polars.Expr.ewm_sum

Expr.ewm_sum(
    *,
    com: float | None = None,
    span: float | None = None,
    half_life: float | None = None,
    alpha: float | None = None,
    min_samples: int = 1,
    ignore_nulls: bool = False,
) → Expr

Compute exponentially-weighted moving sum.

engine:In MemoryStreaming

Warning

This functionality is considered unstable. It may be changed at any point without it being considered a breaking change.

Parameters:

com

Specify decay in terms of center of mass, \(\gamma\), with

\[\alpha = \frac{1}{1 + \gamma} \; \forall \; \gamma \geq 0\]

span

Specify decay in terms of span, \(\theta\), with

\[\alpha = \frac{2}{\theta + 1} \; \forall \; \theta \geq 1\]

half_life

Specify decay in terms of half-life, \(\tau\), with

\[\alpha = 1 - \exp \left\{ \frac{ -\ln(2) }{ \tau } \right\} \; \forall \; \tau > 0\]

alpha

Specify smoothing factor alpha directly, \(0 < \alpha \leq 1\).

min_samples

Minimum number of observations in window required to have a value (otherwise result is null).

ignore_nulls

Ignore missing values when calculating weights.

Examples

>>> df = pl.DataFrame({"a": [1, 2, 3]})
>>> df.select(pl.col("a").ewm_sum(alpha=0.5))
shape: (3, 1)
┌──────┐
│ a    │
│ ---  │
│ f64  │
╞══════╡
│ 1.0  │
│ 2.5  │
│ 4.25 │
└──────┘