What does this contain?

This is a dataset contains whatever information that was scrapable, regarding some 80000 games from the Steam official website. Most of the columns contains valuable information that could give a better insight of the game, but cleaning them is required for most of them. make sure to refer the column descriptors for more information. I have not included all reviews and reviews related time series data for the games in this dataset because, it constantly keeps changing and it can be easily fetched using the steam api.

Checkout this Dashboard Webapp made by Raphael Guyot using this dataset

Review related time series can be fetched from this Steam API Link: https://store.steampowered.com/appreviewhistogram/945360 User reviews data can be fetched from this Steam API Link: https://store.steampowered.com/appreviews/945360?json=1

Here, replace 945360 with the Game ID (available inside the url of the game) of the game for which you are going to fetch the data.

Clean Data in JSON Format has been uploaded :smile: Both JSON and CSV files contains same data, but in JSON one it has been cleaned, so while downloading, choose any one of the filetype Refer Metadata for scripts used for Scraping

JSON Sample data

{'img_url': 'https://steamcdn-a.akamaihd.net/steam/apps/730/header.jpg?t=1592263625',  'date': 'Aug 21, 2012',  'developer': 'Valve, Hidden Path Entertainment',  'publisher': 'Valve',  'full_desc': {'sort': 'game',   'desc': 'About This Game Counter-Strike: Global Offensive (CS: GO) expands upon the team-based action gameplay that it pioneered when it was launched 19 years ago.CS: GO features new maps, characters, weapons, and game modes, and delivers updated versions of the classic CS content (de_dust2, etc.)."Counter-Strike took the gaming industry by surprise when the unlikely MOD became the most played online PC action game in the world almost immediately after its release in August 1999," said Doug Lombardi at Valve. "For the past 12 years, it has continued to be one of the most-played games in the world, headline competitive gaming tournaments and selling over 25 million units worldwide across the franchise. CS: GO promises to expand on CS\' award-winning gameplay and deliver it to gamers on the PC as well as the next gen consoles and the Mac."'},  'requirements': {'minimum': {'windows': {'processor': ' Intel® Core™ 2 Duo E6600 or AMD Phenom™ X3 8750 processor or better',     'memory': ' 2 GB RAM',     'graphics': ' Video card must be 256 MB or more and should be a ',     'os': ' Windows® 7/Vista/XP'},    'linux': {'processor': ' 64-bit Dual core from Intel or AMD at 2.8 GHz',     'memory': ' 4 GB RAM',     'graphics': ' nVidia GeForce 8600/9600GT, ATI/AMD Radeon HD2600/3600 (Graphic Drivers: nVidia 310, AMD 12.11), OpenGL 2.1',     'os': ' Ubuntu 12.04'}},   'recommended': {}},  'popu_tags': ['Shooter',   'Multiplayer',   'Competitive',   'Action',   'Team-',   'Basede',   'Sports',   'Tactical',   'First-',   'Person',   'Online',   'Strategy',   'Military',   'Difficult',   'Trading',   'Realistic',   'Fast-',   'Paced',   'Moddable+'],  'price': 'free',  'url_info': {'url': 'https://store.steampowered.com/app/730/CounterStrike_Global_Offensive/?snr=1_7_7_230_150_1',   'id': '730',   'type': 'app',   'url_name': 'CounterStrike Global Offensive'},  'name': 'Counter-Strike: Global Offensive',  'categories': ['Steam Achievements Full',   'controller supportSteam',   'Trading Cards Steam',   'Workshop In-App Purchases Valve',   'Anti-Cheat enabledStats Remote',   'Play on',   'Phone Remote Play',   'on Tablet Remote',   'Play on']} 

What can be done with this?

I have divided the dataset into 2 parts, one with information based on numbers and other based on text. One can use the number based dataset to practice data cleaning procedures and regrexes, after cleaning, procedures like EDA, feature selection, clustering and many more things can be done. Text based dataset can be used in NLP projects.

Acknowledgements

I would like to thank Hariharan.S.V and Shankar Narayanan for helping me with the data scraping and data cleaning.