Perform same linear regression on different factors within same data frame

Question

I am working on a very large dataset and have laid out a simple version below

group <- c(rep("A", 3), rep("B", 3), rep("C", 3))
X <- c(0, 1, 2, 0, 1, 2, 0, 1, 2)
Y <- c(0, 2, 4, 0, 3, 6, 0, 4, 8)   
df <- data.frame(group, X, Y)

I am attempting to obtain, through linear regression, the coefficients of three lines corresponding to groups A, B, and C (factor variables)... with little luck from the below code...

I came across some R code where a ' * ' sign was suggested to be used on the independent variable to (in the case of this example) calculate the slope of line A, B, and C. A, B, and C being a factor variable.

lin.reg <- lm(Y ~ X*group, data = df)
coefficients_for_ABC <- summary(lin.reg)

I think this code I came across is incorrect and that I need to apply a by function or similar.

Answer 1

This should work. Do what ever reg u want to do inside the function!

lapply(split(df,df$group),function(x){lm( x$Y ~ x$X )})