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
# Start coding!Importing raw data
netflix_df = pd.read_csv("netflix_data.csv") #index_col = 0, not sure if i will need this yet...)
#Test print for sanity check
#netflix_df[1:100]#Filtering the Data to creat a subset with now TV Shows
netflix_subset = netflix_df[netflix_df["type"] == "Movie"]
#Test print for sanity check
#netflix_subset[1:10]#Filtering the netflix subset Dataframe down to just Title, Country, Genre,Release Year, and Duration
netflix_movies = netflix_subset[["title", "country", "genre", "release_year", "duration"]]
#Test print for sanity check
netflix_movies[1:100]#Filtering the netflix_movies subset to movies under 60 minutes in duration
short_movies = netflix_movies[netflix_movies.duration < 60]
#Test print for sanity check
short_movies[1:100]#Iterating through rows of data to assign colors to certain genres and assigning that to a new variable 'colors'
colors = []
for label, 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("black")
short_movies#Now it's time to plot the movie duration by year according to the genre colors we added above
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()