wip

docs/api-reference/series.md

@@ -19,6 +19,7 @@
         - diff
         - drop_nulls
         - dtype
+        - ewm_mean
         - fill_null
         - filter
         - gather_every

mkdocs.yml

@@ -112,3 +112,12 @@ markdown_extensions:
 - pymdownx.emoji:
       emoji_index: !!python/name:material.extensions.emoji.twemoji
       emoji_generator: !!python/name:material.extensions.emoji.to_svg
+- pymdownx.arithmatex:
+      generic: true
+extra_javascript:
+  - javascripts/katex.js
+  - https://unpkg.com/katex@0/dist/katex.min.js
+  - https://unpkg.com/katex@0/dist/contrib/auto-render.min.js
+
+extra_css:
+  - https://unpkg.com/katex@0/dist/katex.min.css

narwhals/_pandas_like/series.py

@@ -174,6 +174,24 @@ def dtype(self: Self) -> DType:
             self._native_series, self._dtypes, self._implementation
         )
 
+    def ewm_mean(
+        self,
+        *,
+        com: float | None = None,
+        span: float | None = None,
+        half_life: float | None = None,
+        alpha: float | None = None,
+        adjust: bool = True,
+        min_periods: int = 1,
+        ignore_nulls: bool = False,
+    ) -> PandasLikeSeries:
+        ser = self._native_series
+        result = ser.ewm(
+            com, span, half_life, alpha, min_periods, adjust, ignore_na=ignore_nulls
+        ).mean()
+
+        return self._from_native_series(result)
+
     def scatter(self, indices: int | Sequence[int], values: Any) -> Self:
         if isinstance(values, self.__class__):
             # .copy() is necessary in some pre-2.2 versions of pandas to avoid

narwhals/expr.py

@@ -404,6 +404,29 @@ def all(self) -> Self:
         """
         return self.__class__(lambda plx: self._call(plx).all())
 
+    def ewm_mean(
+        self: Self,
+        *,
+        com: float | None = None,
+        span: float | None = None,
+        half_life: float | None = None,
+        alpha: float | None = None,
+        adjust: bool = True,
+        min_periods: int = 1,
+        ignore_nulls: bool = False,
+    ) -> Self:
+        return self.__class__(
+            lambda plx: self._call(plx).ewm_mean(
+                com=com,
+                span=span,
+                half_life=half_life,
+                alpha=alpha,
+                adjust=adjust,
+                min_periods=min_periods,
+                ignore_nulls=ignore_nulls,
+            )
+        )
+
     def mean(self) -> Self:
         """
         Get mean value.

narwhals/series.py

@@ -383,6 +383,38 @@ def name(self) -> str:
         """
         return self._compliant_series.name  # type: ignore[no-any-return]
 
+    def ewm_mean(
+        self: Self,
+        *,
+        com: float | None = None,
+        span: float | None = None,
+        half_life: float | None = None,
+        alpha: float | None = None,
+        adjust: bool = True,
+        min_periods: int = 1,
+        ignore_nulls: bool = False,
+    ) -> Self:
+        """
+        Compute exponentially-weighted moving average.
+
+        Arguments:
+            com: Specify decay in terms of center of mass, $\\gamma$, with $\\alpha = \\frac{1}{1+\\gamma}\\;\\forall\\;\\gamma\\geq0$
+            span: Specify decay in terms of span, $\\theta$, with $\\alpha = \\frac{2}{\\theta + 1} \\; \\forall \\; \\theta \\geq 1$
+
+        Examples
+        """
+        return self._from_compliant_series(
+            self._compliant_series.ewm_mean(
+                com=com,
+                span=span,
+                half_life=half_life,
+                alpha=alpha,
+                adjust=adjust,
+                min_periods=min_periods,
+                ignore_nulls=ignore_nulls,
+            )
+        )
+
     def cast(
         self,
         dtype: Any,