Some cleaning
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# Cleaning of datasets
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# Somewhat main in the beninging
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import pandas as pd
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import pandas as pd
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import numpy as np
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# Loading Datasets
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game_sales2019_dat = pd.read_csv('datasets/videogames/vgsales-12-4-2019-short.csv')
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games_dat = pd.read_csv('datasets/videogames/Games.xls')
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# Printing information regarding datasets
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game_sales2019_dat.info()
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games_dat.info()
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# Printing First n values (index start: 0)
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print(game_sales2019_dat.head(10))
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print(games_dat.head(10))
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# Coercing the non-numeric values will result in NaN
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# thus allowing easier removal through `.notnull()`
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games_dat['Score'] = pd.to_numeric(games_dat['Score'], errors = 'coerce')
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games_dat = games_dat[games_dat['Score'].notnull()]
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games_dat.info()
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print(games_dat.head())
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