durBase <- map(distributions, ~microbenchmark::microbenchmark(hist(.x)))

durGgplot <- map(distributions, ~microbenchmark::microbenchmark(qplot(.x)))

dt_durations <- bind_rows(map(durBase, summary), map(durGgplot, summary)) %>% 
                    mutate(sample = rep(c(10^2, 10^3, 10^4, 10^5),2))

dt_durations

##        expr       min        lq      mean    median        uq      max
## 1  hist(.x) 38.336860 54.501315 60.060890 59.531071 64.394342 95.51217
## 2  hist(.x) 49.352128 57.640673 61.879470 61.280147 65.104232 85.97245
## 3  hist(.x) 47.998929 53.813954 57.569624 57.364648 61.048715 71.24887
## 4  hist(.x) 39.912776 59.313690 63.146085 63.132119 67.026831 86.24658
## 5 qplot(.x)  2.679383  2.860507  4.502420  3.236379  4.739060 21.37262
## 6 qplot(.x)  2.710356  3.001929  4.461167  3.377924  4.607217 17.22505
## 7 qplot(.x)  2.694769  3.131219  4.681951  3.763796  5.195556 14.68402
## 8 qplot(.x)  2.715436  2.945233  4.049377  3.380630  4.048654 15.03824
##   neval sample
## 1   100  1e+02
## 2   100  1e+03
## 3   100  1e+04
## 4   100  1e+05
## 5   100  1e+02
## 6   100  1e+03
## 7   100  1e+04
## 8   100  1e+05

ggplot(data = dt_durations) +
  geom_line(aes(x = sample, y = median, color = expr)) +
  ylim(0,NA)