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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 data manipulation 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 have been performing some analyses, and they believe that the average duration of movies has been declining. Using your friends initial research, you'll delve into the Netflix data to if you can explain some of the factors that may be contributing to the shortening movie lengths.

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

    The data


    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
    descriptionDescription of the show
    genreShow genre
    # Importing pandas and matplotlib
    import pandas as pd
    import matplotlib.pyplot as plt
    # Read in the Netflix CSV as a DataFrame
    netflix_df = pd.read_csv("netflix_data.csv")
    # Subset the DataFrame for type "Movie"
    netflix_subset = netflix_df[netflix_df["type"] == "Movie"]
    # Select only the columns of interest
    netflix_movies = netflix_subset[["title", "country", "genre", "release_year", "duration"]]
    # Filter for durations shorter than 60 minutes
    netflix_movies[netflix_movies.duration < 60]
    # Define an empty list
    colors = []
    # Iterate over rows of netflix_movies
    for label, row in netflix_movies.iterrows() :
        if row["genre"] == "Children" :
        elif row["genre"] == "Documentaries" :
        elif row["genre"] == "Stand-Up":
    # Inspect the first 10 values in your list        
    # Set the figure style and initalize a new figure
    fig = plt.figure(figsize=(12,8))
    # Create a scatter plot of duration versus release_year
    plt.scatter(netflix_movies.release_year, netflix_movies.duration, c=colors)
    # Create a title and axis labels
    plt.title("Movie Duration by Year of Release")
    plt.xlabel("Release year")
    plt.ylabel("Duration (min)")
    # Show the plot
    # Are we certain that movies are getting shorter?
    answer = "maybe"