How to speed up resample with for loop?

Question

I want to get the value of rsi on h1 for each m15 candle, this is how I do this. However, with data larger than 500000 lines, this is very time consuming, is there any better way. Note that it is mandatory to resample each row to get the correct result

import talib
import pandas as pd
import numpy as np

def Data(df):
    df['RSI1'] = talib.RSI(df['close'], timeperiod=13)
    df['RSI2'] = talib.RSI(df['close'], timeperiod=21)
    return df

#len(df) > 555555
df = pd.read_csv('m15_candle.csv')
for i in range(0, len(df)):
    t = df.at[i, 'time']
    if t.hour == 0 and t.minute == 0:
        df = df[i:]
        break

df = df.set_index('time')
ohlc = {
    'open': 'first',
    'high': 'max',
    'low': 'min',
    'close': 'last'
}

rsi1 = [0]*len(df)
rsi2 = [0]*len(df)
for i in range(100000, len(df)):
    h1 = Data(df[:i].resample("1h", offset=0).apply(ohlc).dropna())
    rsi1[i] = h1.iloc[-1]['RSI1'] 
    rsi2[i] = h1.iloc[-1]['RSI2'] 

df['RSI1_h1'] = rsi1
df['RSI2_h1'] = rsi2
df = df.reset_index()
df.to_csv("data.csv", index = False)

How to speed up resample with for loop?

0 Answers0