This project involves Exploratory Data Analysis (EDA) and data cleaning of a movie dataset. The primary goal is to analyze the dataset and uncover correlations between various attributes, with a focus on exploring the relationships between budget, gross revenue, movie production companies, and viewer votes.
The dataset used for this project contains information about movies, including details such as movie name, rating, genre, year of release, budget, gross revenue, production company, and viewer votes.
The central objective of this project was to identify correlations between the following variables:
- Budget and Gross Revenue: Assessing whether there exists a correlation between the budget invested in a movie and its gross revenue.
- Gross Revenue and Production Company: Investigating whether the production company influences the gross revenue of a movie.
- Gross Revenue and Viewer Votes: Exploring the relationship between viewer votes and the gross revenue of a movie.
Correlation analysis was conducted to quantify the strength and direction of these relationships.
In conclusion, this project provides valuable insights into budget, gross revenue, production companies, and viewer votes within the movie industry. The process of EDA and data cleaning played a crucial role in ensuring the accuracy of our analysis, ultimately revealing significant correlations that can inform industry strategies.