[Python] 전기기기 관련 종목 종가 그래프 그리는 방법

'''
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_lg_energy        = fdr.DataReader(symbol = get_stock_code('LG에너지솔루션'), start = before_standard)[['Close']]
    df_samsung_sdi      = fdr.DataReader(symbol = get_stock_code('삼성SDI'), start = before_standard)[['Close']]
    df_echoprobm        = fdr.DataReader(symbol = get_stock_code('에코프로비엠'), start = before_standard)[['Close']]
    df_lnf              = fdr.DataReader(symbol = get_stock_code('엘앤에프'), start = before_standard)[['Close']]
    df_ski_tech         = fdr.DataReader(symbol = get_stock_code('SK아이이테크놀로지'), start = before_standard)[['Close']]

    df = pd.concat([df_exchange_rate, df_kospi, df_lg_energy, df_samsung_sdi, df_echoprobm, df_lnf, df_ski_tech], axis = 1, join = 'inner')
    df.columns = ['USD/KRW', 'KOSPI', 'LG_ENSOL', 'SS_SDI', 'ECHOPROBM', 'LNF', 'SKI_TECH']
    df.reset_index(inplace = True)

    df_copy = df.copy()

    df_2_year = df_copy[df_copy['Date'] > str(datetime.now() - relativedelta(years = 2))]
    df_1_year = df_copy[df_copy['Date'] > str(datetime.now() - relativedelta(years = 1))]
    df_9_month = df_copy[df_copy['Date'] > str(datetime.now() - relativedelta(months = 9))]
    df_6_month = df_copy[df_copy['Date'] > str(datetime.now() - relativedelta(months = 6))]
    df_3_month = df_copy[df_copy['Date'] > str(datetime.now() - relativedelta(months = 3))]
    df_1_month = df_copy[df_copy['Date'] > str(datetime.now() - relativedelta(months = 1))]

    stock_list = ['USD/KRW', 'KOSPI', 'LG_ENSOL', 'SS_SDI', 'ECHOPROBM', 'LNF', 'SKI_TECH']

    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.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.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.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.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.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.grid(True)
    plt.legend(fontsize = 6)

    plt.show()