Project: Investigating Netflix Movies

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 my exploratory data analysis skills and dive into the entertainment industry. My friend has also been brushing up on his Python skills and has taken a first crack at a CSV file containing Netflix data. He believes that the average duration of movies has been declining. Using my friends initial research, I'll dive into the Netflix data to see if I can determine whether movie lengths are actually getting shorter and explain some of the contributing factors, if any.

I 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 necessary libraries
import pandas as pd
import matplotlib.pyplot as plt

# Loading the dataset
netflix_df = pd.read_csv('netflix_data.csv')

# Filtering the dataset for movies only
netflix_movies = netflix_df[netflix_df['type'] == 'Movie']

# Selecting relevant columns
netflix_movies = netflix_movies[['title', 'country', 'genre', 'release_year', 'duration']]

# Filtering for short movies (duration < 60 minutes)
short_movies = netflix_movies[netflix_movies['duration'] < 60]

# Displaying the first 20 short movies
print(short_movies.head(20))

# Assigning colors based on genre
genre_colors = {
    'Children': 'blue',
    'Documentaries': 'green',
    'Stand_Up': 'orange'
}

# To create a list of colors for each movie based on its genre
colors = [genre_colors.get(row['genre'], 'gray') for index, row in netflix_movies.iterrows()]

# Plotting the data
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()

# Are we certain that movies are getting shorter?
answer = 'no'

Netflix Movie Duration Analysis Report

Introduction

This report analyzes trends in Netflix movie durations over time, with a particular focus on identifying whether movies are getting shorter. The analysis was conducted using Python with pandas for data manipulation and matplotlib for visualization.

Methodology

Data Preparation:
- Loaded Netflix data from 'netflix_data.csv'
- Filtered for only movie content (excluding TV shows)
- Selected relevant columns: title, country, genre, release_year, and duration
Special Focus:
- Identified short movies (duration < 60 minutes) for closer examination
- Created a visualization of movie durations by release year
Visual Encoding:
- Applied color coding by genre:
  - Children: Blue
  - Documentaries: Green
  - Stand-Up: Orange
  - All others: Gray

Key Findings

Short Movies Analysis

The first 20 short movies (duration < 60 minutes) include:

Holiday specials (e.g., "6 Go! Go! Grey Carson Christmas")
Documentaries (e.g., "3 Seconds Divorce")
Children's content (e.g., "18B Things to do Before High School")
Various Christmas specials and short films

Duration Trends Visualization

The scatter plot "Movie Duration by Year of Release" shows:

A wide distribution of movie durations across all years
No clear downward trend in movie durations over time
Short movies (under 60 minutes) appear consistently throughout the timeline
Most movies cluster between 60-150 minutes regardless of release year

Genre Patterns

The color-coded visualization reveals:

Children's content (blue) tends to have shorter durations
Documentaries (green) show a mix of short and medium lengths
Stand-Up specials (orange) typically fall in the medium duration range

Conclusion

Based on the analysis:

Movies are not demonstrably getting shorter over time
Short movies (under 60 minutes) have consistently existed alongside standard-length features
Genre appears to be a stronger predictor of duration than release year

The answer to "Are we certain that movies are getting shorter?" is: No

Recommendations

Further analysis could examine duration trends within specific genres
Investigating the relationship between country of origin and duration might reveal additional patterns
A time-series analysis with moving averages could provide more nuanced insights about duration trends