This project involves analyzing a movie ratings dataset to uncover insights and correlations between different movies. The dataset comprises user ratings for various movies. By merging this data with a movie titles dataset, we can explore patterns and trends. Initially, the project calculates the mean rating and the count of ratings for each movie. Visualization tools like histograms and scatter plots are used to display the distribution of ratings and their counts. Additionally, a correlation matrix is generated to identify relationships between movies based on user ratings, highlighting movies with similar rating patterns. This analysis can help in building a recommendation system by suggesting movies that are highly correlated with the user's preferences