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This project is aiming to help movie investors to explore the changing trends of the movies added to Netflix from 2009 to 2021. It is analyzing multiple dimensions of the movie data, such as the date of being added to Netflix, movie genres, IMDB ratings, and movie ratings.
For this purpose, I utilized two datasets with over 6,000 Netflix movies to analyze the genre preferences, the changes of IMDB ratings, and the correlation between genres and movie ratings. Through the interactions of selecting, brushing, and filtering, movie investors can quickly discover meaningful information in three interactive visualizations. In this way, movie investors can not only gain an overview of the data at first but also get details by interacting with the visualization forms.