{"id":30889,"date":"2024-10-28T06:04:24","date_gmt":"2024-10-28T06:04:24","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=30889"},"modified":"2024-11-26T06:47:06","modified_gmt":"2024-11-26T06:47:06","slug":"%ed%8c%8c%ec%9d%b4%ec%8d%ac-%ec%9e%90%eb%8f%99%eb%a7%a4%eb%a7%a4-%ea%b0%9c%eb%b0%9c-%eb%9d%bc%eb%b2%a8-%eb%b0%8f-%eb%b2%94%eb%a1%80-%ed%91%9c%ec%8b%9c%ed%95%98%ea%b8%b0","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/30889\/","title":{"rendered":"\ud30c\uc774\uc36c \uc790\ub3d9\ub9e4\ub9e4 \uac1c\ubc1c, \ub77c\ubca8 \ubc0f \ubc94\ub840 \ud45c\uc2dc\ud558\uae30"},"content":{"rendered":"

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\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \ub2e4\uc591\ud55c \uae08\uc735 \uc2dc\uc7a5\uc5d0\uc11c \uac70\ub798\ub97c \uc790\ub3d9\uc73c\ub85c \uc218\ud589\ud558\ub294 \uc2dc\uc2a4\ud15c\uc73c\ub85c, \ub9ce\uc740 \ud22c\uc790\uc790 \ubc0f \ud2b8\ub808\uc774\ub354\ub4e4\uc774 \uc774\uc6a9\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uac00\uc774\ub4dc\uc5d0\uc11c\ub294 \ud30c\uc774\uc36c\uc744 \ud65c\uc6a9\ud558\uc5ec \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uac1c\ubc1c\ud558\ub294 \ubc29\ubc95\uacfc \ud568\uaed8, \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud560 \ub54c \uc720\uc6a9\ud55c \ub77c\ubca8 \ubc0f \ubc94\ub840\ub97c \ud45c\uc2dc\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc740 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f \uc2dc\uac01\ud654\uc758 \uae30\ubcf8\uc744 \uc774\ud574\ud558\ub294\ub370 \ud070 \ub3c4\uc6c0\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4.<\/p>\n

1. \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc758 \uac1c\uc694<\/h2>\n

\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc740 \uc785\ub825\ub41c \uaddc\uce59\uc774\ub098 \uc54c\uace0\ub9ac\uc998\uc5d0 \ub530\ub77c \ub9e4\ub9e4\ub97c \uc790\ub3d9\uc73c\ub85c \uc218\ud589\ud558\uba70, \uae30\uc220\uc801 \ubd84\uc11d, \ucc28\ud2b8 \ud328\ud134, \uc2ec\ub9ac\uc801 \uc694\uc778 \ub4f1\uc744 \uae30\ucd08\ub85c \ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 \ud30c\uc774\uc36c\uc740 pandas, NumPy, Matplotlib, \uadf8\ub9ac\uace0 \uc5ec\ub7ec API \ub77c\uc774\ube0c\ub7ec\ub9ac \ub4f1\uc744 \ud1b5\ud574 \uac15\ub825\ud55c \ub370\uc774\ud130 \ucc98\ub9ac \ubc0f \uc2dc\uac01\ud654 \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n

2. \ub370\uc774\ud130 \uc218\uc9d1<\/h2>\n

\uba3c\uc800, \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uac1c\ubc1c\ud558\uae30 \uc704\ud574\uc11c\ub294 \ub370\uc774\ud130 \uc218\uc9d1\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \ub2e4\uc591\ud55c API\ub97c \ud1b5\ud574 \uc8fc\uc2dd, \uc554\ud638\ud654\ud3d0, \uc678\ud658 \ub4f1\uc758 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 Yahoo Finance API\ub97c \uc0ac\uc6a9\ud558\ub294 \uc608\uc81c\ub97c \ubcf4\uc5ec\ub4dc\ub9ac\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n

import pandas as pd\nimport yfinance as yf\n\n# \ub370\uc774\ud130 \ub2e4\uc6b4\ub85c\ub4dc\nticker = 'AAPL'\nstart_date = '2020-01-01'\nend_date = '2023-01-01'\ndata = yf.download(ticker, start=start_date, end=end_date)\n\nprint(data.head())\n<\/code><\/pre>\n
3. \ub370\uc774\ud130 \ucc98\ub9ac \ubc0f \ubaa8\ub378\ub9c1<\/h2>\n
\uc218\uc9d1\ud55c \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \uc54c\uace0\ub9ac\uc998\uc744 \uc815\uc758\ud574\uc57c \ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ub2e8\uc21c \uc774\ub3d9 \ud3c9\uade0(SMA) \uc804\ub7b5\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc11c\ub294 50\uc77c\uacfc 200\uc77c \uc774\ub3d9 \ud3c9\uade0\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
# \uc774\ub3d9 \ud3c9\uade0 \uacc4\uc0b0\ndata['SMA50'] = data['Close'].rolling(window=50).mean()\ndata['SMA200'] = data['Close'].rolling(window=200).mean()\n<\/code><\/pre>\n
4. \uc2dc\uac01\ud654: \ub77c\ubca8\uacfc \ubc94\ub840 \ucd94\uac00\ud558\uae30<\/h2>\n
\uc2dc\uac01\ud654\ub294 \ub370\uc774\ud130 \ubd84\uc11d\uc5d0\uc11c \ub9e4\uc6b0 \uc911\uc694\ud55c \uc694\uc18c\uc785\ub2c8\ub2e4. \ud30c\uc774\uc36c\uc758 Matplotlib \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc8fc\uac00 \ucc28\ud2b8\uc5d0 \ub77c\ubca8\uacfc \ubc94\ub840\ub97c \ucd94\uac00\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/p>\n
import matplotlib.pyplot as plt\n\n# \ub370\uc774\ud130 \uc2dc\uac01\ud654\nplt.figure(figsize=(14, 7))\nplt.plot(data['Close'], label='Close Price', color='blue')\nplt.plot(data['SMA50'], label='50-Day SMA', color='orange')\nplt.plot(data['SMA200'], label='200-Day SMA', color='green')\n\n# \ub77c\ubca8 \ucd94\uac00\nplt.title('AAPL Price and Moving Averages')\nplt.xlabel('Date')\nplt.ylabel('Price (USD)')\nplt.legend(loc='best') # \ubc94\ub840 \uc704\uce58 \uc9c0\uc815\n\n# \ucc28\ud2b8 \ucd9c\ub825\nplt.show()\n<\/code><\/pre>\n
4.1. \ub77c\ubca8 \ucd94\uac00\ud558\uae30<\/h3>\n
\uc704 \ucf54\ub4dc\uc5d0\uc11c plt.title()<\/code>, plt.xlabel()<\/code>, plt.ylabel()<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \ucc28\ud2b8\uc5d0 \ub77c\ubca8\uc744 \ucd94\uac00\ud558\uc600\uc2b5\ub2c8\ub2e4. \uc774\ub294 \ucc28\ud2b8\uc758 \uc0c1\ub2e8\uacfc \ucd95\uc5d0 \uba85\ud655\ud55c \uc815\ubcf4\ub97c \uc81c\uacf5\ud558\uc5ec \uc0ac\uc6a9\uc790\uc5d0\uac8c \uac00\ub3c5\uc131\uc744 \ub192\uc785\ub2c8\ub2e4.<\/p>\n
4.2. \ubc94\ub840 \ucd94\uac00\ud558\uae30<\/h3>\n
plt.legend()<\/code>\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubc94\ub840\ub97c \ucd94\uac00\ud558\uc600\uc2b5\ub2c8\ub2e4. loc='best'<\/code> \ub9e4\uac1c\ubcc0\uc218\ub294 \ubc94\ub840\uac00 \uacb9\uce58\uc9c0 \uc54a\ub3c4\ub85d \ucd5c\uc801\uc758 \uc704\uce58\ub97c \uc790\ub3d9\uc73c\ub85c \uc120\ud0dd\ud558\ub3c4\ub85d \ud569\ub2c8\ub2e4.<\/p>\n
5. \uc2e4\uc2dc\uac04 \ub370\uc774\ud130 \ubc0f \uc790\ub3d9\ub9e4\ub9e4<\/h2>\n
\uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uad6c\ucd95\ud558\ub824\uba74 \uc2e4\uc2dc\uac04 \ub370\uc774\ud130 \uc218\uc9d1 \ubc0f \ub9e4\ub9e4 \uc2e4\ud589 \uae30\ub2a5\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 WebSocket\uc744 \uc0ac\uc6a9\ud558\uac70\ub098 API\ub97c \uc8fc\uae30\uc801\uc73c\ub85c \ud638\ucd9c\ud558\uc5ec \uc2e4\uc2dc\uac04\uc73c\ub85c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\ub294 Binance\uc758 API\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc2e4\uc2dc\uac04 \uac00\uaca9\uc744 \ubaa8\ub2c8\ud130\ub9c1\ud558\ub294 \ucf54\ub4dc \uc608\uc81c\uc785\ub2c8\ub2e4.<\/p>\n
import requests\n\n# Binance API\ub97c \ud1b5\ud574 \uc2e4\uc2dc\uac04 BTC \uac00\uaca9 \uc5bb\uae30\ndef get_btc_price():\n    url = 'https:\/\/api.binance.com\/api\/v3\/ticker\/price?symbol=BTCUSDT'\n    response = requests.get(url)\n    data = response.json()\n    return float(data['price'])\n\nwhile True:\n    price = get_btc_price()\n    print(f'\ud604\uc7ac BTC \uac00\uaca9: {price} USD')\n    time.sleep(10) # 10\ucd08 \uac04\uaca9\uc73c\ub85c \ud638\ucd9c\n<\/code><\/pre>\n
6. \uacb0\ub860<\/h2>\n
\uc774\ubc88 \ud3ec\uc2a4\ud305\uc5d0\uc11c\ub294 \ud30c\uc774\uc36c\uc744 \uc0ac\uc6a9\ud55c \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c \uac1c\ubc1c \uacfc\uc815\uacfc \ud568\uaed8 \ub370\uc774\ud130 \uc2dc\uac01\ud654\ub97c \uc704\ud55c \ub77c\ubca8 \ubc0f \ubc94\ub840 \ucd94\uac00 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc0b4\ud3b4\ubcf4\uc558\uc2b5\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc740 \uae30\ubcf8\uc801\uc73c\ub85c \ub370\uc774\ud130 \uc218\uc9d1, \ucc98\ub9ac, \uc2dc\uac01\ud654 \ubc0f \ube44\uc988\ub2c8\uc2a4 \ub85c\uc9c1\uc744 \uad6c\uc131\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \uc774\ud574\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \ud5a5\ud6c4 \uc774 \uae30\uc220\uc744 \ubc14\ud0d5\uc73c\ub85c \ub354 \ubcf5\uc7a1\ud55c \uc54c\uace0\ub9ac\uc998 \ubc0f \uc790\ub3d9\ub9e4\ub9e4 \uc2dc\uc2a4\ud15c\uc744 \uac1c\ubc1c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
7. \ucc38\uace0 \uc790\ub8cc<\/h2>\n