diff --git a/bigframes/operations/_matplotlib/core.py b/bigframes/operations/_matplotlib/core.py
index 663e7a789f..ad5abb4bca 100644
--- a/bigframes/operations/_matplotlib/core.py
+++ b/bigframes/operations/_matplotlib/core.py
@@ -14,6 +14,12 @@
 
 import abc
 import typing
+import uuid
+
+import pandas as pd
+
+import bigframes.constants as constants
+import bigframes.dtypes as dtypes
 
 DEFAULT_SAMPLING_N = 1000
 DEFAULT_SAMPLING_STATE = 0
@@ -44,12 +50,13 @@ def _kind(self):
 
     def __init__(self, data, **kwargs) -> None:
         self.kwargs = kwargs
-        self.data = self._compute_plot_data(data)
+        self.data = data
 
     def generate(self) -> None:
-        self.axes = self.data.plot(kind=self._kind, **self.kwargs)
+        plot_data = self._compute_plot_data()
+        self.axes = plot_data.plot(kind=self._kind, **self.kwargs)
 
-    def _compute_plot_data(self, data):
+    def _compute_sample_data(self, data):
         # TODO: Cache the sampling data in the PlotAccessor.
         sampling_n = self.kwargs.pop("sampling_n", DEFAULT_SAMPLING_N)
         sampling_random_state = self.kwargs.pop(
@@ -61,6 +68,9 @@ def _compute_plot_data(self, data):
             sort=False,
         ).to_pandas()
 
+    def _compute_plot_data(self):
+        return self._compute_sample_data(self.data)
+
 
 class LinePlot(SamplingPlot):
     @property
@@ -78,3 +88,45 @@ class ScatterPlot(SamplingPlot):
     @property
     def _kind(self) -> typing.Literal["scatter"]:
         return "scatter"
+
+    def __init__(self, data, **kwargs) -> None:
+        super().__init__(data, **kwargs)
+
+        c = self.kwargs.get("c", None)
+        if self._is_sequence_arg(c):
+            raise NotImplementedError(
+                f"Only support a single color string or a column name/posision. {constants.FEEDBACK_LINK}"
+            )
+
+    def _compute_plot_data(self):
+        sample = self._compute_sample_data(self.data)
+
+        # Works around a pandas bug:
+        # https://github.com/pandas-dev/pandas/commit/45b937d64f6b7b6971856a47e379c7c87af7e00a
+        c = self.kwargs.get("c", None)
+        if pd.core.dtypes.common.is_integer(c):
+            c = self.data.columns[c]
+        if self._is_column_name(c, sample) and sample[c].dtype == dtypes.STRING_DTYPE:
+            sample[c] = sample[c].astype("object")
+
+        return sample
+
+    def _is_sequence_arg(self, arg):
+        return (
+            arg is not None
+            and not isinstance(arg, str)
+            and isinstance(arg, typing.Iterable)
+        )
+
+    def _is_column_name(self, arg, data):
+        return (
+            arg is not None
+            and pd.core.dtypes.common.is_hashable(arg)
+            and arg in data.columns
+        )
+
+    def _generate_new_column_name(self, data):
+        col_name = None
+        while col_name is None or col_name in data.columns:
+            col_name = f"plot_temp_{str(uuid.uuid4())[:8]}"
+        return col_name
diff --git a/tests/system/small/operations/test_plotting.py b/tests/system/small/operations/test_plotting.py
index 5ca3382e2a..41ea7d4ebb 100644
--- a/tests/system/small/operations/test_plotting.py
+++ b/tests/system/small/operations/test_plotting.py
@@ -209,6 +209,37 @@ def test_scatter(scalars_dfs):
     )
 
 
+@pytest.mark.parametrize(
+    ("c"),
+    [
+        pytest.param("red", id="red"),
+        pytest.param("c", id="int_column"),
+        pytest.param("species", id="color_column"),
+        pytest.param(3, id="column_index"),
+    ],
+)
+def test_scatter_args_c(c):
+    data = {
+        "a": [1, 2, 3],
+        "b": [1, 2, 3],
+        "c": [1, 2, 3],
+        "species": ["r", "g", "b"],
+    }
+    df = bpd.DataFrame(data)
+    pd_df = pd.DataFrame(data)
+
+    ax = df.plot.scatter(x="a", y="b", c=c)
+    pd_ax = pd_df.plot.scatter(x="a", y="b", c=c)
+    assert len(ax.collections[0].get_facecolor()) == len(
+        pd_ax.collections[0].get_facecolor()
+    )
+    for idx in range(len(ax.collections[0].get_facecolor())):
+        tm.assert_numpy_array_equal(
+            ax.collections[0].get_facecolor()[idx],
+            pd_ax.collections[0].get_facecolor()[idx],
+        )
+
+
 def test_sampling_plot_args_n():
     df = bpd.DataFrame(np.arange(bf_mpl.DEFAULT_SAMPLING_N * 10), columns=["one"])
     ax = df.plot.line()
diff --git a/third_party/bigframes_vendored/pandas/plotting/_core.py b/third_party/bigframes_vendored/pandas/plotting/_core.py
index d901f41ef8..f8da9efdc0 100644
--- a/third_party/bigframes_vendored/pandas/plotting/_core.py
+++ b/third_party/bigframes_vendored/pandas/plotting/_core.py
@@ -266,10 +266,6 @@ def scatter(
 
                 - A single color string referred to by name, RGB or RGBA code,
                   for instance 'red' or '#a98d19'.
-                - A sequence of color strings referred to by name, RGB or RGBA
-                  code, which will be used for each point's color recursively. For
-                  instance ['green','yellow'] all points will be filled in green or
-                  yellow, alternatively.
                 - A column name or position whose values will be used to color the
                   marker points according to a colormap.