quick97

  1. BITCOIN Dataset 불러오기 - pyupbit 사용 # 패키지선언 import os import pyupbit as py import pandas as pd import numpy as np import seaborn as sns import matplotlib import matplotlib.pyplot as plt ㅤ py . get_tickers ( fiat = 'USD' ) Output ['USDT-BTC', 'USDT-ETH', 'USDT-XRP', 'USDT-ETC', 'USDT-OMG', 'USDT-ADA', 'USDT-TUSD', 'USDT-SC', 'USDT-TRX', 'USDT-BCH', 'USDT-DGB', 'USDT-DOGE', 'USDT-ZRX', 'USDT-RVN', 'USDT-BAT'] ㅤ py.get_current_price(['USDT-BTC','USDT-ETH']) Output {'USDT-BTC': 20878.37330684, 'USDT-ETH': 1225.49151905} ㅤ tickers = ['USDT-BTC','USDT-ETH','USDT-XRP','USDT-ADA','USDT-LTC'] interval = 'minute60' ㅤ from tqdm import tqdm coin_set = [] for ticker in tqdm(tickers): coin = py.get_ohlcv(ticker=ticker,count=20000,interval=interval,to='2022-01-01'...

1. S&P500 Dataset 불러오기 - FinanceDataReader 사용 # 패키지 선언 import pandas as pd import numpy as np import FinanceDataReader as fdr import seaborn as sns import matplotlib import matplotlib.pyplot as plt ㅤ # S&P500 지수 (NYSE) sp = fdr.DataReader('US500', '2020-01-01', '2022-01-01') sp Output Close Open High Low Volume Change Date 2020-01-02 3257.85 3244.67 3258.14 3235.53 0.0 0.0084 2020-01-03 3234.85 3226.36 3246.15 3222.34 0.0 -0.0071 2020-01-06 3246.28 3217.55 3246.84 3214.64 0.0 0.0035 2020-01-07 3237.18 3241.86 3244.91 3232.43 0.0 -0.0028 2020-01-08 3253.05 3238.59 3267.07 3236.67 0.0 0.0049 ... ... ... ... ... ... ... 2021-12-27 4791.19 4733.99 4791.49 4733.99 0.0 0.0138 2021-12-28 4786.36 4795.49 4807.02 4780.04 0.0 -0.0010 2021-12-29 4793.06 4788.64 4804.06 4778.08 0.0 0.0014 2021-12-30 4778.73 4794.23 4808.93 4775.33 0.0 -0.0030 2021-12-31 4766.18 4775.21 4786.83 4765.75 0.0 -0.0026 2. Data Scaling from sklearn.preprocessing import MinMaxScaler sca...