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import yfinance as yf
import pandas as pd

# Set the ticker symbol for Nifty futures and BN futures
nifty_symbol = "^NSEI"
bn_symbol = "^NSEBANK"

# Get the historical data for Nifty futures and BN futures
nifty_data = yf.download(nifty_fut, interval='15m', start='2023-03-01', end='2023-03-09')
bn_data = yf.download(bn_fut, interval='15m', start='2023-03-01', end='2023-03-09')

# Create a new dataframe to store the signals and other details
signals_df = pd.DataFrame(columns=['Date', 'Nifty Signal', 'BN Signal', '10AM Price', 'Open Price', 'High Price', 'Low Price', 'Close Price', '10AM - Close Price'])

# Set the percentage threshold for signal identification
threshold = 0.0005

# Loop through each day's data
for date in nifty_data.index.date.unique():
    # Get the data for the current day
    nifty_day_data = nifty_data.loc[date]
    bn_day_data = bn_data.loc[date]
    
    # Check if there are at least 3 candles for the 10AM signal
    if len(nifty_day_data) < 3 or len(bn_day_data) < 3:
        signals_df = signals_df.append({'Date': date, 'Nifty Signal': 'Neutral', 'BN Signal': 'Neutral'}, ignore_index=True)
        continue
    
    # Check for the 10AM signal
    nifty_10am_signal = ''
    bn_10am_signal = ''
    nifty_10am_price = nifty_day_data.iloc[2]['Close']
    bn_10am_price = bn_day_data.iloc[2]['Close']
    nifty_open_price = nifty_day_data.iloc[0]['Open']
    bn_open_price = bn_day_data.iloc[0]['Open']
    nifty_high_price = nifty_day_data.iloc[0:3]['High'].max()
    bn_high_price = bn_day_data.iloc[0:3]['High'].max()
    nifty_low_price = nifty_day_data.iloc[0:3]['Low'].min()
    bn_low_price = bn_day_data.iloc[0:3]['Low'].min()
    nifty_close_price = nifty_day_data.iloc[-1]['Close']
    bn_close_price = bn_day_data.iloc[-1]['Close']
    nifty_diff = abs(nifty_10am_price - nifty_close_price)
    bn_diff = abs(bn_10am_price - bn_close_price)
    
    if nifty_10am_price > nifty_high_price and bn_10am_price > bn_high_price and nifty_diff / nifty_close_price < threshold and bn_diff / bn_close_price < threshold:
        nifty_10am_signal = 'Bullish'
        bn_10am_signal = 'Bullish'
    elif nifty_10am_price < nifty_low_price and bn_10am_price < bn_low_price and nifty_diff / nifty_close_price < threshold and bn_diff / bn_close_price < threshold:
        nifty_10am_signal = 'Bearish'
        bn_10am_signal = 'Bearish'
    
    # Check for the 9:45AM signal
    nifty_945_signal = """
    bn_945_signal = """
    nifty_945_price = nifty_day_data.iloc[1]['Close
