https://github.com/ziraddingulumjanly/movie-dataset-analytics-using-r

Implementation of numerical R and R Shiny to the movie dataset.
https://github.com/ziraddingulumjanly/movie-dataset-analytics-using-r

datascience datavisualization r

Last synced: about 1 year ago
JSON representation

Implementation of numerical R and R Shiny to the movie dataset.

• Host: GitHub
• URL: https://github.com/ziraddingulumjanly/movie-dataset-analytics-using-r
• Owner: ziraddingulumjanly
• License: mit
• Created: 2024-12-01T14:01:39.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-01T14:09:38.000Z (over 1 year ago)
• Last Synced: 2025-03-25T22:44:57.128Z (about 1 year ago)
• Topics: datascience, datavisualization, r
• Language: R
• Homepage: https://www.kaggle.com/code/yousefsaeedian/movies-dataset-visualization?select=movies_updated.csv
• Size: 2.66 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Movie-dataset-analytics-using-R

By examining a dataset that contains important characteristics including budget, gross income, runtime, IMDb score, votes, and genre, this research investigates the workings of the film business. 

![image](https://github.com/user-attachments/assets/9f2ad1cc-9b4d-454c-a1e3-2c8090a2cddb)

Understanding the relationships between these elements and how they affect a film's success is the aim. We can learn more about trends like the evolution of film releases over time, the financial performance of various genres, and the connection between production budgets and film success by visualizing the data using plots such as bar plots, box plots, violin plots, heatmaps, and histograms. The comparison of genres in terms of runtime, IMDb ratings, and income is also highlighted in this research. The results provide data-driven insights into how several factors impact a film's success and industry trends, which is useful for investors, marketers, and producers.

# ZG2024