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")# Get the movie only in 1990s
years_1990s = netflix_df[(netflix_df['release_year'] >= 1990) & (netflix_df['release_year'] < 2000)]
movies_1990s = years_1990s[years_1990s['type'] == 'Movie']
movies_1990s# Plot the movie duration to find the most frequent value
plt.hist(movies_1990s['duration'])
plt.xlabel('Movie duration in min')
plt.ylabel('Frequency')
plt.show()# Most frequent movie duration in 1990 (using the mode)
print(movies_1990s['duration'].mode()[0])# Using the graph store and print the approximate answer
duration = 100
print('The most frequent movie duration is approximetely: ' + str(duration) + ' min.')# Find the number of movie less than 90min
#less_than_90 = movies_1990s[movies_1990s['duration'] < 90]
#less_than_90# Action movie and less than 90min
action_movie = movies_1990s[movies_1990s['genre'] == 'Action']
action_movie# Setting up counter
short_movie_action = 0# Iterating through a DataFrame
for label, row in action_movie.iterrows():
if row['duration'] < 90:
short_movie_action += 1
else:
pass
print(short_movie_action)
short_movie_count = 7# Count the number of row to found how many action movie are less then 90min
#print(len(action_movie_less_90))
#short_movie_action = 7
#print('The number of short action movie is ' + str(short_movie_action) + '.')