diff --git a/python/pyspark/sql/plot/core.py b/python/pyspark/sql/plot/core.py
index eb00b8a04f977..0a3a0101e1898 100644
--- a/python/pyspark/sql/plot/core.py
+++ b/python/pyspark/sql/plot/core.py
@@ -96,6 +96,7 @@ class PySparkPlotAccessor:
         "bar": PySparkTopNPlotBase().get_top_n,
         "barh": PySparkTopNPlotBase().get_top_n,
         "line": PySparkSampledPlotBase().get_sampled,
+        "scatter": PySparkSampledPlotBase().get_sampled,
     }
     _backends = {}  # type: ignore[var-annotated]
 
@@ -230,3 +231,36 @@ def barh(self, x: str, y: Union[str, list[str]], **kwargs: Any) -> "Figure":
         ... )  # doctest: +SKIP
         """
         return self(kind="barh", x=x, y=y, **kwargs)
+
+    def scatter(self, x: str, y: str, **kwargs: Any) -> "Figure":
+        """
+        Create a scatter plot with varying marker point size and color.
+
+        The coordinates of each point are defined by two dataframe columns and
+        filled circles are used to represent each point. This kind of plot is
+        useful to see complex correlations between two variables. Points could
+        be for instance natural 2D coordinates like longitude and latitude in
+        a map or, in general, any pair of metrics that can be plotted against
+        each other.
+
+        Parameters
+        ----------
+        x : str
+            Name of column to use as horizontal coordinates for each point.
+        y : str or list of str
+            Name of column to use as vertical coordinates for each point.
+        **kwargs: Optional
+            Additional keyword arguments.
+
+        Returns
+        -------
+        :class:`plotly.graph_objs.Figure`
+
+        Examples
+        --------
+        >>> data = [(5.1, 3.5, 0), (4.9, 3.0, 0), (7.0, 3.2, 1), (6.4, 3.2, 1), (5.9, 3.0, 2)]
+        >>> columns = ['length', 'width', 'species']
+        >>> df = spark.createDataFrame(data, columns)
+        >>> df.plot.scatter(x='length', y='width')  # doctest: +SKIP
+        """
+        return self(kind="scatter", x=x, y=y, **kwargs)
diff --git a/python/pyspark/sql/tests/plot/test_frame_plot_plotly.py b/python/pyspark/sql/tests/plot/test_frame_plot_plotly.py
index 1c52c93a23d3a..ccfe1a75424e0 100644
--- a/python/pyspark/sql/tests/plot/test_frame_plot_plotly.py
+++ b/python/pyspark/sql/tests/plot/test_frame_plot_plotly.py
@@ -28,6 +28,12 @@ def sdf(self):
         columns = ["category", "int_val", "float_val"]
         return self.spark.createDataFrame(data, columns)
 
+    @property
+    def sdf2(self):
+        data = [(5.1, 3.5, 0), (4.9, 3.0, 0), (7.0, 3.2, 1), (6.4, 3.2, 1), (5.9, 3.0, 2)]
+        columns = ["length", "width", "species"]
+        return self.spark.createDataFrame(data, columns)
+
     def _check_fig_data(self, kind, fig_data, expected_x, expected_y, expected_name=""):
         if kind == "line":
             self.assertEqual(fig_data["mode"], "lines")
@@ -37,6 +43,9 @@ def _check_fig_data(self, kind, fig_data, expected_x, expected_y, expected_name=
         elif kind == "barh":
             self.assertEqual(fig_data["type"], "bar")
             self.assertEqual(fig_data["orientation"], "h")
+        elif kind == "scatter":
+            self.assertEqual(fig_data["type"], "scatter")
+            self.assertEqual(fig_data["orientation"], "v")
 
         self.assertEqual(fig_data["xaxis"], "x")
         self.assertEqual(list(fig_data["x"]), expected_x)
@@ -79,6 +88,16 @@ def test_barh_plot(self):
         self._check_fig_data("barh", fig["data"][0], [10, 30, 20], ["A", "B", "C"], "int_val")
         self._check_fig_data("barh", fig["data"][1], [1.5, 2.5, 3.5], ["A", "B", "C"], "float_val")
 
+    def test_scatter_plot(self):
+        fig = self.sdf2.plot(kind="scatter", x="length", y="width")
+        self._check_fig_data(
+            "scatter", fig["data"][0], [5.1, 4.9, 7.0, 6.4, 5.9], [3.5, 3.0, 3.2, 3.2, 3.0]
+        )
+        fig = self.sdf2.plot.scatter(x="width", y="length")
+        self._check_fig_data(
+            "scatter", fig["data"][0], [3.5, 3.0, 3.2, 3.2, 3.0], [5.1, 4.9, 7.0, 6.4, 5.9]
+        )
+
 
 class DataFramePlotPlotlyTests(DataFramePlotPlotlyTestsMixin, ReusedSQLTestCase):
     pass