Your friend suspects that movies are getting shorter and they've found some initial evidence of this. Having peaked your interest, you will perform exploratory data analysis on the netflix_data.csv data to understand what may be contributing to movies getting shorter over time. Your analysis will follow these steps:
- Load the CSV file and store as netflix_df.
- Filter the data to remove TV shows and store as netflix_subset.
- Investigate the Netflix movie data, keeping only the columns "title", "country", "genre", "release_year", "duration", and saving this into a new DataFrame called netflix_movies.
- Filter netflix_movies to find the movies that are strictly shorter than 60 minutes, saving the resulting DataFrame as short_movies; inspect the result to find possible contributing factors.
- Using a for loop and if/elif statements, iterate through the rows of netflix_movies and assign colors of your choice to four genre groups ("Children", "Documentaries", "Stand-Up", and "Other" for everything else). Save the results in a colors list. Initialize a matplotlib figure object called fig and create a scatter plot for movie duration by release year using the colors list to color the points and using the labels "Release year" for the x-axis, "Duration (min)" for the y-axis, and the title "Movie Duration by Year of Release".
- After inspecting the plot, answer the question "Are we certain that movies are getting shorter?" by assigning either "yes" or "no" to the variable answer.
