- This file consist of short and structured comments for jupyter notebook used in Social Science lab SoSe21:
- Topic: Preferences between NA and EU games in board games.
- BGG Forum data overview.ipynb
- notebook to analyse avaliable data set from BGG (https://boardgamegeek.com/thread/2287371/boardgamegeek-games-and-ratings-datasets)
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Scrape initial list of games to work with.ipynb
- notebook with code to scrape top games (name, id, url)
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Assestment of how many pages to scrape.ipynb
- notebook with code to understand how many pages we can scrape considering average time to scrapte 1 page (~13 seconds) and necessary number of rating needed to answer research question
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Scrape games categories.ipynb
- notebook with code to scrape list of categories of each game (i.e Fantasy, CardGame, Wargame, Medieval and so on)
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Scrape. Num of pages from games.ipynb
- notebook with code to scrape number of ranting pages of each game. Number of pages we need to randomly choose 20 pages on next steps
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Scrape game additional data (playing time, age, num of players).ipynb
- notebook with code to scrape playing time, age, num of players of 1000 games
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Main scraper. Scrape rating with random pages.ipynb
- notebook with code to scrape 1000 ratings info of each game
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Folders reading for scraped files and short analysis.ipynb
- notebook with code to form one dataset of all scraped ratings and short analysis of data
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Categories transformation.ipynb
- notebook with code to make game cateroies trasformation from list to binary columns
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Preliminar analysis of descriptive games attributes.ipynb
- notebook with code for preliminary analysis of descriptive games attributes (playing time, age, num of players)
- Descriptive stat.ipynb
- notebook with code to calculate Descriptive stat
- Answering reserach question (subquestions 1-2).ipynb
- notebook with code to answer subquestion 1 (Hypothesis test and efect size calculation), subquestion 2 (p-value and effect size calculation for top 20 catregories for 2 continents)
- Regression BGG (subquestions 3).ipynb
- this notebook is expansion of Bhanu.Vijayaraj's analysis notebook with code of RandomForestRegressor and LinearRegression to answer subquestions 3 (which features play main role in average rating prediction).
- Popularity_of_categories (research subquestion 4).ipynb
- notebook with code to answer research subquestion 4
- rating_chi_test.ipynb
- Are ratings and continents dependent on each other ? (research subquestion 5)