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Project: Investigating Netflix Movies
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  • Netflix! What started in 1997 as a DVD rental service has since exploded into one of the largest entertainment and media companies.

    Given the large number of movies and series available on the platform, it is a perfect opportunity to flex your exploratory data analysis skills and dive into the entertainment industry. Our friend has also been brushing up on their Python skills and has taken a first crack at a CSV file containing Netflix data. They believe that the average duration of movies has been declining. Using your friends initial research, you'll delve into the Netflix data to see if you can determine whether movie lengths are actually getting shorter and explain some of the contributing factors, if any.

    You have been supplied with the dataset netflix_data.csv , along with the following table detailing the column names and descriptions:

    The data

    netflix_data.csv

    ColumnDescription
    show_idThe ID of the show
    typeType of show
    titleTitle of the show
    directorDirector of the show
    castCast of the show
    countryCountry of origin
    date_addedDate added to Netflix
    release_yearYear of Netflix release
    durationDuration of the show in minutes
    descriptionDescription of the show
    genreShow genre
    # Importing pandas and matplotlib
    import pandas as pd
    import matplotlib.pyplot as plt
    
    # Start coding! load the CSV file and store as netflix_df
    netflix_df = pd.read_csv('netflix_data.csv')
    
    # filter the data to remove TV shows 
    netflix_subset = netflix_df[netflix_df['type'] == 'Movie']
    
    # investigate netflix movie data
    netflix_movies = netflix_subset[["title", "country", "genre", "release_year", "duration"]]
    
    # filter netflix_movies to find the movies shorter than 60 minutes
    short_movies = netflix_movies[netflix_movies['duration'] < 60]
    print(short_movies.head())
    
    # using a loop to assign colour to four genre groups
    colors = []
    for index, rows in netflix_movies.iterrows():
        if rows['genre'] == 'Children':
            colors.append('pink')
        elif rows['genre'] == 'Documentaries':
            colors.append('purple')
        elif rows['genre'] == 'Stand-up':
            colors.append('blue')
        else:
            colors.append('red')
    
    # to initialize a figure object called fig
    fig = plt.figure()
    
    # create a scatter plot for movie duration by release year and colors list to color
    plt.scatter(netflix_movies['duration'], netflix_movies['release_year'], c=colors)
    plt.xlabel("Release year")  
    plt.ylabel("Duration (min)")  
    plt.title("Movie Duration by Year of Release")
    
    # show the plot
    plt.show()
    
    # Are we certain movies are getting shorter over time?
    answer = "maybe"

    Answer = "maybe"