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. This data does contain null values and some outliers, but handling these is out of scope for the project. Feel free to experiment after submitting!
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
# Start coding!# import the dataset
netflix_df = pd.read_csv('netflix_data.csv')
netflix_df.head()# Filter the data to remove TV shows
netflix_subset = netflix_df[netflix_df['type'] != 'TV Show']
netflix_subset.head()# subseting the data to keeping only the columns "title", "country", "genre", "release_year", "duration"
netflix_movies = netflix_subset[["title", "country", "genre", "release_year", "duration"]]
netflix_movies.head()# Filter netflix_movies to find the movies that are strictly shorter than 60 minutes
short_movies = netflix_movies[netflix_movies['duration'] < 60]
short_movies.head(20)# an empty list to store colors
colors = []
# Iterate through each row in the DataFrame
for index, row in netflix_movies.iterrows():
genre = row['genre']
# Assign colors based on genre
if genre == 'Children':
colors.append('skyblue') # Light blue for children's movies
elif genre == 'Documentaries':
colors.append('lightgreen') # Light green for documentaries
elif genre == 'Stand-Up':
colors.append('gold') # Gold for stand-up comedy
else:
colors.append('lightcoral') # Light coral for all other genres
# Create the scatter plot
fig, ax = plt.subplots(figsize=(10, 6)) # Adjust figure size if needed
# Scatter plot with colors for each genre
ax.scatter(netflix_movies['release_year'], netflix_movies['duration'], c=colors, alpha=0.7) # Adjust alpha for transparency
# Customize plot appearance
ax.set_xlabel('Release year', fontsize=12)
ax.set_ylabel('Duration (min)', fontsize=12)
ax.set_title('Movie Duration by Year of Release', fontsize=14)
ax.grid(axis='y', linestyle='--', alpha=0.5) # Add a subtle grid
# Show the plot
plt.show()# Are we certain that movies are getting shorter?
answer = 'no'
print(answer)