'''
pip install pandas,beautifulsoup4,finance-datareader,matplotlib -y
'''
import pandas as pd
import matplotlib.pyplot as plt
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
if __name__ == '__main__':
before_one_week = (datetime.now() - relativedelta(years = 3)).strftime('%Y-%m-%d')
df_exchange_rate = fdr.DataReader(symbol = 'USD/KRW', start = before_one_week)[['Close']]
df_kospi = fdr.DataReader(symbol = 'KS11', start = before_one_week)[['Close']]
df_samsung_elec = fdr.DataReader(symbol = get_stock_code('삼성전자'), start = before_one_week)[['Close']]
df_samsung_pre_elec = fdr.DataReader(symbol = get_stock_code('삼성전자우'), start = before_one_week)[['Close']]
df_sk_hynix = fdr.DataReader(symbol = get_stock_code('SK하이닉스'), start = before_one_week)[['Close']]
df_db_hitek = fdr.DataReader(symbol = get_stock_code('DB하이텍'), start = before_one_week)[['Close']]
df_hanmi = fdr.DataReader(symbol = get_stock_code('한미반도체'), start = before_one_week)[['Close']]
moving_average_list = list(range(1, 121))
result_dict = {}
for day in moving_average_list:
result_dict[f'{day}'] = [
int(df_exchange_rate.tail(day).sum() / day),
int(df_kospi.tail(day).sum() / day),
int(df_samsung_elec.tail(day).sum() / day),
int(df_samsung_pre_elec.tail(day).sum() / day),
int(df_sk_hynix.tail(day).sum() / day),
int(df_db_hitek.tail(day).sum() / day),
int(df_hanmi.tail(day).sum() / day)]
df_result = pd.DataFrame(result_dict).T
df_result.columns = ['USD/KRW', 'KOSPI', 'SS_ELEC', 'SS_ELEC_PRE', 'SK_HINIX', 'DB_HITEK', 'HANMI']
for column_name in df_result.columns:
df_result[f'{column_name}_per'] = round(df_result[column_name] / df_result[column_name].iloc[0], 3) * 100
df_result.reset_index(inplace = True)
df_result = df_result.astype({'index': 'int64'})
df_result = df_result.sort_values(by = 'index', ascending = False)
plt.plot(df_result['index'].to_list()[::-1], df_result['USD/KRW_per'].to_list(), label = 'USD/KRW')
plt.plot(df_result['index'].to_list()[::-1], df_result['KOSPI_per'].to_list(), label = 'KOSPI')
plt.plot(df_result['index'].to_list()[::-1], df_result['SS_ELEC_per'].to_list(), label = 'SS_ELEC')
plt.plot(df_result['index'].to_list()[::-1], df_result['SS_ELEC_PRE_per'].to_list(), label = 'SS_ELEC_PRE')
plt.plot(df_result['index'].to_list()[::-1], df_result['SK_HINIX_per'].to_list(), label = 'SK_HINIX')
plt.legend()
plt.show()
