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.
You work for a production company that specializes in nostalgic styles. You want to do some research on movies released in the 1990's. You'll delve into Netflix data and perform exploratory data analysis to better understand this awesome movie decade!
You have been supplied with the dataset netflix_data.csv, along with the following table detailing the column names and descriptions. Feel free to experiment further 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
# Read in the Netflix CSV as a DataFrame
netflix_df = pd.read_csv("netflix_data.csv")# Start coding here! Use as many cells as you like# Filtering for "Movie" type
netflix_movies = netflix_df[netflix_df["type"] == "Movie"]
# Filtering for Movies in the 1900s only
netflix_movies_1990s = netflix_movies[(netflix_movies["release_year"] >= 1990) & (netflix_movies["release_year"] <= 1999)]
# Check subset
print(netflix_movies_1990s)# Creating histogram of the duration column to see the distribution and check which is the highest
plt.hist(netflix_movies_1990s["duration"])
plt.title('Distribution of Movie Durations in the 1990s')
plt.xlabel('Duration in minutes')
plt.ylabel('Number of Movies')
plt.show
# Most frequent movie duration in the 1990s
duration = 100
print("Most frequent movie duration in the 1990s: " + str(duration) + " minutes")# Filtering the data for "Action" movies
action_movies_1990s = netflix_movies_1990s[netflix_movies_1990s["genre"] == "Action"]
# Count the number of short action movies by using a for loop and an if-else statement
short_movie_count = 0
for label, row in action_movies_1990s.iterrows() :
if row["duration"] < 90 :
short_movie_count = short_movie_count + 1
else :
short_movie_count = short_movie_count
print("Number of short action movies released in 1990s: " + str(short_movie_count))