'''
pip install pandas,beautifulsoup4,finance-datareader -y
'''
import pandas as pd
import FinanceDataReader as fdr
from datetime import datetime
from dateutil.relativedelta import relativedelta
def get_stock_code(name):
'''이름을 입력하면 코드를 리턴'''
df = fdr.StockListing('KRX')
stock_code = df[df['Name'] == name]['Code'].to_string(index = False)
return stock_code
def get_kospi_dataframe():
'''코스피를 리턴'''
df = fdr.StockListing('KRX')
df = df[df['Market'] == 'KOSPI']
return df
if __name__ == '__main__':
before_one_week = (datetime.now() - relativedelta(years = 3)).strftime('%Y-%m-%d')
df_ks11 = fdr.DataReader(symbol = 'KS11', start = before_one_week)[['Close']]
df_samsung = fdr.DataReader(symbol = get_stock_code('삼성전자'), start = before_one_week)[['Close']]
moving_average_list = [1, 3, 5, 7, 10, 15, 20, 30, 40, 50, 60, 120, 200, 240, 360, 400, 480, 600, 720]
result_dict = {}
for day in moving_average_list:
result_dict[f'avg_{day}'] = [int(df_ks11.tail(day).sum() / day), int(df_samsung.tail(day).sum() / day)]
df_result = pd.DataFrame(result_dict).T
df_result.columns = ['kospi', 'samsung']
df_result['kospi_per'] = round(df_result['kospi'] / df_result['kospi'].iloc[0], 2)
df_result['samsung_per'] = round(df_result['samsung'] / df_result['samsung'].iloc[0], 2)
print(df_result)
