Values Belong In Columns

John Mount argues that to reduce ambiguity, ensure that your values are columns on appropriate data frames:

Here is an (artificial) example.

chamber_sizes <- mtcars$disp/mtcars$cyl
form <- hp ~ chamber_sizes
model <- lm(form, data = mtcars)
print(model)
# Call:
# lm(formula = form, data = mtcars)
#
# Coefficients:
#   (Intercept)  chamber_sizes  
#         2.937          4.104  

Notice: one of the variables came from a vector in the environment, not from the primary data.frame. chamber_sizes was first looked for in the data.frame, and then in the environment the formula was defined (which happens to be the global environment), and (if that hadn’t worked) in the executing environment (which is again the global environment).

Our advice is: do not do that. Place all of your values in columns. Make it unambiguous all variables are names of columns in your data.frame of interest. This allows you to write simple code that works over explicit data. The style we recommend looks like the following.

Read the whole thing.