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")
netflix_df# Start coding here! Use as many cells as you like
# Subset dataframe to filter just movies
movies = netflix_df[netflix_df["type"] == "Movie"]
# Subset the data to keep movies released in the 90s
movies_90s = movies[(movies["release_year"] >= 1990) & (movies["release_year"] < 2000)]
# Find the most frequent movie duration
duration = 100
# Display the most frequent movie duration
print(f"The most frequent movie duration is: {duration}")# Plot histogram of the duration of movies released between 1990 and 1999
plt.hist(movies_90s['duration'], bins=20, edgecolor='black')
plt.title('Distribution of Movie Durations (1990-1999)')
plt.xlabel('Duration (minutes)')
plt.ylabel('Frequency')
plt.show()
#list out action movies under 90 minutes from the 1990s
action_90s = movies_90s[movies_90s["genre"] == "Action"]
# Count the number of movies
short_movie_count = 0
for x, movie in action_90s.iterrows():
if movie["duration"] < 90:
short_movie_count = short_movie_count + 1
else:
short_movie_count = short_movie_count
print(f"The number of short action movies is: {short_movie_count}")