Movie Ratings Project
Data Analysis Project
This project is short and sweet! I took an example of a company called MovieLens to analyze their data. The goal here is to understand audience preferences. By the power of data science, I was able to find some interesting patterns and insights that drive viewer behavior.
Let’s explore together…
Assume this Movielens dataset is a valid source of movie ratings and user information. The data has some info about viewer preferences and movie characteristics. but in order to make a business decission, I took the info and performed statistics using Python.
First, I checked the Genres:
My analysis revealed a diverse landscape of genres, Drama and Comedy were the most popular choices. However, hidden gems like Film Noir and War films showed some interest from a few users.
This means focusing on the Drama and Comedy, Film Noir and War Films could be a huge advantage when it comes to business growth.
This took me to my next step which was understanding the users a little bit more.
The demographic factors of users was influencing movie preferences. Interestingly, male users made up 71% of the user base, and both genders rated movies similarly, indicating a shared appreciation for cinematic experiences.
Mmmm male users were more than females…that is really interesting!
Based on this graph, I highly recommend that the company incorporates more movies that target female users. This can increase the sales.
Did age affect the movie ratings?
Age played a role in shaping genre preferences. Older viewers tended to gravitate towards Film-Noir, while younger audiences were more drawn to Animation.
Here is my advise for the marketing team, use these findings for your targeted audience.
Another interesting insight is Star Wars Movies, here is why…
It was clear that a wide range of movies were showered with 5-star ratings. For example, Star Wars has been the most rated (583 times). on the other hand, Paris Was a Woman, Á köldum klaka (Cold Fever) have the least rating counts.
My Highlight:
Genre Popularity: Drama and Comedy reigned supreme, but Film Noir and War films garnered critical interest.
Gender Dynamics: Males made up the majority of the user base, but both genders rated movies similarly.
Age and Genre Preferences: Older viewers favored Film-Noir, while younger audiences were drawn to Animation.
Movie Ratings: Star Wars Movies are the most favorite movies among users.
My Advise:
I was able to gain valuable insights that can be used to create personalized recommendations, tailor marketing campaigns, and enhance the overall movie-watching experience. As the world of entertainment continues to evolve, data-driven analysis will remain a crucial tool for understanding and meeting the ever-changing needs of audiences.