Programming Language/Python
2023.02.27
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..
Programming Language/Python
2023.02.27
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..
Programming Language/Python
2023.02.27
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..
Programming Language/Python
2023.02.27
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..
Programming Language/Python
2023.02.20
- 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 ..
Programming Language/Python
2023.02.20
- 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['..
Programming Language/Python
2023.02.20
''' 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..
Programming Language/Python
2023.02.20
''' 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..
Programming Language/Python
2023.02.20
''' 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..
Programming Language/Python
2023.02.19
Python - 프로그래밍 언어 - 인터프리터 언어 - 인터프리터로 동작하는 스크립트 언어 - 인터프리터 언어는 한줄한줄 읽어 그때마다 기계어로 번역하여 실행 - 단점은 속도가 느림 - 파이썬은 C로 구현됨 CPython - C를 이용하여 Python을 구현 - CPython은 Python을 한줄한줄 읽어서 CPU가 이해할 수 있도록 번역함 - CPython은 파이썬의 인터프리터 역할 - CPython 외에 파이썬 인터프리터 역할을 하는 것은 많음 Cython - Python 구현 이후 등장 - 인터프리터 언어는 컴파일 언어보다 성능이 떨어짐, 그래서 Cython 등장 - C언어에 Python 문법을 사용할 수 있게 만듦. C++과 비슷함. - Cython은 컴파일 언어 - 성능이 좋은 라이브러리는 Cy..
