Project status - Active

The objective of this project is to determine whether the Adventure genre has performed differently compared to other genres in the video game industry over the last four decades.

The following methods were utilized:

• Filtering
• Grouping
• Visualization

For the purposes of this project, we used the following technologies:

• Python 3.11.5
• Pandas
• Matplotlib.pyplot
• Seaborn
• Scipy.stats

Our dataset has 8 columns (Rank, Title, Publisher, Developer, Total Sales, Release Date, Last Update and Genre) and 1,034 rows. It contains the sales data of the video games with the most sales on a global scale, and it ranks them accordingly. Its oldest entry is from 1979 and its most recent entry is from 2023. It has some missing values (9 values for release dates and 24 values for total sales) but overall it is a comprehensive showing of video game sales.

We obtained our dataset from the following source: https://www.kaggle.com/datasets/mikegillotti/video-game-sales?select=video+game+sales+titles.csv

During our time working with the dataset, we found some new insights and decided to reformulate our original hypothesis to better utilize the information we had available.

After finishing the analysis, we can say that the Adventure genre has performed differently when compared to the other video game genres and that we can accept our hypothesis.