Analyzing TMDB Movies: Trends, Insights, and Key Metrics

Arbash HussainArbash Hussain
5 min read

Introduction

Exploring the vast world of movies through the TMDB dataset reveals fascinating trends, standout films, and key figures shaping the film industry. Join me on a comprehensive analysis journey, covering various aspects of movie data, from general statistics to genre dynamics and beyond.

Analysis Notebook is available here.

General Statistics

Understanding the basic statistics provides a foundation for deeper insights. Here are some key metrics:

  • Average Budget: The average budget for movies is $10 million.

  • Average Revenue: The average revenue generated by movies is $30 million.

  • Average Runtime: The average runtime for movies is 90 minutes.

Distribution Plots

Average Movie Budget over the Years

A significant finding is the planned release of '100 Years' in 2115, which challenges conventional movie planning timelines. Notably, 2025 is projected to have the highest average movie budget of $11.82 million, driven by productions like 'John Wick Presents: Ballerina' and 'Avatar 3.'

Average Movie Revenue over the Years

The peak average revenue of $2.29 million was observed in 1997, marking a noteworthy year for box office successes.

Genre Analysis

Genre Trend over the Years

Documentary emerges as the most prolific genre since 1997, reflecting its feasibility with lower production budgets

Genre Distribution

Documentary and Drama dominate the industry, accounting for 30.9% and 27.2% of productions, respectively.

Top Genres based on Revenue

Despite its prevalence, Documentary doesn't feature among the top revenue-generating genres.

Top Genres based on Budget

Top Genres based on Ratings

Drama and Documentary dominate in terms of movie ratings, underscoring their popularity with audiences.

Top Genres based on Vote Count

"Action, Adventure, Science Fiction" and "Drama" lead in terms of vote counts, reflecting their broad appeal.

Revenue and Budget Analysis

ROI Analysis

Return on Investment (ROI) is calculated as:

$$(Revenue - Budget) / Budget$$

Movies with a budget of $0 have infinite ROI, which may be due to data entry errors or undisclosed budgets.

Note: The plotted movies are the movies, that comes after the movies with ROI as infinite.

Vote Analysis

Vote Distribution

The top 10 movies all have similar Vote Averages. However, when it comes to Vote Count, "Inception" has the highest, followed by "Interstellar" and "The Dark Knight", all of which are Christopher Nolan films.

Runtime Analysis

Runtime Distribution

While most movies fall within 1.5 hours, Some movies are as long as several days.

Top 10 Longest Movies

Modern Times Forever is the Longest Movie ever made of 240 hours. The movie shows how Helsinki's Stora Enso headquarters building would decay over the next few millennia. The film was originally projected against the building itself.

Director and Cast Analysis

Top Directors With Most No of Movies

Dave Fleischer and D.W. Griffith top the list of directors with the most movies, spanning eras of cinematic history.

Top Directors with Maximum Revenue Movies

Martin Scorsese and James Cameron stand out for their blockbuster hits, setting benchmarks with acclaimed films like "Taxi Driver" and the "Avatar" series.

Top Directors with Maximum Vote Count Movies

Christopher Nolan leads in terms of vote counts, underlining his influence on audience engagement.

Language and Production Country Analysis

Top Languages Movies are Produced In

As Expected, English dominates the global film landscape, accounting for 57.2% of productions.

Top Countries with Most no of Movies

Hollywood.

Cast Analysis

Top Artists with Most no of Movies

Mel Blanc was an American voice actor is 1900s, with no of movies worked in counting to 1061. Another Notable Name, Bess Flowers who was also known as "The Queen of the Hollywood Extras".

Top Artists with Most no of Vote Count

I'm Sure you all can see whats common in all Top 7, except for Frank Welker who is a voice actor behind shows like Scooby-Doo.

Observations

  • English Dominance: Most movies are in English (57.2%), making it the most common language. This helps movies reach a global audience easily.

  • Blockbuster Hits: Movies like "Avatar," "Avengers," and "Star Wars" make huge amounts of money worldwide. They set records and are loved by people everywhere.

  • Unique Films: Some films, like "TikTok Rizz Party" and "בראול סטארס בחיים האמיתיים-אלון קאט," stand out for different reasons.

  • Cultural Diversity: Movies show different cultures and stories. They help us understand each other better. From big action movies to small dramas, they teach us about people from all over the world.

  • Technology in Movies: Movies keep getting better with new technology. Things like CGI (computer-generated imagery) make movies look more real. This helps tell stories in new and exciting ways.

  • Future of Movies: The future looks bright for movies. Streaming services and new technologies will change how we watch and make movies. This means more types of movies and more ways to enjoy them.

Conclusion

In conclusion, the TMDB movie analysis provides a comprehensive look into the evolving landscape of the film industry. By examining various metrics such as budget, revenue, genre trends, and audience engagement, we uncover significant insights that highlight the dominance of certain genres, the impact of technological advancements, and the cultural diversity represented in films.

For a more detailed exploration, check out the full analysis notebook here. If you like these types of Blog Posts, Please Leave a like❤️and a follow✔, this motivates me to create more of these.

Thank you for reading, and stay tuned for more data analysis insights!

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Written by

Arbash Hussain
Arbash Hussain

I'm a student of Computer Science with a passion for data science and AI. My interest for computer science has motivated me to work with various tech stacks like Flutter, Next.js, React.js, Pygame and Unity. For data science projects, I've used tools like MLflow, AWS, Tableau, SQL, and MongoDB, and I've worked with Flask and Django to build data-driven applications. I'm always eager to learn and stay updated with the latest in the field. I'm looking forward to connecting with like-minded professionals and finding opportunities to make an impact through data and AI.