jhofman
commented
2 years ago One idea here is to simply treat count as "syntatic sugar" and always map it to a group_by + summarize.
For instance, df %>% count(vaccination_status, outcome) becomes df %>% group_by(vaccination_status, outcome) %>% summarize(n = n()).
This raises the separate issue of having a summarize operation that doesn't use a variable explicitly because the n() function is called without an argument.
In this case I think that raises the question of whether we want a "custom aggregation animation" for count, maybe? Could be a simpler version of what's here on page 4.
giorgi-ghviniashvili
sharlagelfand
I think this is inevitable as part of #97, and especially this infographic:
Right now we can show a similar infogrid by just grouping by e.g. vaccinated and outcome (
df %>% group_by(vaccination_status, outcome)), but the fact that this would work and show the info grid is more of a side effect / hidden feature and is not how someone would actually be summarizing the data - more likely to have e.g.df %>% count(vaccination_status, outcome).We will likely want to split each counted variable into a step as we do with data, e.g.
In dplyr,
df %>% count(vaccination_status, outcome)is equivalent todf %>% group_by(vaccination_status) %>% count(outcome), and I think it's important to make it clear in how we title things that the counts are combinations of vaccination status x outcome.Will have to think a bit more of the hierarchy of how these are displayed too and keeping it consistent with the grouping hierarchy, but also with the new rules we're creating as part of #98 - e.g. it would be nice to lean on colors / shapes here!