Let's say I'd like to write anscombe %>% lm_tidy("x1", "y1"). So, as the following function seems working:

plot_gg <- function(df, x, y) {
  x <- enquo(x)
  y <- enquo(y)
  ggplot(df, aes(x = !!x, y = !!y))   geom_point()  
    geom_smooth(formula = y ~ x, method="lm", se = FALSE)
}

I started writing the following function:

lm_tidy_1 <- function(df, x, y) {
  x <- enquo(x)
  y <- enquo(y)
  fm <- y ~ x            ##### I tried many stuff here!
  lm(fm, data=df)
}
## Error in model.frame.default(formula = fm, data = df, drop.unused.levels = TRUE) : 
##   object is not a matrix

One comment in passing in column name as argument states that embrace {{...}} is a shorthand notation for the quote-unquote pattern. Unfortunately, error messages were different in both situations:

lm_tidy_2 <- function(df, x, y) {
  fm <- !!enquo(y) ~ !!enquo(x) # alternative: {{y}} ~ {{x}} with different errors!!
  lm(fm, data=df)
}
## Error:
## ! Quosures can only be unquoted within a quasiquotation context.

This seems working (based on @jubas's answer but we're stuck with string handling and paste):

lm_tidy_str <- function(df, x, y) {
  fm <- formula(paste({{y}}, "~", {{x}}))
  lm(fm, data=df)
}

Yet again, {{y}} != !!enquo(y). But it's worse: the following function breaks down with the same Quosure error as earlier:

lm_tidy_str_1 <- function(df, x, y) {
  x <- enquo(x)
  y <- enquo(y)
  fm <- formula(paste(!!y, "~", !!x))
  lm(fm, data=df)
}

1. Is {{y}} != !!enquo(y)?
2. How to pass data-variables to lm?

CodePudding user response：

Consider:

lm_tidy_1 <- function(df, x, y) {
  fm <- reformulate(as.character(substitute(x)), substitute(y))
  lm(fm, data=df)
}

lm_tidy_1(iris, Species, Sepal.Length)
lm_tidy_1(iris, 'Species', Sepal.Length)
lm_tidy_1(iris, Species, 'Sepal.Length')
lm_tidy_1(iris, 'Species', 'Sepal.Length')

CodePudding user response：

Wrap the formula in "expr," then evaluate it.

library(dplyr)
lm_tidy <- function(df, x, y) {
  x <- sym(x)
  y <- sym(y)
  fm <- expr(!!y ~ !!x)
  lm(fm, data = df)
}

This function is equivalent:

lm_tidy <- function(df, x, y) {
  fm <- expr(!!sym(y) ~ !!sym(x))
  lm(fm, data = df)
}

Then

lm_tidy(mtcars, "cyl", "mpg")

gives

Call:
lm(formula = fm, data = .)

Coefficients:
(Intercept)          cyl  
     37.885       -2.876