?

More info for mathematics some one: Become way more particular, we'll grab the ratio out-of fits so you can swipes best, parse people zeros throughout the numerator or perhaps the denominator to 1 (very important to promoting actual-cherished journalarithms), and do the sheer logarithm of this worth. It fact itself may not be instance interpretable, however the relative total manner could well be.

bentinder = bentinder %>% mutate(swipe_right_rate = (likes / (likes+passes))) %>% mutate(match_rate = log( ifelse(matches==0,1,matches) / ifelse(likes==0,1,likes))) rates = bentinder %>% look for(big date,swipe_right_rate,match_rate) match_rate_plot = ggplot(rates) + geom_area(size=0.2,alpha=0.5,aes(date,match_rate)) + geom_simple(aes(date,match_rate),color=tinder_pink,size=2,se=Untrue) + geom_vline(xintercept=date('2016-09-24'),color='blue',size=1) +geom_vline(xintercept=date('2019-08-01'),color='blue',size=1) + annotate('text',x=ymd('2016-01-01'),y=-0.5,label='Pittsburgh',color='blue',hjust=1) + annotate('text',x=ymd('2018-02-26'),y=-0.5,label='Philadelphia',color='blue',hjust=0.5) + annotate('text',x=ymd('2019-08-01'),y=-0.5,label='NYC',color='blue',hjust=-.