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I'm rather new to the tidyverse, and I want to learn, so this question is specifically about doing this the tibble way, using things like select(), mutate() and the like. I know how to achieve the desired effect with data frames matching column indices.

I have a rather large tibble, containing columns named Day1, Day2, ..., Day48, among others. I'd like to add columns of averages for every week, using regular expressions (assume the column names could be more complicated). How would I achieve this?

user11130854
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    It's generally a good idea to give a minimal reproducible example if possible. – Eli Berkow Jul 04 '19 at 09:36
  • This seems to be a problem for `summarize_at(vars(.), etc)`. (This is a package `dplyr` function.) – Rui Barradas Jul 04 '19 at 09:38
  • You'll need to give us some example input and output data before you get a definitive answer, but I believe `gather`ing and `group_by`ing (dplyr functions) your variables might be part of a potential solution. –  Jul 04 '19 at 11:07

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Figured it out:

data <- mutate(data, Week1=select(data, matches("^Day[1-7]$")) %>% rowMeans(na.rm=T))
user11130854
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