updated: 2018-07-24

Tidy evaluation is a bit difficult to have a good understanding. Since ggplot released its 3.0 and the sell point is tidy eval, it’s time to get it through.

!! and quo

test code highlight

library(tidyverse)
## ── Attaching packages ──────────────────────────── tidyverse 1.2.1 ──
## ✔ ggplot2 3.0.0     ✔ purrr   0.2.5
## ✔ tibble  1.4.2     ✔ dplyr   0.7.6
## ✔ tidyr   0.8.1     ✔ stringr 1.3.1
## ✔ readr   1.1.1     ✔ forcats 0.3.0
## ── Conflicts ─────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
mtcars %>%
  select(1:3) %>%
  group_by(cyl) %>%
  summarise(n=n())
## # A tibble: 3 x 2
##     cyl     n
##   <dbl> <int>
## 1     4    11
## 2     6     7
## 3     8    14