In kate-pyper/MM916ProgrammingExercises:

library(learnr)
library(testwhat)
knitr::opts_chunk$set(echo = FALSE)
tutorial_options(exercise.timelimit = 60, exercise.checker=testwhat::testwhat_learnr)

require(tidyverse)
data(mtcars)

For the following examples you should use functions from dplyr to extract the relevant pieces of data from the mtcars data set:

head(mtcars)

Exercise 1

Find the cars which get at least 20 miles per gallon (mpg).

# tidy the penguins data
mtcars %>% filter(mpg>=20) %>% arrange(mpg)

ex() %>% {
  check_error(.)
  check_function(., "filter", index=1) %>% check_result(.) %>% check_equal(.)
}

Exercise 2

Order the data in mtcars by highest to lowest weight (wt)

mtcars %>% arrange(desc(wt))

ex() %>%{
  check_error(.)
  check_function(., "arrange") %>% check_result(.) %>% check_equal(., incorrect_msg="Did you sort the data in decreasing order?")
}

Exercise 3

Extract the rows from the mtcars data set where the number of gears (gear) is not equal to 4. Order the results by increasing horsepower (hp)

mtcars %>% filter(gear!=4) %>% arrange(hp)

ex() %>%{
  check_error(.)
  check_or(.,
           {check_function(.,"filter") %>% check_result(.) %>% check_equal(.)
             check_function(.,"arrange") %>% check_result(.) %>% check_equal(.)},
           override_solution_code(., "mtcars %>% arrange(hp) %>% filter(gear!=4)") %>% {check_function(.,"arrange") %>% check_result(.) %>% check_equal(.)
             check_function(.,"filter") %>% check_result(.) %>% check_equal(.)})
}

Exercise 4

Extract all of the columns from mtcars from hp to vs.

mtcars %>% select(hp:vs)

ex() %>%{
  check_error(.)
  check_function(.,"select") %>% check_result(.) %>% check_equal(.)
}

kate-pyper/MM916ProgrammingExercises documentation built on Oct. 15, 2020, 10:40 p.m.