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
2026-07-13 317.019989 323.450012 315.779999 317.309998 43257800
2026-07-14 313.760010 316.190002 311.910004 314.859985 36336800
2026-07-15 317.619995 328.730011 317.320007 327.500000 60957600
2026-07-16 328.010010 334.679993 326.790009 333.260010 62970600
2026-07-17 331.980011 334.989990 329.000000 333.739990 63365300

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
2026-07-13 275.218388 299.187001 323.155614 16.022496 0.878057
2026-07-14 275.776575 300.373500 324.970425 16.377560 0.794478
2026-07-15 274.735727 301.927499 329.119271 18.012120 0.970225
2026-07-16 273.252201 303.628500 334.004799 20.008859 0.987741
2026-07-17 272.685283 305.517999 338.350715 21.493147 0.929785
Back to top