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Programming Language/Python
# Quick Start # input : 사용자ID, 아이템ID # Output : 평점 import pandas as pd from surprise import Dataset from surprise import Reader from surprise import KNNBasic from surprise.model_selection import train_test_split data = Dataset.load_builtin('ml-100k') df = pd.DataFrame(data.__dict__['raw_ratings'], columns = ['user_id', 'item_id', 'rating', 'timestamp']) df.drop(['timestamp'], axis = 1, inplace =..
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Programming Language/Python
import pandas as pd from surprise import Dataset from surprise import Reader from surprise import SVD from surprise import accuracy from surprise.model_selection import train_test_split data = Dataset.load_builtin('ml-100k') df = pd.DataFrame(data.__dict__['raw_ratings'], columns = ['user_id', 'item_id', 'rating', 'timestamp']) df.drop(['timestamp'], axis = 1, inplace = True) reader = Reader(rat..
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Programming Language/Python
import pandas as pd from surprise import Dataset from surprise import Reader from surprise import SVD from surprise import accuracy from surprise.model_selection import train_test_split data = Dataset.load_builtin('ml-100k') df = pd.DataFrame(data.__dict__['raw_ratings'], columns = ['user_id', 'item_id', 'rating', 'timestamp']) df.drop(['timestamp'], axis = 1, inplace = True) # df reader = Reade..
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Programming Language/Python
import pandas as pd from surprise import Dataset from surprise import Reader from surprise import SVD from surprise import accuracy from surprise.model_selection import train_test_split data = Dataset.load_builtin('ml-100k') df = pd.DataFrame(data.__dict__['raw_ratings'], columns = ['user_id', 'item_id', 'rating', 'timestamp']) df.drop(['timestamp'], axis = 1, inplace = True) reader = Reader(rat..
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Programming Language/Python
import pandas as pd from surprise import Dataset from surprise import Reader from surprise import SVD from surprise.model_selection import train_test_split data = Dataset.load_builtin('ml-100k') df = pd.DataFrame(data.__dict__['raw_ratings'], columns = ['user_id', 'item_id', 'rating', 'timestamp']) df.drop(['timestamp'], axis = 1, inplace = True) reader = Reader(rating_scale=(1, 5)) data = Datas..
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Programming Language/Python
- DB하이텍 - 5년 주가 ''' pip install pandas,beautifulsoup4,finance-datareader,matplotlib,cufflinks,chart_studio -y ''' import FinanceDataReader as fdr import cufflinks as cf import plotly.offline as plyo import pandas as pd # import matplotlib.pyplot as plt from datetime import datetime from dateutil.relativedelta import relativedelta def get_stock_code(name): df = fdr.StockListing('KRX') stock_code ..
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Programming Language/Python
- 삼성전자 ''' pip install pandas,beautifulsoup4,finance-datareader,matplotlib,cufflinks,chart_studio -y ''' import FinanceDataReader as fdr import cufflinks as cf import plotly.offline as plyo import pandas as pd # import matplotlib.pyplot as plt from datetime import datetime from dateutil.relativedelta import relativedelta def get_stock_code(name): df = fdr.StockListing('KRX') stock_code = df[df['..
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Programming Language/Python
''' pip install pandas,beautifulsoup4,finance-datareader,matplotlib,cufflinks,chart_studio -y ''' import FinanceDataReader as fdr import cufflinks as cf import plotly.offline as plyo import pandas as pd # import matplotlib.pyplot as plt from datetime import datetime from dateutil.relativedelta import relativedelta if __name__ == '__main__': before_standard = (datetime.now() - relativedelta(years..
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Programming Language/Python
''' pip install pandas,beautifulsoup4,finance-datareader,matplotlib,cufflinks,chart_studio -y ''' import FinanceDataReader as fdr import cufflinks as cf import plotly.offline as plyo import pandas as pd # import matplotlib.pyplot as plt from datetime import datetime from dateutil.relativedelta import relativedelta if __name__ == '__main__': before_standard = (datetime.now() - relativedelta(years..
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Programming Language/Python
''' pip install pandas,beautifulsoup4,finance-datareader,matplotlib,cufflinks,chart_studio -y ''' import FinanceDataReader as fdr import cufflinks as cf import plotly.offline as plyo import pandas as pd # import matplotlib.pyplot as plt from datetime import datetime from dateutil.relativedelta import relativedelta if __name__ == '__main__': before_standard = (datetime.now() - relativedelta(years..
