D.F.

Movie Industry Correlation

Generic image of movie production equipment

Data Correlation using Python

View code on GitHub

Summary:

I conducted this data analysis project to uncover the key factors influencing movie popularity and to practice using the matplotlib and Seaborn Python libraries. I chose this dataset because it spans movie genres, budgets, and release years. By applying data visualization techniques and statistical analysis, I tested my hypothesis that a movie's budget has a high correlation with it's gross revenue.

Data Source:

Daniel Grijalvas's Kaggle page (September 2023).

Skills & Programs Used:

  • Python
  • Jupyter Notebooks
  • Data Correlation

Process

Gather Data

Download the Kaggle movie industry dataset and setup a Jupiter Notebook.

Check for missing information

Loop through columns and rows with Python.

Check data types

Check each column for correct data types.

Create visuals

Create scatter plots of film budget vs gross revenue and related correlation matrix.

Results

There is a positive relationship between the film budget and gross revenue.

Movie budget vs gross earnings scatterplot with trend line.

Future Posibilities

  • Determine if movie genres affect gross revenue.
  • Redo the project in R programming language.