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
| Column | Description |
|---|---|
show_id | The ID of the show |
type | Type of show |
title | Title of the show |
director | Director of the show |
cast | Cast of the show |
country | Country of origin |
date_added | Date added to Netflix |
release_year | Year of Netflix release |
duration | Duration of the show in minutes |
description | Description of the show |
genre | Show 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')
# Filter the data to remove TV shows
netflix_subset = netflix_df[netflix_df['type'] != 'TV Show']# Create a new DataFrame called netflix_movies with selected columns
netflix_movies = netflix_subset[["title", "country", "genre", "release_year", "duration"]].copy()# Filter netflix_movies to find the movies that are shorter than 60 minutes
short_movies = netflix_movies[netflix_movies['duration'] < 60]
# Inspect the result
short_movies.head()# Initialize an empty list to store the colors
colors = []
# Iterate through the rows of netflix_movies
for index, row in netflix_movies.iterrows():
genre = row['genre']
# Assign colors based on genre groups
if genre == 'Children':
colors.append('blue')
elif genre == 'Documentaries':
colors.append('green')
elif genre == 'Stand-Up':
colors.append('red')
else:
colors.append('gray')
# Create a scatter plot
fig, ax = plt.subplots()
ax.scatter(netflix_movies['release_year'], netflix_movies['duration'], c=colors)
# Set labels and title
ax.set_xlabel('Release year')
ax.set_ylabel('Duration (min)')
ax.set_title('Movie Duration by Year of Release')# After inspecting the plot, answer the question "Are we certain that movies are getting shorter?"
answer = "maybe"