Manipulate data

Select variables in a dataset using select() and sort using arrange()

The dataframe movies has been loaded into memory. It contains a sample of movies from IMDB, and its contents are shown below:

Filter rows in a dataset using filter()

Remember that select() allows us to choose columns, or variables, whereas filter() chooses rows, or cases, that conform to certain criteria

mutate() to change the data type of a variable and create new variables

group_by()/summarise() to get summary statistics, including counts, means, etc., within categories.

Putting it all together

You can put together all of your dplyr knowledge to work four genres of movies, namely action, adventure, comedy and drama and create the following plot.

For these genres, you have to

1. Make sure you do not have multiple entries of the same movie; use distinct(movie, _keep.all=TRUE)
2. Calculate a normalised metric for rating, where you adjust the movie’s rating by the number of votes it received out of the total votes in its genre, normalised_rating = rating * (votes / total votes in genre)
3. Arrange movies, so higher normalised_rating appears first.
4. Categorise and colour movies according to their budget cost
   • cheap (<20m, or <20e6 as e6 is R shorthand for 1 million, or \(10^6\),
   • moderate (20-120m), and
   • expensive (>120m)
5. Convert cost column to a factor variable and re-level in the correct order (cheap, moderate, expensive)
6. Change the labels in the x- and y-axis, and give appropriate titles, subtitles, etc
7. use theme minimal

Some tips:

1. for sorting columns within a a ggplot, check out the reorder() in x argument
2. if you perform dplyr on original dataframe make sure to overwrite dataframe otherwise all changes are done on the fly and are not saved
3. consider freeing the scales of the facet wrap