We have the data for the 100 top-rated movies from the past decade along with various pieces of information about the movie, its actors, and the voters who have rated these movies online. we will try to find some interesting insights into these movies and their voters, using Python.

Full details and Implementation

• Jupyter Notebook

Some of the interesting insights

Average ratings by Males and Females varying across the genres

Inferences: Sci-Fi appears to be the highest rated genre in the age group of U18 for both males and females. Also, females in this age group have rated it a bit higher than the males in the same age group. Three more inferences/observations below:

• Inference 1: Sci-Fi genres appears most popular acoss all age group, while animation is most popular genres among women of all age groups as compared to others genres
• Inference 2: For under 18 age group and regardless of gender, almost all types of generes are popular
• Inference 3: In age group of under 18 and 18-29, most of the ratings given by male very close to each other across all the genres

Number of Votes for US and Non-US movies by US and Non-US voters

Inferences: Two inferences/observations below:

• Inference 1: Median of average rating for US based movies higher than non-US based movies irrespective of the voters (US voters and Non-US voters)
• Inference 2: US voters gave almost uniform ratings to non-US movies as compared to non-US people to the non-US movies

Votes from top 1000 voters across genres

Inferences: Few inferences/observations:

• Sci-Fi movies are popular across all age groups irrespective of gender and also among top 1000 voters.
• Comedy and Biography genres has no relation but still received similar votes. This seems to be a conincidence
• Thriller and Adventure received sort of similar votes. Both genres seems to be related to each other. Therefore, movies that has thriller, have a tendancy to be adventurous and vice-versa