How to succinctly write a formula with many variables from a data frame?

Question

Suppose I have a response variable and a data containing three covariates (as a toy example):

y = c(1,4,6)
d = data.frame(x1 = c(4,-1,3), x2 = c(3,9,8), x3 = c(4,-4,-2))

I want to fit a linear regression to the data:

fit = lm(y ~ d$x1 + d$x2 + d$y2)

Is there a way to write the formula, so that I don't have to write out each individual covariate? For example, something like

fit = lm(y ~ d)

(I want each variable in the data frame to be a covariate.) I'm asking because I actually have 50 variables in my data frame, so I want to avoid writing out x1 + x2 + x3 + etc.

Answer 1

There is a special identifier that one can use in a formula to mean all the variables, it is the . identifier.

y <- c(1,4,6)
d <- data.frame(y = y, x1 = c(4,-1,3), x2 = c(3,9,8), x3 = c(4,-4,-2))
mod <- lm(y ~ ., data = d)

You can also do things like this, to use all variables but one (in this case x3 is excluded):

mod <- lm(y ~ . - x3, data = d)

Technically, . means all variables not already mentioned in the formula. For example

lm(y ~ x1 * x2 + ., data = d)

where . would only reference x3 as x1 and x2 are already in the formula.