TA-Lib

q.indicator.talib wraps every TA-Lib indicator in a pandas-friendly signature. The provider path is explicit because formulas and warm-up behavior can differ from native and pandas-ta implementations.

Sample data

We use qrt’s bundled AAPL sample dataset — loaded offline via q.data.datasets.load, no network dependency (see the Data tutorial for more on q.data):

import pandas as pd

import qrt as q

aapl = q.data.datasets.load("aapl")
aapl.tail()
open high low close volume
datetime
2026-07-20 333.510010 333.709991 323.679993 326.589996 53468000
2026-07-21 323.130005 329.600006 322.220001 327.739990 41338900
2026-07-22 327.869995 329.000000 323.339996 325.890015 38755900
2026-07-23 321.730011 323.299988 319.350006 321.660004 40840800
2026-07-24 NaN NaN NaN NaN 47460975

Single-output indicators return a Series named after the indicator; multi-output indicators return a DataFrame with TA-Lib’s output names as columns:

rsi = q.indicator.talib.RSI(aapl)
atr = q.indicator.talib.ATR(aapl, timeperiod=20)
macd = q.indicator.talib.MACD(aapl)

pd.concat([rsi, atr, macd], axis=1).tail()
rsi atr macd macdsignal macdhist
datetime
2026-07-20 63.879542 8.034510 8.889585 6.168248 2.721337
2026-07-21 64.546165 8.001785 8.932867 6.721172 2.211696
2026-07-22 62.546375 7.884696 8.717402 7.120418 1.596985
2026-07-23 58.112878 7.817461 8.111810 7.318696 0.793114
2026-07-24 NaN NaN NaN NaN NaN
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