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
#read netflix_data.csv in python
netflix_df = pd.read_csv('netflix_data.csv', index_col = 0)
# print(netflix_df)
#Filter Tv Shows out (look at type column above)
netflix_subset = netflix_df[netflix_df['type'] == 'Movie']
#print(netflix_subset)
#Make new dataframe keeping columns: title, country, genre, release_year, and
#duration. Save it into new dataframe netflix_movies
netflix_movies = netflix_subset[['title', 'country', 'genre', 'release_year','duration']]
#print(netflix_movies)
#Filter movies that are shorter than 60 min
short_movies = netflix_movies[netflix_movies['duration'] < 60]
#print(short_movies)
#Use For-loop to iterate thru netflix_movies and assign colors
colors = [] #start by creating an empty list
for lab, row in netflix_movies.iterrows(): #next create a forloop to iterate in df
if row['genre'] == "Children": # Corrected to use row['genre'] instead of netflix_movies['genre']
colors.append('red')
elif row['genre'] == "Documentaries": # Corrected to use row['genre'] instead of netflix_movies['genre']
colors.append('blue')
elif row['genre'] == "Stand-Up": # Corrected to use row['genre'] instead of netflix_movies['genre']
colors.append('green')
else:
colors.append('black')
print(colors[0:10])
#Creating a scatter plot
fig = plt.figure(figsize = (12,8))
plt.scatter(netflix_movies['release_year'], netflix_movies['duration'], c = colors)
#Adding title and labels
plt.title('Movie Duration by Year of Release',c = 'r')
plt.xlabel('Release year', c = 'b')
plt.ylabel('Duration (min)', c = 'g')
plt.show()
#Are we certain that movies are getting shorter?
answer = 'no'