'''
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_standard = (datetime.now() - relativedelta(years = 2)).strftime('%Y-%m-%d')
df_exchange_rate = fdr.DataReader(symbol = 'USD/KRW', start = before_standard)[['Close']]
df_kospi = fdr.DataReader(symbol = 'KS11', start = before_standard)[['Close']]
df_kosdaq = fdr.DataReader(symbol = 'KQ11', start = before_standard)[['Close']]
df = pd.concat([df_exchange_rate, df_kospi, df_kosdaq], axis = 1, join = 'inner')
stock_list = ['USD/KRW', 'KOSPI', 'KOSDAQ']
df.columns = stock_list
df.reset_index(inplace = True)
df_2_year, df_1_year, df_9_month, df_6_month, df_3_month, df_1_month = df.copy(), df.copy(), df.copy(), df.copy(), df.copy(), df.copy()
df_1_year = df_1_year[df_1_year['Date'] > str(datetime.now() - relativedelta(years = 1))]
df_9_month = df_9_month[df_9_month['Date'] > str(datetime.now() - relativedelta(months = 9))]
df_6_month = df_6_month[df_6_month['Date'] > str(datetime.now() - relativedelta(months = 6))]
df_3_month = df_3_month[df_3_month['Date'] > str(datetime.now() - relativedelta(months = 3))]
df_1_month = df_1_month[df_1_month['Date'] > str(datetime.now() - relativedelta(months = 1))]
for stock in stock_list:
df_2_year[stock] = round((df_2_year[stock] - (df_2_year[stock].sum() / df_2_year['Date'].count())) / df_2_year[stock] * 100, 2)
df_1_year[stock] = round((df_1_year[stock] - (df_1_year[stock].sum() / df_1_year['Date'].count())) / df_1_year[stock] * 100, 2)
df_9_month[stock] = round((df_9_month[stock] - (df_9_month[stock].sum() / df_9_month['Date'].count())) / df_9_month[stock] * 100, 2)
df_6_month[stock] = round((df_6_month[stock] - (df_6_month[stock].sum() / df_6_month['Date'].count())) / df_6_month[stock] * 100, 2)
df_3_month[stock] = round((df_3_month[stock] - (df_3_month[stock].sum() / df_3_month['Date'].count())) / df_3_month[stock] * 100, 2)
df_1_month[stock] = round((df_1_month[stock] - (df_1_month[stock].sum() / df_1_month['Date'].count())) / df_1_month[stock] * 100, 2)
plt.figure(figsize=(20, 10))
plt.subplot(3,2,1)
for stock in stock_list:
plt.plot(df_2_year['Date'], df_2_year[stock].to_list(), label = stock, linewidth = '1')
plt.title('2 Years')
plt.grid(True)
plt.legend(fontsize = 6)
plt.subplot(3,2,2)
for stock in stock_list:
plt.plot(df_1_year['Date'], df_1_year[stock].to_list(), label = stock, linewidth = '1')
plt.title('1 Years')
plt.grid(True)
plt.legend(fontsize = 6)
plt.subplot(3,2,3)
for stock in stock_list:
plt.plot(df_9_month['Date'], df_9_month[stock].to_list(), label = stock, linewidth = '1')
plt.title('9 Months')
plt.grid(True)
plt.legend(fontsize = 6)
plt.subplot(3,2,4)
for stock in stock_list:
plt.plot(df_6_month['Date'], df_6_month[stock].to_list(), label = stock, linewidth = '1')
plt.title('6 Months')
plt.grid(True)
plt.legend(fontsize = 6)
plt.subplot(3,2,5)
for stock in stock_list:
plt.plot(df_3_month['Date'], df_3_month[stock].to_list(), label = stock, linewidth = '1')
plt.title('3 Months')
plt.grid(True)
plt.legend(fontsize = 6)
plt.subplot(3,2,6)
for stock in stock_list:
plt.plot(df_1_month['Date'], df_1_month[stock].to_list(), label = stock, linewidth = '1')
plt.title('1 Months')
plt.grid(True)
plt.legend(fontsize = 6)
plt.show()
