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title : Insert the chapter title here description : Insert the chapter description here attachments : slides_link : https://s3.amazonaws.com/assets.datacamp.com/course/teach/slides_example.pdf

--- type:VideoExercise lang:r xp:50 skills:1

Analyze movie ratings

*** =video_link //player.vimeo.com/video/154783078

--- type:MultipleChoiceExercise lang:r xp:50 skills:1

A really bad movie

Have a look at the plot that showed up in the viewer to the right. Which type of movie has the worst rating assigned to it?

*** =instructions

  • Adventure
  • Action
  • Animation
  • Comedy

*** =hint Have a look at the plot. Which color does the point with the lowest rating have?

*** =pre_exercise_code

# The pre exercise code runs code to initialize the user's workspace. You can use it for several things:

# 1. Preload a dataset. The code below will read the csv that is stored at the URL's location.
# The movies variable will be available in the user's console.
movies <- read.csv("http://s3.amazonaws.com/assets.datacamp.com/course/introduction_to_r/movies.csv")

# 2. Pre-load packages, so that users don't have to do this manually.
library(ggplot2)

# 3. Create a plot in the viewer, that students can check out while reading the exercise
ggplot(movies, aes(x = runtime, y = rating, col = genre)) + geom_point()

*** =sct

# The sct section defines the Submission Correctness Tests (SCTs) used to
# evaluate the student's response. All functions used here are defined in the 
# testwhat R package

msg_bad <- "That is not correct!"
msg_success <- "Exactly! There seems to be a very bad action movie in the dataset."

# Use test_mc() to grade multiple choice exercises. 
# Pass the correct option (Action, option 2 in the instructions) to correct.
# Pass the feedback messages, both positive and negative, to feedback_msgs in the appropriate order.
test_mc(correct = 2, feedback_msgs = c(msg_bad, msg_success, msg_bad, msg_bad))

--- type:NormalExercise lang:r xp:100 skills:1

More movies

In the previous exercise, you saw a dataset about movies. In this exercise, we'll have a look at yet another dataset about movies!

A dataset with a selection of movies, movie_selection, is available in the workspace.

*** =instructions

  • Check out the structure of movie_selection.
  • Select movies with a rating of 5 or higher. Assign the result to good_movies.
  • Use plot() to plot good_movies$Run on the x-axis, good_movies$Rating on the y-axis and set col to good_movies$Genre.

*** =hint

  • Use str() for the first instruction.
  • For the second instruction, you should use ...[movie_selection$Rating >= 5, ].
  • For the plot, use plot(x = ..., y = ..., col = ...).

*** =pre_exercise_code

# Pre-load a package in the workspace
library(MindOnStats)

# You can prepare the data before the student starts:
data(Movies)
movie_selection <- Movies[Movies$Genre %in% c("action", "animated", "comedy"),c("Genre", "Rating", "Run")]

# You can also clean up data so that it's not available in the student's workspace anymore:
rm(Movies)

*** =sample_code

# movie_selection is available in your workspace

# Check out the structure of movie_selection


# Select movies that have a rating of 5 or higher: good_movies


# Plot Run (i.e. run time) on the x axis, Rating on the y axis, and set the color using Genre

*** =solution

# movie_selection is available in your workspace

# Check out the structure of movie_selection
str(movie_selection)

# Select movies that have a rating of 5 or higher: good_movies
good_movies <- movie_selection[movie_selection$Rating >= 5, ]

# Plot Run (i.e. run time) on the x axis, Rating on the y axis, and set the color using Genre
plot(good_movies$Run, good_movies$Rating, col = good_movies$Genre)

*** =sct

# The sct section defines the Submission Correctness Tests (SCTs) used to
# evaluate the student's response. All functions used here are defined in the 
# testwhat R package. Documentation can also be found at github.com/datacamp/testwhat/wiki

# Test whether the function str is called with the correct argument, object
# If it is not called, print something informative
# If it is called, but called incorrectly, print something else
test_function("str", args = "object",
              not_called_msg = "You didn't call `str()`!",
              incorrect_msg = "You didn't call `str(object = ...)` with the correct argument, `object`.")

# Test the object, good_movies
# Notice that we didn't define any feedback here, this will cause automatically 
# generated feedback to be given to the student in case of an incorrect submission
test_object("good_movies")

# Test whether the student correctly used plot()
# Again, we use the automatically generated feedback here
test_function("plot", args = "x")
test_function("plot", args = "y")
test_function("plot", args = "col")

# Alternativeley, you can use test_function() like this
# test_function("plot", args = c("x", "y", "col"))

# It's always smart to include the following line of code at the end of your SCTs
# It will check whether executing the student's code resulted in an error, 
# and if so, will cause the exercise to fail
test_error()

# Final message the student will see upon completing the exercise
success_msg("Good work!")