> crime
# A tibble: 8 x 8
  iso    year  theft robbery burglary theft_price robbery_price burglary_price
  <chr> <dbl>  <dbl>   <dbl>    <dbl>       <dbl>         <dbl>          <dbl>
1 ALB    2003   3694     199      874        32.9          115           49.3
2 ALB    2004   3694     199      874        38.2          134           57.3
3 ALB    2005   3694     199      874        42.8          150           64.2
4 ALB    2006   3450     164      779        47.0          165           70.5
5 AUS    2003 722334   14634   586266       408.4         1427          612.4
6 AUS    2004 636717   14634   512551       481.3         1683          721.2
7 AUS    2005 598700   14634   468558       536.7         1877          804.5
8 AUS    2006 594111   14634   433974       564.8         1973          846.5

crime %>%
  mutate_at(vars(theft, robbery, burglary),
            funs(prod = . * ????))