To visualise a model, it is very useful to be able to generate an
evenly spaced grid of points from the data.
data_grid helps you
do this by wrapping around
A data frame
Variables passed on to
A model. If supplied, any predictors needed for the model
not present in
seq_range() for generating ranges from continuous
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data_grid(mtcars, vs, am) # For continuous variables, seq_range is useful data_grid(mtcars, mpg = seq_range(mpg, 10)) # If you optionally supply a model, missing predictors will # be filled in with typical values mod <- lm(mpg ~ wt + cyl + vs, data = mtcars) data_grid(mtcars, .model = mod) data_grid(mtcars, cyl = seq_range(cyl, 9), .model = mod)
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