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Project: Investigating Netflix Movies

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


#Load the CSV file and store as netflix_df
netflix_df = pd.read_csv("netflix_data.csv")
netflix_df
#View the first five rows of the DataFrame
netflix_df.head(5)
#Filter the data to remove TV shows(Subset the DataFrame for "Movies") and store as netflix_subset.
netflix_subset = netflix_df[netflix_df["type"]=="Movie"]
netflix_subset
#Subset certain columns of the new DataFrame
netflix_movies = netflix_subset[["title", "country","genre", "release_year", "duration"]]
netflix_movies
#Filter netflix_movies to find the movies that are shorter than 60 minutes
short_movies = netflix_movies[netflix_movies["duration"] < 60]
short_movies.head(20)
#Assign colors to movie genres
colors = []
for lab, row in netflix_movies.iterrows():
    if row["genre"] == "Children":
        colors.append("Red")
    elif row["genre"] == "Documentaries":
        colors.append("Blue")
    elif row["genre"] == "Stand-up":
        colors.append("Green")
    else:
        colors.append("Yellow")
colors[:10]        
        
#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".
fig = plt.figure(figsize=(12,8))
plt.scatter(netflix_movies.release_year, netflix_movies.duration, c=colors)
plt.xlabel("Release year")
plt.ylabel("Duration (min)")
plt.title("Movie Duration by Year of Release")
plt.show()
#After inspecting the plot, answer the question "Are we certain that movies are getting shorter?" by assigning either "yes", "no", or "maybe" to the variable answer.
answer="maybe"