Indicators

q.indicator contains deterministic market measurements for one instrument at a time. Indicators preserve pandas indexes, never group by symbol implicitly, and do not express investment intent.

Use indicators directly in research, dashboards, alerts, and rules, or wrap them in q.feature.Feature when the result must be named, versioned, computed per entity, and materialized for model training.

q.indicator.sma(prices["close"], 20)
q.indicator.ema(prices["close"], 20)
q.indicator.relative_strength(prices["close"], benchmark, lookback=21)

Native functions are flat under q.indicator; provider-specific formulas remain explicit under q.indicator.talib and q.indicator.pandas_ta. The examples below are executed live by Quarto every time the docs are built.

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

Calculate reusable market measurements directly. These values are not registered or persisted as model features until they are wrapped by q.feature.Feature:

sma_20 = q.indicator.sma(aapl["close"], 20)
sma_100 = q.indicator.sma(aapl["close"], 100)

price_indicators = pd.DataFrame({"close": aapl["close"], "sma_20": sma_20, "sma_100": sma_100})
price_indicators.tail()
close sma_20 sma_100
datetime
2026-07-13 317.309998 299.187001 279.561089
2026-07-14 314.859985 300.373500 280.068622
2026-07-15 327.500000 301.927499 280.740221
2026-07-16 333.260010 303.628500 281.429456
2026-07-17 333.739990 305.517999 282.107506 
q.indicator.ema(aapl["close"], 20).tail()
datetime
2026-07-13    303.524259
2026-07-14    304.603852
2026-07-15    306.784438
2026-07-16    309.305921
2026-07-17    311.632975
Name: close, dtype: float64

To add a native indicator, create qrt/indicator/_<indicator>.py with one public function and re-export it from qrt/indicator/__init__.py. Keep one canonical formula per native name; provider variants remain under their provider namespace.

Visualizing indicators

q.plot.col renders any indicator DataFrame as an interactive Plotly chart with hover, zoom, and range-selector buttons. Visualization does not register the values as stored features:

fig = q.plot.col(
    price_indicators,
    title="AAPL close price with SMA overlays",
    ylabel="Price",
    height=450,
)
fig.show()
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