Movie_Recommandation_System
Based on a combination of an existing dataframe and API ressources from oMBD, the API website from (iMBD) we are trying to identify the most commercially successful genre and optimal runtime for a new movie to be released in the near future, given current audience preferences and market trends .
After the elaboration of th business question we came up with the 3 following hypothesis, that will be accepted or rejected, after our analysis:
H1:Genre Popularity:
'Genres with higher average ratings and vote counts in the past 10 years will likely be more successful in terms of box office earnings’
H2:Audience Trends:
'There is a correlation between a movie's financial success and the popularity of its featured actors.
H3: Runtime Preference:
'‘Movies with a runtime between 120 and 150 minutes tend to perform better commercially.’
Data you are using (and comments, main challenges, strengths & weaknesses, etc…)
Questions you want to answer (maybe divided by different topics). Each question should include a conclusion written in a markdown cell.
Describe the methodology you are using, explaining the steps upi took for data cleaning, analysis, etc.
Conclusions after your analysis.
Further questions.
OMDB API link- https://www.omdbapi.com/
Dataset link- https://www.kaggle.com/datasets/amanbarthwal/imdb-movies-data
Git Hub link- https://github.com/Marc-Bouche/Movie_Recommandation_System
Trello link- https://trello.com/b/Hj5kYts9/project-movie-recommendation-system