Movie Data Analysis Overview This project is an exploratory data analysis of movie ratings, titles, and genres from the MovieLens dataset. The goal was to perform a preliminary analysis on the data, uncovering basic statistical insights and relationships between key features. Key findings from this initial analysis include:

Average Rating: The average movie rating across the entire dataset is approximately 3.53 out of 5, with a standard deviation of 1.06. This suggests that while there is a spread in ratings, the distribution is centered around a moderately positive score.

Rating Distribution: The ratings range from a minimum of 0.5 to a maximum of 5.0. The dataset includes a wide variety of opinions, from very negative to overwhelmingly positive.

Movie ID Correlation: A correlation analysis revealed a very weak negative relationship (correlation coefficient of approximately -0.09) between the movieId and the rating. This indicates that the chronological or numerical assignment of a movie ID does not have a significant linear impact on its rating.

This project was developed as part of an academic journey to practice fundamental data analysis techniques using Python libraries such as pandas and matplotlib.

Requirements To run this notebook, you need to have the following Python libraries installed:

pandas

matplotlib

os (standard library)

Data Source The data used in this project is the ml-25m dataset, a large movie rating dataset compiled by GroupLens. The data was sourced from their official website: https://grouplens.org/datasets/movielens/.

Author Name: tpchiripa

Email: tpchiripa@gmail.com