Global Video Game Sales and Reviews

Global Video Game Performance: Sales, Reviews, and Rankings

By Andy Bramwell [source]

About this dataset

The elements covered in this well-curated dataset include: The ranking of the game based on global sales under the column 'Rank'. This metric provides perspective on how popular or successful a particular game has been across countries in comparison to others during its time. Noting that video games' popularity could vary greatly from one geography to another due to factors like cultural nuances, gamer preferences, etc., regional sales have been marked separately for North America (North America), Europe (Europe), Japan (Japan) as well as for other parts of the World excluding these three regions under the column 'Rest of World'.

For easy identification among massive chunks of data, we've included each game's title (Game Title) along with additional categorization based on their genre (Genre). From action-packed adventures to strategic board-like scenarios or enchanted magic realms - classifications cover it all! In addition, detailed information about publishers can be found under 'Publisher', which grants insights about leading companies dominating market shares.

Further details expand into mentioning platforms such as PS4, Xbox, PC where these games can be played under 'Platform'. A unique attribute covered in this database is ‘Review’. Given that critique ratings play an influential role in engaging new players into trying out a particular video game or boosting existing user morale regarding their choice; this numeric representation ranging typically from 1-10 vividly captures public opinion about them.

Lastly, just for keeping tabs on ever-evolving gaming technology standards where newer versions often outshine predecessors irrespective of actual gameplay quality itself; having release years mentioned ('Year') proves beneficial for categorizing them chronologically. This helps correlate whether higher sales figures can sometimes merely be indicative of more people having access to necessary high-end gaming hardware during later periods.

In essence, this dataset titled ‘Video Games Sales.csv’ holds immense potential for informative deep-dives into the Video Game industry's trends and paradigms, forming a solid foundation for market research, academic purposes or personal projects

How to use the dataset

This dataset provides extensive information about various video game titles, their sales performance across multiple regions, publisher details and game reviews. Follow the steps outlined below to make the most out of this remarkable dataset!

1. Game Research & Evaluation:

With columns such as 'Game Title', 'Genre' and 'Review', you can research on particular games or genres that interest you. You can evaluate a game based on its review scores, delving into what makes a top-rated game.

2. Publisher Analysis:

The 'Publisher' column lets you track which publishers are behind the most successful games in terms of sales and reviews. This analysis could be useful for people interested in business trends in gaming industry or trying to identify potential innovative publishers.

3. Regional Market Trend Identification:

You can use data from columns like ‘North America’, ‘Europe’, ‘Japan’ and ‘Rest of World’ to study regional market trends for certain genres or platforms; it might enable one to recognize patterns over time or cultural preferences with regard to video games.

4. Global Sales Analysis:

Using the 'Global' column, you could observe which games have been globally successful, going beyond regional preferences by genre or platform.

5. Platform Insight:

The platform on which a particular game is available is another significant factor (e.g., PC, PS4, Xbox). By utilizing the data contained in this dataset regarding platforms, one may learn how platform choice impacts global sales as well as discern any correlation between preferred platform types among specific regions.

Remember that every statistical analysis begins with knowing your data - dive deep into each variable; explore patterns within variables before looking at correlations between different fields.

Don't forget - when engaged with comprehensive datasets like these - creativity is your only limit! Happy analyzing!

Research Ideas

• Trend Analysis: This dataset can be used to analyze the trends in video game preferences over the years based on genre, publisher, platform and region. It can provide interesting insights into how consumer tastes have evolved with time and which game genres are becoming more popular.
• Sales Forecasting: U...

This dataset contains a list of video games with sales greater than 100,000 copies. It was generated by a scrape of vgchartz.com.

Fields include

• Rank - Ranking of overall sales

• Name - The games name

• Platform - Platform of the games release (i.e. PC,PS4, etc.)

• Year - Year of the game's release

• Genre - Genre of the game

• Publisher - Publisher of the game

• NA_Sales - Sales in North America (in millions)

• EU_Sales - Sales in Europe (in millions)

• JP_Sales - Sales in Japan (in millions)

• Other_Sales - Sales in the rest of the world (in millions)

• Global_Sales - Total worldwide sales.

The script to scrape the data is available at https://github.com/GregorUT/vgchartzScrape. It is based on BeautifulSoup using Python. There are 16,598 records. 2 records were dropped due to incomplete information.

General video gaming use among the U.S. population increased significantly during the COVID-19 pandemic. Between May and December 2020, U.S. teens aged 15 to 19 years spent an average of 112.8 daily minutes on playing games and using computers for leisure, up from 73.8 minutes per day in the corresponding period of 2019. In 2024, the daily time spent on such activities among this age group decreased to 78.6 minutes per day.

In July 2025, total video games sales in the United States amounted to **** billion U.S. dollars, representing a five percent year-over-year increase. Generally speaking, the video game industry has its most important months in November and December, as video game software and hardware make very popular Christmas gifts. In December 2024, total U.S. video game sales surpassed **** billion U.S. dollars. Birth of the video game industry Although the largest regional market in terms of sales, as well as number of gamers, is Asia Pacific, the United States is also an important player within the global video games industry. In fact, many consider the United States as the birthplace of gaming as we know it today, fueled by the arcade game fever in the ’60s and the introduction of the first personal computers and home gaming consoles in the ‘70s. Furthermore, the children of those eras are the game developers and game players of today, the ones who have driven the movement for better software solutions, better graphics, better sound and more advanced interaction not only for video games, but also for computers and communication technologies of today. An ever-changing market However, the video game industry in the United States is not only growing, it is also changing in many ways. Due to increased internet accessibility and development of technologies, more and more players are switching from single-player console or PC video games towards multiplayer games, as well as social networking games and last, but not least, mobile games, which are gaining tremendous popularity around the world. This can be evidenced in the fact that mobile games accounted for ** percent of the revenue of the games market worldwide, ahead of both console games and downloaded or boxed PC games.

Video Games Sales Dataset

About Dataset

This Dataset provides up-to-date information on the sales performance and popularity of various video games worldwide. The data includes the name, platform, year of release, genre, publisher, and sales in North America, Europe, Japan, and other regions. It also features scores and ratings from both critics and users, including average critic score, number of critics reviewed, average user score, number of users reviewed, developer, and rating. This comprehensive and essential dataset offers valuable insights into the global video game market and is a must-have tool for gamers, industry professionals, and market researchers. by source

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Columns

Research Ideas / Data Use

• Market Analysis: The video game sales data can be used to analyze market trends and identify popular genres, platforms, and publishers. This can be useful for industry professionals to make informed decisions about game development and marketing strategies.
• Sales Forecasting: The sales data can be used to forecast future trends and predict the success of upcoming games.
• Consumer Insights: The data can be analyzed to gain insights into consumer preferences and buying habits, which can be used to tailor marketing strategies and improve customer satisfaction.
• Comparison of Competitors: The data can be used to compare the sales performance of competing video games and identify market leaders.
• Gaming Industry Performance: The data can be used to evaluate the overall performance of the gaming industry and track its growth over time.
• Gaming Popularity by Region: The data can be analyzed to determine which regions are the largest markets for video games and which genres are most popular in each region.
• Impact of Reviews: The data can be used to study the impact of critic and user reviews on sales and the relationship between scores and sales performance.
• Gaming Trends over Time: The data can be used to identify trends in the gaming industry over time and to track the evolution of the market.
• Gaming Demographics: The data can be used to analyze the demographic makeup of the gaming audience, including age, gender, and income.
• Impact of Gaming Industry on the Economy: The data can be used to evaluate the impact of the gaming industry on the economy and to assess its contribution to job creation and economic growth.

Acknowledgements

if this dataset was used in your work or studies, please credit the original source Please Credit ↑ ⠀⠀⠀

Global Video Game Sales and Ratings

Global Overview of Video Game Sales, User and Critic Ratings

By LearnToViz [source]

About this dataset

The Video Game Sales and Ratings Dataset is a comprehensive collection of data points concerning the video game industry. Predominantly prepared with the intent of facilitating data-driven decision making, this dataset serves as an essential tool for game developers, publishers, critics and researchers interested in examining trends and patterns within this burgeoning domain.

Consisting of a wide gamut of variables such as platform availability, genre classification, publishing entities involved, developers responsible for creating the games to understanding their global reach through sales figures across various regions including North America (NA_Sales), Europe (EU_Sales), Japan (JP_Sales) and even other diverse regions consolidated under 'Other_Sales'- this dataset offers an in-depth exploration into the intricacies inherent in video gaming business dynamics.

Furthermore, since it includes both critic reviews and user ratings along with associated count metrics that denote how many individuals voiced their opinion via these ratings; it not only lends performance transparency but also ensures broad inclusivity to make assessment more holistic. Therein lies its uniqueness: aptly capturing both market reception (sales diligence) along with perceptual quality review criteria led by expert critics and public users alike.

To facilitate a thorough understanding our array fields also cover critical detail including 'Year_of_Release', offering temporal insight into when these games arrived on market shelves around the world; how they have been categorized ('Genre'), which platforms host these games ('Platform'); who took responsibility for developing them ('Developer') & then getting them promoted or distributed to target consumer base ('Publisher').

Our 'User_Count' column offers further informed perspective about community engagement levels while inclusion of 'Rating' variable provides standards-based categorical info about age-specific content appropriateness as per internationally recognized rating agency- Entertainment Software Rating Board. With all these multifaceted components combined together in one robust dataset- rich analysis like sales forecasting, trend identification or patterns discernment among others can be most effectively accomplished.

By providing such a wealth of diverse and detailed information, this dataset opens up a world of possibilities for analysis and investigation that stretches the boundaries of what we can learn about video games- both as entertainment artifacts and as commercial entities. Overall this dataset stands to be an informative resource to better comprehend the complex dynamics shaping the globally-flourishing video game industry

How to use the dataset

This guide will provide tips on how to effectively navigate this dataset for both beginners in Data Science and researchers with more advanced skills.

• Getting Started: Familiarize yourself with the general contents of the data file by checking all column descriptions. This will give you an overarching understanding of what kind of data you can find in this dataset.

• Conceptual Understanding: Understand the context each column provides for every unique video game title:

• Platform: Can help highlight which gaming platforms have optimal sales.

• Year_of_Release: Can provide insights into gaming market trends or allow creation of timeline analysis.

• Genre: Useful for analyzing popular genres or identifying niche markets.

• Publisher / Developer: Monitoring these can reveal industry leaders or developers that consistently produce well-received games.

• NA_Sales / EU_Sales / JP_Sales / Other_Sales / Global_Sales : These columns are instrumental in performing regional market analyses, studying performance indicators globally, or comparing regional popularity differences versus global acceptance levels.

• User Scores Vs Critic Scores: These two columns might present divergent perspectives about a video-game's quality; critics might highly rate games users didn't favor & vice versa. Exploring these discrepancies could prove intriguing!

• Choosing Tasks:

  • Exploratory Data Analysis (EDA): This could be your first step if you're starting out learning how to handle datasets; identify missing values/nulls & their impact on data analysis; extract meaningful summary statistics.

  • Data Visualization: Generate charts, scatter plots, heat maps etc. to encapsulate sale...

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Data obtained using a program from the site vgchartz.com.

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"Founded in 2005 by Brett Walton, VGChartz (Video Game Charts) is a business intelligence and research firm and publisher of the VGChartz.com websites. As an industry research firm, VGChartz publishes video game hardware estimates every week and hosts an ever-expanding game database with over 55,000 titles listed, featuring up-to-date shipment information and legacy sales data. The VGChartz.com website provides consumers with a range of content from news and sales features, to reviews and articles, to social networking and a community forum." - from the site vgchartz.com.

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"Since the end of 2018 VGChartz no longer produces estimates for software sales. This is because the high digital market share for software was making it both more difficult to produce reliable retail estimates and also making those estimates increasingly unrepresentative of the wider performance of the games in question. As a result, on the software front we now only record official shipment/sales data, where such data is made available by developers and publishers. The legacy data remains on the site for those who are interested in browsing through it." - from the site vgchartz.com.

What can you do with the data set?

If you are new to data analytics, try answering the following questions: - in what year did the active growth in the number of video games produced begin? What year was the most successful from this point of view? What can you conclude if you look at the number of video games released by country? - on what day and month were the largest number of video games released? What could be the reason for this pattern? - is there a dependence of the number of copies sold on the ratings of critics or users? - which gaming platforms, publishers and developers are the most common (the largest number of video games have been released over time)? - which gaming platforms, publishers and developers have the largest number of video game copies sold (over all time, the total number of copies sold was the largest)?

If you have enough experience, try solving a regression problem. Train a model that can predict the number of copies sold of video games: - what signs can be used to prevent leakage of the target variable? - how do outliers affect the quality of the model? - which metric should be chosen to evaluate the model? - can adding new data improve the predictive ability of the model? - does the trained model have signs of heteroscedasticity of the residuals? How does this affect the predictive ability of the model? What can you do?

Field descriptions:

The data contains the following fields: 1. name – name of the video game. 2. date - release date of the video game. 3. platform - gaming platform (All – all gaming platforms, Series – all video game series). 4. publisher – publisher. 5. developers - developer. 6. shipped - the number of copies sent (relevant for records with the values All and Series in the platform field). 7. total - total number of copies sold (millions of copies). 8. america - number of copies sold in America (millions of copies). 9. europe - number of copies sold in Europe (millions of copies). 10. japan - number of copies sold in Japan (millions of copies). 11. other - other sales in the world. 12. vgc - rating VGChartz.com. 13. critic - critics' assessment. 14. user - user rating.

Found an error or inaccuracy in the data?

This dataset is the result of painstaking work. After collection and systematization, the data is checked for integrity and correctness. If you notice an error or inaccuracy in the data, or have a suggestion on how to improve the data set, please let me know.

You can look at working with data in my github repository.

In 2024, Call of Duty: Black Ops 6, published by Activision Blizzard, was the top-selling video game in the United States based on dollar sales. EA Sports College Football 25 was in second place, followed by the shooter Helldivers II. The dominance of AAA gaming productions In the video-game industry, AAA (pronounced Triple-A) is a classification that is used when describing or talking about video games that are produced and distributed by major or mid-tier video game developers. These game productions typically have a large development and marketing budget. When looking at the top-selling video games in the United States in 2023, the majority of the best-selling titles were produced by the biggest gaming companies worldwide. In addition to several publicly listed video game companies, gaming platform owners Sony and Nintendo also produce top-selling games with Sony's Marvel's Spider-Man 2 and Nintendo’s The Legend of Zelda: Tears of the Kingdom also reaching rank four and five, respectively. Spotlight: Call of Duty series Activision Blizzard’s long-running Call of Duty franchise usually features in many end-of-the-year lists as it is one of the top-grossing and best-selling gaming franchises worldwide. As of April 2021, the Call of Duty (CoD) series has generated more than 400 million lifetime unit sales and the most recent entry in the series is Call of Duty: Modern Warfare III, which was released in November 2023. The annual releases of the game series are rotated between several game development studios which are subsidiaries of Activision Blizzard: Infinity Ward, Sledgehammer Games, Treyarch, and Raven Software.

Nintendo Switch Dedicated Video Game Sales Units: 2017-2020

Quantifying Unit Sales Performance

By Charlie Hutcheson [source]

About this dataset

This dataset contains dedicated video game sales unit data for the Nintendo Switch platform from 2017 to 2020, as reported by official Nintendo Investor Relations. It provides an snapshot of consumers’ buying trends over the past four years and helps us gain insightful understanding into the introduction, expansion and success of this platform across global markets. The data can be used to analyze multiple aspects such as performance of specific titles/genres/franchises, changes in market expectations over time and more. This chart helps to visualize the dynamic changes in these sales units over that four-year timeframe. From this chart we can gain valuable understanding about how successful various releases have been on this gaming console, what titles drove its popularity levels and more useful insights that could help other developers in creating future products for similar platforms

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How to use the dataset

This dataset contains historical sales unit data for the Nintendo Switch platform from 2017 to 2020. The original visualization provides a clear visual representation of the number of sales units over time. It is easy to discern which months have seen higher levels of sales, and which have seen lower ones.

Using this dataset, users can perform various analyses on the results to gain further insights into consumer trends and buy behavior associated with the Nintendo Switch platform. Users can also glean information on pricing strategies taken by Nintendo as well as consumer preferences over time in order to inform future business decisions.

In order to maximize use of this data set, users are encouraged to consider questions such as: What types of games do consumers prefer? How has their taste changed over time? What is the average amount spent per game by region or country? How often are certain consoles purchased or rented? And what role do discounts or promotions play in influencing purchasing decisions? By exploring these questions, users can begin understanding how different factors may be affecting overall demand for a product associated with the Nintendo Switch platform.

By analyzing this dataset, users also get an insight into how other competitors within the industry are affecting sales performance and allowing them take steps necessary for either surpassing competitors or maintaining dominance through suitable tactics like improved marketing campaigns or better-priced products that appeal more strongly customers’ needs and wants . In addition, examining this data enables companies keenly understand customer demands at detailed levels including whether customers prefer switch game bundles with extra features like custom skins etc., titles released during special times such as a holiday season that incite strong demand among buyers and also relevant discounts/promotions offered during times when people want/needing much needed break from regular routine life.. Ultimately , gaining greater insight into customer objectives allows firms efficiently manage their costs while maximizing profits through effective decisions based on reliable datasets such as that contained in this one instead rarely updated manual counts/observations which dont just lack comprehensiveness but also accuracy in nature.

Research Ideas

• Producing a mobile application to present the sales units in an intuitive and interactive way;
• Utilizing the data for machine learning algorithms to predict and analyze trends in Nintendo Switch dedicated video game sales units;
• Creating infographics and visualizations that can be used for promotional materials or to educate customers about the success of Nintendo Switch dedicated game sales

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the or...

Video Game Sales and Ratings

Global Video Game Sales, Ratings, and User Insights

By Sumit Kumar Shukla [source]

About this dataset

The Video Games Sales and Ratings Dataset provides an in-depth view into the dynamic world of video games, offering a comprehensive analysis of sales and ratings across diverse platforms and publishers. This dataset contains valuable facets of information that bring to light various insights about the video game industry over the years.

The dataset includes critical aspects such as the Name of each individual video game which was accounted for in this data aggregation process. The name captures the branded title under which a specific game is marketed and sold within the global market.

Additionally, key details on numbers relating to sales are included as well; such as Global Sales which refers to the total number of copies each individual game has sold on all indicated platforms worldwide- recorded in millions; NA_Sales representing accumulated sales figures from North America- also captured in millions; JP_Sales showing similarly compiled data specifically for Japan and EU_Sales for Europe respectively, both equally reflected in millions.

There is more insightful granularity embedded within our Dataset including Other_Sales, that tallies copies sold outside of specifically mentioned regions (North American, European & Japanese markets), expanding our insights into an even wider spectrum.

This Dataset not only shares hard figures on sales but also valuable opinions voiced by professional critics & users alike with Critic_Count & User_Count detailing how many individuals had reviewed any specific product with Critic Score being an averaged rating given by critics while User Score echoes sentiments from regular end-users or consumers who purchased these products - showcasing public opinion on these games.

Critical parameters defining characteristics essential related to gaming experiences like Genre detail distinctive aspects or themes around gameplay found within respective titles while Platform lists down where these titles were played specifically (between options like PC based or console front like PS4, Xbox etc.). The Publisher spotlights deserved attention onto those who took upon themselves to disseminate this creative work unto masses while Developer's name elucidates those daring visionaries who birthed unique experiences with their own hands through coding & design.

Last but not least, the Rating as per ESRB (Entertainment Software Rating Board) is included to give a sense of what demographic brackets/age each title was intended and marketed for - an essential aspect for parents and individuals mindful about content consumed within video games.

In short, this Video Games Sales and Ratings Dataset offers insights into the vast world of video gaming from various impactful perspectives serving as a valuable learning resource to anyone interested in gaining understanding or deploying data-driven strategies within any facet of this industry

How to use the dataset

Exploring the Dataset

The first step in analyzing this dataset is getting familiarized with its structure:

• Name: This attributes refers to the name of each video game included in the dataset.
• Platform: This denotes the platform(s) on which a particular game operates.
• Year_of_Release: The year when a particular game was launched is depicted by this attribute.
• Genre: It indicates what type of genre does a certain video game correspond to.
• Publisher & Developer: These fields detail out which company has published and developed every game respectively.
• NA_Sales, EU_Sales, JP_Sales & Other_Sales: These signify sales numbers from North America (NA), Europe(EU), Japan(JP) regions as well as other parts of world respectively (measured in millions).
• Global_Sales: This category refers to overall international sales for each described gaming product.
• Critic_Score & User_score: It represents average scores attributed by critics or users; where higher indicates better reception mostly measured on a scale often spanning 0–10 or 0–100.
• Critic_Count & User_Count: They denote how many critics/users have rated particular games respectively. -**Rating**: ESRB's categorization for games (e.g., E for Everyone,T for Teen,M for Mature etc.) is portrayed through it.

Data Analysis Recommendations

Here are some suggestions based on common practices:

• Sales Performance: You can examine sales figures categorized regionally or globally, leading to understanding which games have ...

As of 2025, puzzle games had the overall shortest time between installation and first purchase across mobile operating systems. On Android, the time to first purchase was 1.6 days after installation, compared to 1.7 days on iOS. The largest discrepancy occurred with match games, with only 1.7 days between installation and first purchase on iOS compared to three days on Android.

🎮 Global Video Game Sales and Ratings Dataset

📘 Overview

This dataset provides a detailed view of video game sales performance, critical reception, and developer/publisher data across multiple gaming platforms. It’s perfect for exploring how factors like genre, publisher reputation, and critic scores influence global sales — and for building predictive models in data science and machine learning.

📊 Dataset Summary

💡 Potential Use Cases

• Predict global sales based on critic ratings and regions
• Analyze how game genres perform across regions
• Compare publisher or developer performance
• Study the impact of platform exclusivity on total sales
• Build recommendation systems for games

🧠 Example Ideas

• Machine Learning: Train regression models to forecast sales based on critic scores, genre, and platform.
• Visualization: Create dashboards showing top publishers, regional trends, or sales by genre.
• Statistical Insights: Correlation between critic score and sales success.

📅 Source

Compiled and formatted for analysis — suitable for both beginners exploring EDA (Exploratory Data Analysis)** and advanced users** working on predictive analytics projects.

This is a dataset of 10 very famous video games in the world.

These include

• Among Us
• Apex Legends
• Fortnite
• Forza Horizon
• Free Fire
• Genshin Impact
• God of War
• Minecraft
• Roblox
• Terraria

There are 1000 images per class and all are sized 640 x 360. They are in the .png format.

ThisDataset was made by saving frames every few seconds from famous gameplay videos on Youtube

Context

Join your crewmates in a multiplayer game of teamwork and betrayal! Play online or over local wifi with 4-10 players as you attempt to hold your spaceship.

Content

This dataset contains a subset of cleaned up gameplay data assembled by Twitch user ScaldingHotSoup. The complete dataset is available in this Google Sheet. The dataset on Kaggle is cleaned up for easier analysis in R or Python. It's made up of four tabs from the original dataset:

• Player Analysis: Analysis of individual players
• Player Record: Counts for individual players
• Game Feed: Events that happened in a given game
• Crewmate Voting: How crew voted on each day of gameplay

Acknowledgements

Thanks to Twitch user ScaldingHotSoup for assembling the original dataset from which this is derived.

Global Video Game Sales

Analyzing Platform-Genre Dynamics in the Top 100 Games

By [source]

About this dataset

This dataset, sourced from vgchartz.com, offers a wealth of insights into the dynamics between platform and genre for the top 100 video games worldwide. Observe which platforms are driving global sales, what genres have been most successful in different regions across the world, and how both of these factors have changed over time. Analyze this data to inform your understanding of the gaming industry and discover trends propelling game developers to success!

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Featured Notebooks

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How to use the dataset

This dataset provides an excellent snapshot of the top 100-selling video games, along with their respective platforms, genres and publishers. By analyzing the data provided in this Kaggle dataset, it is possible to gain insights on the popularity of different gaming platforms and the most successful genres associated with those platforms. Additionally, one can also observe which publishers have achieved success in publications of multiple series or even single titles.

In order to begin making use of this dataset effectively, start by looking through each column and determining how it might be contributing useful information. This dataset contains 11 columns: rank (ranked from 1-100), name (name of title), platform (platform game was released for), year (year game was released), genre (genre classification for title), publisher (publisher responsible for release), NA_sales & EU_sales & JP_sales & other_sales (total fractions of sales worldwide by region) & global_sales(total fractional sales worldwide). These columns can be used to draw comparisons between various specific aspects or discover general trends about certain parts of the industry over a prolonged period of time.

Those wanting to understand more specifically how certain releases have performed over time should consider using graphs/charts to depict their findings; as diagramatic visual representations always make understanding easier while also providing insight that wouldn’t have been visible through raw data alone. To further narrow down your focus on subsets within subsets, implement crosstabs! Keywords are also incredibly helpful when sifting through large amounts - search queries allow you to find further info based on detailed parameters while restriction allows fine tuning these queries into very specific datasets you need in order to answer any given question properly!

Research Ideas

• Probing the relationship between video game expenditure and user satisfaction to understand consumer behavior.
• Examining the most popular platform-genre combinations in the top 100 games to inform game development decisions.

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: vgsales.csv | Column name | Description | |:-----------------|:-----------------------------------------------------| | Rank | Ranking of the game based on global sales. (Integer) | | Name | Name of the game. (String) | | Platform | Platform the game was released on. (String) | | Year | Year the game was released. (Integer) | | Genre | Genre of the game. (String) | | Publisher | Publisher of the game. (String) | | NA_Sales | Sales of the game in North America. (Float) | | EU_Sales | Sales of the game in Europe. (Float) | | JP_Sales | Sales of the game in Japan. (Float) | | Other_Sales | Sales of the game in other regions. (Float) | | Global_Sales | Total sales of the game worldwide. (Float) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Game Boy Games

Games released for game boy

About this dataset

How do you determine whether a video game is good or bad? There are many factors to consider, from graphics to gameplay to story. But one of the most important factors is reception – how well the game is received by players and critics.

The Game Boy was one of the most popular handheld gaming consoles of all time, and it had a huge library of games. Some of these games were beloved by fans and critics alike, while others were met with indifference or even outright hostility.

So, what makes a good Game Boy game? And what makes a bad one? This dataset attempts to answer those questions by collecting information on every Game Boy game ever released, including their reception von players and critics

How to use the dataset

The dataset can be used to examine the successes and failures of individual games or groups of games on the Game Boy platform

Research Ideas

• Examining the most and least successful games on the Game Boy platform in terms of sales, reviews, or player engagement.
• Determining which developers or publishers were most successful at releasing quality games on the Game Boy platform.
• Investigating how the release date impacted the success of a Game Boy game in different regions

Acknowledgements

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: df_1.csv | Column name | Description | |:-------------------|:---------------------------------------------------------------| | Title | The title of the Game Boy game. (String) | | Developer(s) | The developer(s) of the Game Boy game. (String) | | Publisher(s) | The publisher(s) of the Game Boy game. (String) | | Release date | The release date of the Game Boy game. (Date) | | Release date.1 | The release date of the Game Boy game in North America. (Date) | | Release date.2 | The release date of the Game Boy game in Europe. (Date) |

File: df_4.csv | Column name | Description | |:-----------------|:-------------------------------------------------------------| | Title | The title of the Game Boy game. (String) | | Developer(s) | The developer(s) of the Game Boy game. (String) | | Publisher(s) | The publisher(s) of the Game Boy game. (String) | | Release date | The release date of the Game Boy game. (Date) | | Region | The region in which the Game Boy game was released. (String) |

File: df_3.csv | Column name | Description | |:-----------------|:-------------------------------------------------------------| | Title | The title of the Game Boy game. (String) | | Developer(s) | The developer(s) of the Game Boy game. (String) | | Publisher(s) | The publisher(s) of the Game Boy game. (String) | | Region | The region in which the Game Boy game was released. (String) |

File: df_2.csv | Column name | Description | |:-------------------|:---------------------------------------------------------------| | Title | The title of the Game Boy game. (String) | | Developer(s) | The developer(s) of the Game Boy game. (String) | | Publisher(s) | The publisher(s) of the Game Boy game. (String) | | Release date | The release date of the Game Boy game. (Date) | | Release date.1 | The release date of the Game Boy game in North America. (Date) | | Release date.2 | The release date of the Game Boy game in Europe. (Date) |

File: df_6.csv

File: df_5.csv

Wii U Games: A Comprehensive Sorted List

From AAA to Indie Games

About this dataset

This dataset includes a comprehensive list of all Wii U games, both physical copies and those available for download from the Nintendo eShop. The games are sorted by genre, developer, publisher, and release date, making it the perfect resource for gamers looking to find new and exciting titles for their collection. Whether you're a fan of AAA blockbusters or niche indie titles, this dataset has something for everyone. So check it out today and see what amazing games you might have been missing out on!

How to use the dataset

To use this dataset, simply choose the file you would like to download and open it in your preferred spreadsheet software. From there, you can sort the games by any of the given columns

Research Ideas

• This dataset can be used to find the most popular genres of Wii U games.
• This dataset can be used to find the most popular developers of Wii U games.
• This dataset can be used to find the most popular publishers of Wii U games

Acknowledgements

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: df_1.csv | Column name | Description | |:-------------------|:--------------------------------------------------------------| | Title | The name of the video game. (String) | | Genre | The genre of the video game. (String) | | Developer(s) | The developer(s) of the video game. (String) | | Publisher(s) | The publisher(s) of the video game. (String) | | Release date | The release date of the video game. (String) | | Release date.1 | The release date of the video game in North America. (String) | | Release date.2 | The release date of the video game in Europe. (String) | | Release date.3 | The release date of the video game in Japan. (String) | | Ref. | A reference to the source of the data. (String) |

File: df_4.csv | Column name | Description | |:--------------|:--------------| | 0 | | | 1 | |

File: df_3.csv

File: df_2.csv | Column name | Description | |:-------------------|:--------------------------------------------------------------| | Title | The name of the video game. (String) | | Genre | The genre of the video game. (String) | | Developer(s) | The developer(s) of the video game. (String) | | Publisher(s) | The publisher(s) of the video game. (String) | | Release date | The release date of the video game. (String) | | Release date.1 | The release date of the video game in North America. (String) | | Release date.2 | The release date of the video game in Europe. (String) | | Release date.3 | The release date of the video game in Japan. (String) | | Ref. | A reference to the source of the data. (String) |

File: df_6.csv

File: df_5.csv | Column name | Description | |:--------------|:--------------| | 0 | | | 1 | |

Context

The dataset featured below was created by gathering data from various sources across the internet including *Wikipedia *and VGCharts. This dataset contain sales data on every single Nintendo 64 game. It tracks many different variables about each title. I would love to continue this journey and create a dataset for GameCube and other systems as well.

Content

The number of columns for this dataset is 17 and the total number of rows is 388.

## Variables: GameID: Acts as the unique identifier for each title. *Title: *The title of the video game. There are a total of 388 titles for the Nintendo 64. System: Of course, since this is a Nintendo 64 dataset, then for each title the system is “Nintendo 64”, but I would love to develop other datasets for Nintendo Consoles. Genre: What is the overall type of game? Sub-Genre: Some titles have a sub-genre or more exact type of game that it is. For example, while the game “All-Star Tennis ‘99” has a genre of "Sports", specifically, it is a “Tennis” game. So therefore, the sub-genre is “Tennis.” Release Date: The day the title was released. Publisher: The company that is responsible for publishing the game. Developer: The company that is responsible for developing the game. Mode: Single-Player or Multiplayer? Units Sold: Number of units sold during the lifetime of the system for each title. Review Score: Reviewer score for each title for the system. Retail Price: Most titles back then were worth $60 so here I set each price of for each title to be $60. Estimated Sales: Calculated by multiplying the Retail Price by the number of Units Sold. Japan Release?: Was the game released in Japan or not? European Release?: Was the game released in Europe or not? North America Release?: Was the game released in North America or not? ESRB Rating: What is the rating for the title.

Digital Habits and Employment Status Survey

American Digital Usage and Employment Trends

By Joshua Shepherd [source]

About this dataset

This comprehensive dataset provides a rich and multi-faceted exploration into the intriguing world of digital habits, employment status, and demographics of Americans. Inspired by evolving modern lifestyle trends, this dataset meticulously draws information from varied topics such as gaming habits, job search techniques and broadband usage.

The first part of the dataset delves into the realm of video games and gaming culture. It explores various aspects related to individual's preferences towards different types of games across diverse platforms. It uncovers insights into how much time users spend on these games, their favoured genres and platforms (such as consoles or PC), along with their perspectives on important issues concerning violence in video games.

Next up is an insightful dataset that revolves around job seeking trends through digital channels. In a fast-paced business world where online resources have started playing an integral role in career progression and job hunt processes, this data provides valuable insights about Americans' reliance on internet services for finding potential jobs.

Hard-hitting questions revolving around workforce automation form yet another component of this extensive database. This section throws light upon the use of computers, robots or artificial intelligence to carry out tasks traditionally performed by human workers.

Probing further into modern relationship dynamics comes queries pertaining to online dating landscape. This segment explores Americans' attitudes towards online dating platforms - their usual go-to applications/web portals for seeking new relationships or love interests.

Lastly but importantly is an exhaustive set containing facts and figures regarding home broadband usage among Americans across all age groups & genders including their access to crucial cable TV services & smartphone possession rates & dependency levels over them in daily life activities ranging from shopping to banking & even learning new skills!

Collectively offering a well-rounded snapshot at contemporary American societies –this explorative data aims at providing stepping stones for researchers trying to understand these realms thereby serving larger cause making our society better

How to use the dataset

This dataset provides a rich collection of information about the digital habits, employment status, and secondary demographic data of respondents from the June-July 2015 Gaming, Job Search, and Broadband Usage Among Americans survey. With multiple sections regarding diverse topics such as gaming, online job searches, internet usage patterns and more fundamental demographics details - this dataset can be used for various kinds of exploratory data analysis (EDA), machine learning models or creating informative visualizations.

Here is how you can get started with this dataset:

1. Exploring Digital Habits:

The questions about video games ask if a respondent ever plays video games on a computer or console. This can be used to identify key trends in digital habits among different demographic groups - for instance correlation between age or gender and propensity towards gaming.

2. Analysing Job Searches:

The job seeking portion has information regarding use of internet in search processes and its effectiveness according to respondents’ opinion. You could perform an analysis on how working status (or even age group) affects the way individuals employ technology during their job searches.

3. Studying Broadband Usage:

Data about broadband usage at home would give insights into internet adoption rates among various demographic groups.

4.Predictive Modelling:

Potential predictive modeling could include predicting someone's employment status based on their digital habits or vice versa.

5.Cross-Referencing Data Points:

Using two or more datapoints can yield some interesting results as well - like finding out if gamers are more likely than non-gamers to frequently change jobs or seeing if there is any correlation with high speed broadband usage and employment type etc.

Before conducting any analysis do keep in mind that it would be beneficial to conduct some basic cleaning tasks such as checking for missing values, removing duplicates etc., suitable encoding discrete variables including education level into numerical ones based upon intuition behind categories ordinality could also provide better model performance.

This is just scratching the surface of p...

Playstation 4 Games

The PlayStation 4 (PS4) is a home video game console developed by Sony Computer Entertainment. Announced as the successor to the PlayStation 3 in February 2013, it was launched on November 15, 2013, in North America, November 29, 2013, in Europe, South America a and Australia, and on February 22, 2014, in Japan.

Acknowledments

The dataset is scraped from TrueTrophies.com which is a website that maintains players' winnings and achievements of PlayStation games.

Interesting Tasks - Analysis / Modelling Ideas

1. Which year were the most games released?
2. What are some of the shortest and longest games?
3. Who are the popular publishers and developers?
4. Is there any relation between game time and game size?