Asset Management Program (yfinance API, Google Colab)

実行結果

コード#コード#

#code
!pip install yfinance
from pandas_datareader import data as pdr
import yfinance as yf
import datetime
import matplotlib.pyplot as plt
from PIL import Image, ImageDraw, ImageFont
import os
from google.colab import drive
drive.mount('/content/drive')
os.system('cp /content/drive/MyDrive/Stock_Record/Stock_Own_Record.txt /content/drive/MyDrive/Stock_Record/Stock_Own_Record_backup.txt')
os.system('cp /content/drive/MyDrive/Stock_Record/Stock_Price_Record.txt /content/drive/MyDrive/Stock_Record/Stock_Price_Record_backup.txt')
now = datetime.datetime.now()
start_date = datetime.date(2021, 1, 1)
now_date = now.strftime('%Y-%m-%d')
f = open('/content/drive/MyDrive/Stock_Record/Money_Debt_Record.txt', 'r')
money = {}
housing = {}
debt = {}
global_deposit = {}
korea_deposit = {}
pension_deposit = {}
principal = {}
i = -1
while True:
    line = f.readline()
    if not line:
        break
    if line[0] == '#':
        i += 1
        continue
    if i == 0:
        money[line.split()[0]] = float(line.split()[1])
    if i == 1:
        housing[line.split()[0]] = float(line.split()[1])
    if i == 2:
        debt[line.split()[0]] = float(line.split()[1])
    if i == 3:
        global_deposit[line.split()[0]] = float(line.split()[1])
    if i == 4:
        korea_deposit[line.split()[0]] = float(line.split()[1])
    if i == 5:
        pension_deposit[line.split()[0]] = float(line.split()[1])
    if i == 6:
        principal[line.split()[0]] = float(line.split()[1])
f.close()
f = open('/content/drive/MyDrive/Stock_Record/Stock_Own_Record.txt', 'r')
ticker = []
stock_type = []
stock_own = []
i = -1
while True:
    line = f.readline()
    if not line:
        break
    if line[0] == '#':
        ticker.append(line.split('#')[1])
        stock_type.append(int(line.split('#')[2].split('\n')[0]))
        i += 1
        stock_own.append({})
        continue
    stock_own[i][line.split()[0]] = float(line.split()[1])
f.close()
f = open('/content/drive/MyDrive/Stock_Record/Stock_Price_Record.txt', 'r')
stock_price = []
for i in range(len(ticker)):
    stock_price.append({})
i = -1
while True:
    line = f.readline()
    if not line:
        break
    if line[0] == '#':
        i += 1
        continue
    stock_price[i][line.split()[0]] = float(line.split()[1])    
f.close()
yf.pdr_override()
new_stock_price = []
for i in ticker:
    new_stock_price.append(pdr.get_data_yahoo(i, start=start_date, end=now_date))
for i in range(len(ticker)):
    for j in new_stock_price[i].index:
        stock_price[i][j.strftime('%Y-%m-%d')] = float('{:.2f}'.format(new_stock_price[i].at[j,'Close']))
stock_price[16]['2020-12-31'] = 25.11
f = open('/content/drive/MyDrive/Stock_Record/Stock_Price_Record.txt', 'w')
for i in range(len(ticker)):
    f.write('#'+ticker[i]+'\n')
    for j in stock_price[i].keys():
        f.write(str(j) + ' ')
        f.write(str('{:.2f}'.format(stock_price[i][j])))
        f.write('\n')
f.close()    
    
dollar_price = yf.download(['USDKRW=X'],start=start_date, end=now_date)
dollar_price_record = {}
for i in dollar_price.index:
    dollar_price_record[i.strftime('%Y-%m-%d')] = float('{:.2f}'.format(dollar_price.at[i,'Close']))
print()
dollarperwon = dollar_price.at[dollar_price.index[-1], 'Close']
amount = []
amount_by_type = [0, 0, 0, 0]
total_amount = 0
for i in range(len(ticker)):
    temp = stock_price[i][list(stock_price[i].keys())[-1]] * stock_own[i][list(stock_own[i].keys())[-1]]
    if stock_type[i] == 1 or stock_type[i] == 2:
        temp /= dollarperwon
    amount.append(temp)
    amount_by_type[stock_type[i]] += temp
    total_amount += temp
amount_by_type[0] += global_deposit[list(global_deposit.keys())[-1]]
amount_by_type[1] += korea_deposit[list(korea_deposit.keys())[-1]]/dollarperwon
amount_by_type[2] += pension_deposit[list(pension_deposit.keys())[-1]]/dollarperwon
total_amount_plus_deposit = total_amount + global_deposit[list(global_deposit.keys())[-1]] + korea_deposit[list(korea_deposit.keys())[-1]]/dollarperwon + pension_deposit[list(pension_deposit.keys())[-1]]/dollarperwon
sorted_amount_index = list(reversed(sorted(range(len(amount)), key=lambda k: amount[k])))
print('**INVESTMENT STATUS**')
for i in sorted_amount_index:
    if stock_own[i][list(stock_own[i].keys())[-1]] == 0:
        break
    if stock_type[i] == 0:
        print('{}{:10.1f}%{:10.1f}{:15.0f}  {:10.2f}'.format('{0: <10}'.format(ticker[i]), amount[i]/total_amount*100, amount[i], stock_own[i][list(stock_own[i].keys())[-1]], stock_price[i][list(stock_price[i].keys())[-1]]))
    if stock_type[i] == 1 or stock_type == 2:
        print('{}{:10.1f}%{:10.1f}{:15.0f}  {:10.0f}'.format('{0: <10}'.format(ticker[i]), amount[i]/total_amount*100, amount[i], stock_own[i][list(stock_own[i].keys())[-1]], stock_price[i][list(stock_price[i].keys())[-1]]))
    if stock_type[i] == 3:
        print('{}{:10.1f}%{:10.1f}{:15.8f}  {:10.2f}'.format('{0: <10}'.format(ticker[i]), amount[i]/total_amount*100, amount[i], stock_own[i][list(stock_own[i].keys())[-1]], stock_price[i][list(stock_price[i].keys())[-1]]))
print()
print('**SUMMARY**')
print('GLOBAL STOCK     : {:.1f}%\t${:.1f}\t￦{}'.format(amount_by_type[0]/total_amount_plus_deposit*100, amount_by_type[0], '{:,}'.format(int(amount_by_type[0]*dollarperwon))))
print('KOREA  STOCK     : {:.1f}%  \t${:.1f}   \t￦{}'.format(amount_by_type[1]/total_amount_plus_deposit*100, amount_by_type[1], '{:,}'.format(int(amount_by_type[1]*dollarperwon))))
print('PENSION S. FUND  : {:.1f}%  \t${:.1f}   \t￦{}'.format(amount_by_type[2]/total_amount_plus_deposit*100, amount_by_type[2], '{:,}'.format(int(amount_by_type[2]*dollarperwon))))
print('CRYPTOCURRENCY   : {:.1f}%  \t${:.1f}   \t￦{}'.format(amount_by_type[3]/total_amount_plus_deposit*100, amount_by_type[3], '{:,}'.format(int(amount_by_type[3]*dollarperwon))))
print('TOTAL ASSET      : 100%   \t${:.1f}\t￦{}'.format(total_amount_plus_deposit, '{:,}'.format(int(total_amount_plus_deposit*dollarperwon))))
cur = start_date
now = datetime.date(now.year, now.month, now.day)
cur_stock_price = []
cur_stock_own = []
for i in range(len(ticker)):
    cur_stock_price.append(stock_price[i][list(stock_price[i].keys())[0]])
    cur_stock_own.append(stock_own[i][list(stock_own[i].keys())[0]])
cur_money = money[list(money.keys())[0]]
cur_housing = housing[list(housing.keys())[0]]
cur_debt = debt[list(debt.keys())[0]]
cur_global_deposit = global_deposit[list(global_deposit.keys())[0]]
cur_korea_deposit = korea_deposit[list(korea_deposit.keys())[0]]
cur_pension_deposit = pension_deposit[list(pension_deposit.keys())[0]]
cur_dollarperwon = dollar_price_record[list(dollar_price_record.keys())[0]]
cur_principal = principal[list(principal.keys())[0]]
asset_axis = []
invest_axis = []
earning_axis = []
global_axis = []
korea_axis = []
pension_axis = []
btc_axis = []
date_axis = []
day_count = 0
for_xaxis = []
datetime_axis = []
earning_rate_axis = []
principal_axis = []
while cur <= now:
    for i in range(len(ticker)):
        if cur.strftime('%Y-%m-%d') in list(stock_price[i].keys()):
            cur_stock_price[i] = stock_price[i][cur.strftime('%Y-%m-%d')]
        if cur.strftime('%Y-%m-%d') in list(stock_own[i].keys()):
            cur_stock_own[i] = stock_own[i][cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(money.keys()):
        cur_money = money[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(housing.keys()):
        cur_housing = housing[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(debt.keys()):
        cur_debt = debt[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(global_deposit.keys()):
        cur_global_deposit = global_deposit[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(korea_deposit.keys()):
        cur_korea_deposit = korea_deposit[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(pension_deposit.keys()):
        cur_pension_deposit = pension_deposit[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(dollar_price_record.keys()):
        cur_dollarperwon = dollar_price_record[cur.strftime('%Y-%m-%d')]
    if cur.strftime('%Y-%m-%d') in list(principal.keys()):
        cur_principal = principal[cur.strftime('%Y-%m-%d')]
    temp = 0
    temp_invest = 0
    temp_asset = 0
    temp_global = 0
    temp_korea = 0
    temp_pension = 0
    temp_btc = 0
    temp_earning = 0
    for i in range(len(ticker)):
        if stock_type[i] == 0:
            temp_invest += cur_stock_price[i] * cur_stock_own[i] * cur_dollarperwon
            temp_global += cur_stock_price[i] * cur_stock_own[i] * cur_dollarperwon
        elif stock_type[i] == 1:
            temp_invest += cur_stock_price[i] * cur_stock_own[i]
            temp_korea += cur_stock_price[i] * cur_stock_own[i]
        elif stock_type[i] == 2:
            temp_invest += cur_stock_price[i] * cur_stock_own[i]
            temp_pension += cur_stock_price[i] * cur_stock_own[i]
        elif stock_type[i] == 3:
            temp_invest += cur_stock_price[i] * cur_stock_own[i] * cur_dollarperwon
            temp_btc += cur_stock_price[i] * cur_stock_own[i] * cur_dollarperwon
    temp_invest += cur_global_deposit*cur_dollarperwon + cur_korea_deposit + cur_pension_deposit
    temp_asset = temp_invest + cur_money + cur_housing - cur_debt
    temp_earning = temp_invest - cur_principal
    earning_axis.append(temp_earning)
    asset_axis.append(temp_asset)
    invest_axis.append(temp_invest)
    global_axis.append(temp_global)
    korea_axis.append(temp_korea)
    pension_axis.append(temp_pension)
    btc_axis.append(temp_btc)
    date_axis.append(day_count)
    datetime_axis.append(cur)
    principal_axis.append(cur_principal)
    earning_rate_axis.append(temp_earning/cur_principal*100)
    if day_count%28 == 0:
        for_xaxis.append(day_count)
    day_count += 1
    cur += datetime.timedelta(days=1)
    
cur = start_date
label_for_xaxis = []
while cur <= now:
    label_for_xaxis.append(cur.strftime('%Y-%m-%d'))
    cur += datetime.timedelta(weeks=4)
plt.figure(figsize=(20,10))
plt.yticks([0, 10000000, 20000000, 30000000, 40000000, 50000000, 60000000, 70000000, 80000000, 90000000, 100000000, 110000000, 120000000], labels=['0', '10,000,000', '20,000,000', '30,000,000', '40,000,000', '50,000,000', '60,000,000', '70,000,000', '80,000,000', '90,000,000', '100,000,000', '110,000,000', '120,000,000'])
plt.xticks(for_xaxis, labels=label_for_xaxis, rotation=60)
plt.plot(date_axis, asset_axis, label='NET ASSET', color='black')
plt.plot(date_axis , earning_axis, label='EARNING', color='red')
plt.plot(date_axis, invest_axis, label='ASSET', linestyle = 'dashed')
plt.plot(date_axis, global_axis, label='GLOBAL', linestyle = 'dashed')
plt.plot(date_axis, korea_axis, label='KOREA', linestyle = 'dashed')
plt.plot(date_axis, pension_axis, label='PENSION', linestyle = 'dashed')
plt.plot(date_axis, btc_axis, label='BTC', linestyle = 'dashed')
max_asset = max(asset_axis)
min_asset = min(asset_axis)
max_asset_index = asset_axis.index(max_asset)
min_asset_index = asset_axis.index(min_asset)
max_earning = max(earning_axis)
min_earning = min(earning_axis)
max_earning_index = earning_axis.index(max_earning)
min_earning_index = earning_axis.index(min_earning)
plt.annotate('{}\n{} {:,}'.format(datetime_axis[max_asset_index].strftime('%Y-%m-%d'), u"\u20A9", int(asset_axis[max_asset_index])), xy=(date_axis[max_asset_index], asset_axis[max_asset_index]), xytext=(-200,70), textcoords='offset points', fontsize=20, ha='center', arrowprops=dict(color='black',arrowstyle="-|>"))
plt.annotate('{}\n{} {:,}'.format(datetime_axis[min_asset_index].strftime('%Y-%m-%d'), u"\u20A9", int(asset_axis[min_asset_index])), xy=(date_axis[min_asset_index], asset_axis[min_asset_index]), xytext=(100,120), textcoords='offset points', fontsize=20, ha='center', arrowprops=dict(color='black',arrowstyle="-|>"))
plt.annotate('{}\n{} {:,}'.format(datetime_axis[-1].strftime('%Y-%m-%d'), u"\u20A9", int(asset_axis[-1])), xy=(date_axis[-1], asset_axis[-1]), xytext=(0,70), textcoords='offset points', fontsize=20, ha='center', arrowprops=dict(color='black',arrowstyle="-|>"))
plt.annotate('{}\n{} {:,}'.format(datetime_axis[max_earning_index].strftime('%Y-%m-%d'), u"\u20A9", int(earning_axis[max_earning_index])), xy=(date_axis[max_earning_index], earning_axis[max_earning_index]), xytext=(0,70), textcoords='offset points', fontsize=20, ha='center', arrowprops=dict(color='red',arrowstyle="-|>"))
plt.annotate('{}\n-{} {:,}'.format(datetime_axis[min_earning_index].strftime('%Y-%m-%d'), u"\u20A9", abs(int(earning_axis[min_earning_index]))), xy=(date_axis[min_earning_index], earning_axis[min_earning_index]), xytext=(0,70), textcoords='offset points', fontsize=20, ha='center', arrowprops=dict(color='red',arrowstyle="-|>"))
plt.annotate('{}\n{} {:,}'.format(datetime_axis[-1].strftime('%Y-%m-%d'), u"\u20A9", int(earning_axis[-1])), xy=(date_axis[-1], earning_axis[-1]), xytext=(0,70), textcoords='offset points', fontsize=20, ha='center', arrowprops=dict(color='red',arrowstyle="-|>"))
print()
print('NET ASSET       : ￦{:,}'.format(int(asset_axis[-1])))
print('MAX NET ASSET   : ￦{:,}'.format(int(max_asset)))
print()
print('EARNING         : ￦{:,}'.format(int(earning_axis[-1])))
print('MAX EARNING     : ￦{:,}'.format(int(max_earning)))
print()
print('RATE OF RETURN  : {:.1f}%'.format(earning_rate_axis[-1]))
plt.legend()
plt.grid(True, axis='y')
plt.savefig('/content/drive/MyDrive/Stock_Record/Asset.png')
old_im = Image.open('/content/drive/MyDrive/Stock_Record/Asset.png')
old_size = old_im.size
new_size = (1440, 1080)
new_im = Image.new("RGB", new_size) ## luckily, this is already black!
new_im.paste(old_im, ((int)((new_size[0]-old_size[0])/2), (int)((new_size[1]-old_size[1])/2)))
new_im.show()
new_im.save('/content/drive/MyDrive/Stock_Record/Asset.png')
bg_color = 'rgb(105,105,105)' 
font = ImageFont.truetype('/content/drive/MyDrive/Stock_Record/Monoid-Retina.ttf', 15) 
font_color = 'rgb(255,255,255)' 
w = 932
h = 699
image = Image.new('RGB', (w,h), color=bg_color) 
draw = ImageDraw.Draw(image) 
x_text = 165
y_text = 50 
lines = []
lines.append('**INVESTMENT STATUS**')
for i in sorted_amount_index:
    if stock_own[i][list(stock_own[i].keys())[-1]] == 0:
        break
    if stock_type[i] == 0:
        lines.append('{}{:10.1f}%{:10.1f}{:15.0f}  {:10.2f}'.format('{0: <10}'.format(ticker[i]), amount[i]/total_amount*100, amount[i], stock_own[i][list(stock_own[i].keys())[-1]], stock_price[i][list(stock_price[i].keys())[-1]]))
    if stock_type[i] == 1 or stock_type == 2:
        lines.append('{}{:10.1f}%{:10.1f}{:15.0f}  {:10.0f}'.format('{0: <10}'.format(ticker[i]), amount[i]/total_amount*100, amount[i], stock_own[i][list(stock_own[i].keys())[-1]], stock_price[i][list(stock_price[i].keys())[-1]]))
    if stock_type[i] == 3:
        lines.append('{}{:10.1f}%{:10.1f}{:15.8f}  {:10.2f}'.format('{0: <10}'.format(ticker[i]), amount[i]/total_amount*100, amount[i], stock_own[i][list(stock_own[i].keys())[-1]], stock_price[i][list(stock_price[i].keys())[-1]]))
for line in lines:
    width, height = font.getsize(line)
    draw.text((x_text,y_text),line,font=font,fill=font_color)
    y_text += height+10
image.save('/content/drive/MyDrive/Stock_Record/Investment_Status.png')
image
w = 600
h = 450
image1 = Image.new('RGB', (w,h), color=bg_color) 
draw1 = ImageDraw.Draw(image1)
x_text = 50
y_text = 50 
lines = []
lines.append('**SUMMARY**')
lines.append('GLOBAL STOCK     : {:.1f}%    ${:.1f}     {}'.format(amount_by_type[0]/total_amount_plus_deposit*100, amount_by_type[0], '{:,}'.format(int(amount_by_type[0]*dollarperwon))))
lines.append('KOREA  STOCK     : {:.1f}%    ${:.1f}     {}'.format(amount_by_type[1]/total_amount_plus_deposit*100, amount_by_type[1], '{:,}'.format(int(amount_by_type[1]*dollarperwon))))
lines.append('PENSION S. FUND  : {:.1f}%     ${:.1f}       {}'.format(amount_by_type[2]/total_amount_plus_deposit*100, amount_by_type[2], '{:,}'.format(int(amount_by_type[2]*dollarperwon))))
lines.append('CRYPTOCURRENCY   : {:.1f}%     ${:.1f}       {}'.format(amount_by_type[3]/total_amount_plus_deposit*100, amount_by_type[3], '{:,}'.format(int(amount_by_type[3]*dollarperwon))))
lines.append('TOTAL ASSET      : 100%     ${:.1f}    {}'.format(total_amount_plus_deposit, '{:,}'.format(int(total_amount_plus_deposit*dollarperwon))))
lines.append('')
lines.append('NET ASSET       : {:,}'.format(int(asset_axis[-1])))
lines.append('MAX NET ASSET   : {:,}'.format(int(max_asset)))
lines.append('')
lines.append('EARNING         : {:,}'.format(int(earning_axis[-1])))
lines.append('MAX EARNING     : {:,}'.format(int(max_earning)))
lines.append('')
lines.append('RATE OF RETURN  : {:.1f}%'.format(earning_rate_axis[-1]))
for line in lines:
    width, height = font.getsize(line)
    draw1.text((x_text,y_text),line,font=font,fill=font_color)
    y_text += height+10
image1.save('/content/drive/MyDrive/Stock_Record/Summary.png')
image1