pandas-ta-classic

q.indicator.pandas_ta wraps every pandas-ta-classic indicator. The provider path preserves pandas-ta’s formulas, parameters, and output names explicitly.

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

Outputs keep pandas-ta’s parameterised names (e.g. BBL_20_2.0, RSI_14):

bbands = q.indicator.pandas_ta.bbands(aapl, length=20)
bbands.tail()
BBL_20_2.0 BBM_20_2.0 BBU_20_2.0 BBB_20_2.0 BBP_20_2.0
datetime
2026-07-20 273.074430 306.946999 340.819567 22.070630 0.789954
2026-07-21 273.775738 308.483498 343.191257 22.502182 0.777409
2026-07-22 275.205973 310.062999 344.920025 22.483834 0.727028
2026-07-23 277.198303 311.492000 345.785696 22.018990 0.648249
2026-07-24 NaN NaN NaN NaN NaN
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