Is there an association between
the weight and the fuel efficiency of cars?
To find out, we use the mtcars example from drake_example("mtcars")
.
The mtcars dataset itself only has 32 rows,
so we generate two larger bootstrapped datasets
and then analyze them with regression models.
Finally, we summarize the regression models
to see if there is an association.
Usage
load_mtcars_example(
envir = parent.frame(),
report_file = NULL,
overwrite = FALSE,
force = FALSE
)
Arguments
- envir
The environment to load the example into. Defaults to your workspace. For an insulated workspace, set
envir = new.env(parent = globalenv())
.- report_file
Where to write the report file. Deprecated. In a future release, the report file will always be
report.Rmd
and will always be written to your working directory (current default).- overwrite
Logical, whether to overwrite an existing file
report.Rmd
.- force
Deprecated.
Details
Use drake_example("mtcars")
to get the code
for the mtcars example.
This function also writes/overwrites
the file, report.Rmd
.
Examples
if (FALSE) { # \dontrun{
isolate_example("Quarantine side effects.", {
if (suppressWarnings(require("knitr"))) {
# Populate your workspace and write 'report.Rmd'.
load_mtcars_example() # Get the code: drake_example("mtcars")
# Check the dependencies of an imported function.
deps_code(reg1)
# Check the dependencies of commands in the workflow plan.
deps_code(my_plan$command[1])
deps_code(my_plan$command[4])
# Plot the interactive network visualization of the workflow.
outdated(my_plan) # Which targets are out of date?
# Run the workflow to build all the targets in the plan.
make(my_plan)
outdated(my_plan) # Everything should be up to date.
# For the reg2() model on the small dataset,
# the p-value is so small that there may be an association
# between weight and fuel efficiency after all.
readd(coef_regression2_small)
# Clean up the example.
clean_mtcars_example()
}
})
} # }