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")# Import necessary libraries
import pandas as pd
# Assuming the data is in a CSV file named 'netflix_data.csv'
# Load the dataset
netflix_df = pd.read_csv('netflix_data.csv')
# Start coding here! Use as many cells as you like
print(netflix_df.columns)
print(netflix_df.head())
# The most frequent movie duration in the 1990's
# Filtering the movies released between 1990 and 1999
netflix_df_1990s = netflix_df[(netflix_df['release_year'] >= 1990) & (netflix_df['release_year'] <= 1999)]
# Dropping rows with missing duration values
netflix_df_1990s = netflix_df_1990s.dropna(subset= ['duration'])
# Rounding duration to the nearest integer
netflix_df_1990s['duration'] = netflix_df_1990s['duration'].round().astype(int)
# Most frequent movie duration
duration = netflix_df_1990s['duration'].mode()[0]
print("Duration:", duration)
# Count of short action movies
# movies that are less than 90 minutes and are the "Action" genre
short_movies = netflix_df_1990s [(netflix_df_1990s['duration'] < 90) & (netflix_df_1990s['genre'] == 'Action') ]
# count of short_movies
short_movie_count = len(short_movies)
#action_movies = netflix_df_1990s[netflix_df_1990s['genre'] == 'Action']
print("short_movie_count:", short_movie_count)