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
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 |
description | Description of the show |
genre | Show genre |
Pandas - DataFrame Reference -->https://www.w3schools.com/python/pandas/pandas_ref_dataframe.asp
# Importing pandas and matplotlib
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
# Start coding!netflix_df = pd.read_csv('netflix_data.csv')
netflix_df.head() #Load and inspect the Netflix data
netflix_df.shapenetflix_subset = netflix_df[netflix_df['type'] == 'Movie']
netflix_subset #Subset the DataFrame for "Movies"#Subset the columns of the new DataFrame
netflix_movies = netflix_subset[['title', 'country', 'genre', 'release_year', 'duration']]
netflix_moviesStep 4: Filter the DataFrame by Movie duration
netflix_movies[netflix_movies['duration'] < 60].head(20)Step 5: Assign colors to movie genres
colors = []
for lab, row in netflix_movies.iterrows() :
if row['genre'] == "Children":
colors.append("pink")
elif row['genre'] == "Documentaries":
colors.append("blue")
elif row['genre'] == "Stand-Up":
colors.append("yellow")
else:
colors.append("green")Step 6: Plot the movie duration by year using the genre colors created
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()Step 7: Answer "Are we certain that movies are getting shorter?"