This project aims to analyze and explore a dataset of movies from the United States, obtained from Kaggle. The analysis was conducted using the R programming language, with a focus on data visualization to identify patterns and trends within the film industry.
- Visualize and Explore Data: Understand trends in film production, cinema audience flow, and the relationship between film duration and critical reception.
- Identify the Impact of the 2008 Crisis: Analyze how the global financial crisis affected the quantity of films released and cinema attendance.
- Explore Release Strategies: Investigate the choice of release days for films and how this impacts their initial performance.
- Evaluate the Relationship Between Film Duration and Reviews: Determine if there is a significant correlation between the length of a film and its rating on review websites such as IMDb.
- Impact of the 2008 Crisis: A significant decrease in the number of films released was observed in the years following the 2008 financial crisis, with a slow recovery over the subsequent four years.
- Cinema Attendance Trends: Despite the decline in film production, the number of tickets sold increased, indicating sustained public interest in cinema even during economic hardship.
- Film Release Day Strategies: The majority of films are released on Fridays, leveraging the weekend to maximize initial audience reach. However, strategic releases on other days, particularly holidays, are also employed to extend the initial screening period.
- Correlation Between Film Duration and Critical Reception: No strong correlation was found between the duration of films and their IMDb ratings. Notable exceptions exist within certain genres, such as drama, which tend to exhibit slightly higher correlations.
- Language: R
- Key Libraries:
ggplot2,dplyr,readr
- Clone this repository:
git clone [https://github.com/Gabriel-Machado-GM/data_movies_A2.git](https://github.com/Gabriel-Machado-GM/data_movies_A2.git)