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https://github.com/srikarveluvali/dataanalysis

The "Dataset - Extraction, Analysis, and Visualization" project is a Python-based data analysis venture that focuses on exploring and interpreting the "Video Game Sales Analysis" dataset.
https://github.com/srikarveluvali/dataanalysis

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The "Dataset - Extraction, Analysis, and Visualization" project is a Python-based data analysis venture that focuses on exploring and interpreting the "Video Game Sales Analysis" dataset.

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# Dataset - Extraction, Analysis, and Visualization Project



### Presented at `PRAKALP2023 (KMIT)` on 5th August 2023



## Project Team



**Keshav Memorial Institute of Technology**, [IT-A]:



1. **Srikar Veluvali** (Roll Number: 22BD1A1264)

2. **Srikar Narsingoju** (Roll Number: 22BD1A1255)

3. **Sesha Sai Pratiek Yeggina** (Roll Number: 22BD1A1253)

4. **Anpur Phani Charan** (Roll Number: 22BD1A1201)



## Overview



The "Dataset - Extraction, Analysis, and Visualization" project is a Python-based data analysis venture that focuses on exploring and interpreting the "Video Game Sales Analysis" dataset. This dataset contains valuable information about video games, including their sales figures, ratings, genres, platforms, and more. Through meticulous analysis and visualization, the project aims to answer 15 essential questions related to the dataset. Additionally, it explores the practical implications of these answers in day-to-day life and game development.



## Dataset Description



The "Video Game Sales Analysis" dataset comprises the following columns:



| Column         | Description                                                                                      |

|----------------|--------------------------------------------------------------------------------------------------|

| Name           | The name of a video game.                                                                        |

| Platform       | The platform (PC, PS4, Xbox, etc.) for which a game is released.                                 |

| Year           | The release year of a video game.                                                                |

| Genre          | The genre of a video game.                                                                       |

| Publisher      | The publisher of a video game.                                                                   |

| NA_Sales       | Approximate total number of units sold (in million) of a video game in North America.           |

| EU_Sales       | Approximate total number of units sold (in million) of a video game in Europe.                   |

| JP_Sales       | Approximate total number of units sold (in million) of a video game in Japan.                    |

| Other_Sales    | Approximate total number of units sold (in million) of a video game in the rest of the world.    |

| Global_Sales   | Approximate total number of units sold (in million) of a video game worldwide.                   |

| Critic_score   | Aggregate score compiled by Metacritic staff.                                                    |

| User_score     | Score by Metacritic's subscribers.                                                               |

| User_count     | Number of users who gave the user_score.                                                         |

| Developer      | Party responsible for creating the game.                                                         |

| Rating         | The ESRB ratings.                                                                               |



## Project Questions



The project aims to answer the following 15 questions:



1. Which genre of video games is the most liked?

2. Which platform is the most used for playing games?

3. Which developer has released the most highly-rated games?

4. Which year had the highest number of game releases?

5. What are the most liked and most disliked video games?

6. How does the distribution of sales vary across different regions?

7. Which year had the highest total global sales?

8. Which developer has released the most games?

9. What are the highest rated games in each genre?

10. What are the highest rated publishers in each genre?

11. What is the best game in each ESRB Rating?

12. What are some popular games in PC, PS4, GBA, X360?

13. What are the most sold games in each region?

14. Which genre of video games has the most sales?

15. How do the answers to the above 14 questions aid in game development?



## Project Execution



The project utilizes Python for data extraction, analysis, and visualization. Pandas, NumPy, and Matplotlib are some of the core libraries leveraged for data manipulation and visualization. The dataset is thoroughly examined to uncover insights and trends related to video game preferences, sales, and ratings across various dimensions.



## Importance and Application



The answers to the 15 questions provide valuable insights into the video game industry and player preferences. Game developers and publishers can benefit from this analysis in the following ways:



1. **Game Development Decisions**: Understanding the most liked genres and highly-rated games helps developers in making informed decisions about the type of games to create and invest in.



2. **Platform Targeting**: Identifying the most popular gaming platforms assists in strategizing platform-specific game releases and optimizations.



3. **Publisher Strategies**: Recognizing the highest-rated publishers in each genre can guide potential collaborations and publishing decisions.



4. **Market Trends**: Analyzing the sales distribution across regions and over the years aids in identifying market trends and adapting marketing strategies accordingly.



5. **Competitor Analysis**: Exploring the most sold games in each region provides insights into successful titles from competitors.



6. **ESRB Rating Impact**: Understanding the best games in each ESRB rating helps in developing games suitable for specific age groups and target audiences.



## Conclusion



The "Dataset - Extraction, Analysis, and Visualization" project is a comprehensive exploration of the "Video Game Sales Analysis" dataset. By analyzing the data and answering 15 pertinent questions, the project sheds light on player preferences, popular genres, successful games, and regional market dynamics. These insights are highly beneficial for game developers, publishers, and marketers in making strategic decisions and understanding the industry landscape better.



[Link to GitHub Repository](https://github.com/SrikarVeluvali/dataanalysis)



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