Question

Consider the following sample data from a data file about movies that have been added to the national film registry. The data includes the title of the movie, the year it was released, and the year it was added to the registry. movieTitle,yearReleased,yearAdded Chicana,1979,2021 Cooley High,1975,2021 Evergreen,1965,2021 Flowers and Trees,1932,2021 The Flying Ace,1926,2021 Cabin in the Sky,1943,2020 A Clockwork Orange,1971,2020 The Dark Knight,2008,2020 The Devil Never Sleeps,1994,2020 Freedom Riders,2010,2020 Grease,1978,2020 Download movies.txt to your computer. Movies Dataset Open an instance of Trinket in your browser. Trinket Import movies.txt using the upload button found on the far right, top corner of the trinket editor screen. It will open a dialogue window for you to navigate to the data.txt location on your computer (most likely the downloads folder). Note that only text files with the extension *.txt can be uploaded to trinket as data files. After the file appears in the editor window in the data.txt tab, click on the Main.py tab and copy in the following code. Run the program. The code below will produce a bar chart #importing required libraries import pandas from seaborn import catplot from matplotlib import pyplot data = pandas.read_csv('movies.txt') catplot(x = 'yearReleased',col = "yearAdded", data = data, hue = 'yearAdded', kind = "count") pyplot.show() How would removing the hue parameter from the catplot function alter the visualization and possibly influence the interpretation?

Answer 1

Removing the hue parameter from the catplot function will significantly change the visualization and how the data is interpreted. Here’s how it would affect the results:

1. Visual Representation:

   • With hue = 'yearAdded', each bar representing the counts of movies released in a specific year would be further subdivided by the years they were added to the registry. This allows viewers to see not just how many movies were released in each year but also how those counts differ by the year they were added to the registry.
   • Without the hue parameter, each bar will only show the total count of movies released in that year, independently of when they were added. This provides a more simplistic view and can obscure trends or patterns related to the addition of those movies to the registry over different years.

2. Interpretation:

   • With the hue parameter, you could interpret trends over time—e.g., whether a particular release year has consistently been added to the registry in specific years or if certain decades are favored for inclusion.
   • Without the hue, the analysis would be limited to just the number of movies released per year, lacking insights into how these releases correlate with the years they were recognized. This means vital contextual information might be lost, which could lead to oversimplified conclusions.

3. Insights into Trends:

   • The hue parameter allows for insights into the relationship between the timing of a movie's release and its recognition years. For example, patterns such as whether newer films are being recognized more quickly than older films or if there are gaps in recognition of films from certain years would be visible with hue.
   • Without this, one might mistakenly assume that all released films receive similar recognition without honoring the complexity of timing and historical context.

In conclusion, removing the hue parameter limits the detail and the depth of the story the data tells, reducing the ability to identify and analyze patterns in the relationship between movie release years and their recognition years.