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c417b6f 99ccc0e c417b6f 99ccc0e 79cf85f 99ccc0e c417b6f 36bbb34 c417b6f 36bbb34 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | import yfinance as yf
import pandas as pd
import os
def create_data():
os.makedirs("data", exist_ok=True)
btc_ticker = yf.Ticker("BTC-USD")
df = btc_ticker.history(period="max")
df.index = pd.to_datetime(df.index).date
df.index = pd.to_datetime(df.index)
del df["Dividends"]
del df["Stock Splits"]
df.columns = [c.lower() for c in df.columns]
# Create target feature
df['Tomorrow'] = df['close'].shift(-1)
df['target'] = df['Tomorrow'].pct_change() * 100
df = df.drop(['Tomorrow'], axis=1)
assets = (
"^GSPC ^DJI ^N225 ^N100 000001.SS "
"CL=F GC=F HG=F NVDA AAPL"
)
additional_data = yf.download(assets, start="2014-09-17")
df_add = additional_data.Close
df_add = df_add.fillna(method='ffill')
df_ = df.merge(df_add, left_index=True, right_index=True, how='left')
df_ = df_.fillna(method='ffill')
df_.dropna(inplace=True)
df_.to_csv("data/assets_data.csv")
return df_
if __name__ == '__main__':
create_data()
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