diff --git a/networkx/drawing/layout.py b/networkx/drawing/layout.py
index fa120d670748..c6f2f16ec92f 100644
--- a/networkx/drawing/layout.py
+++ b/networkx/drawing/layout.py
@@ -33,6 +33,7 @@
     "spiral_layout",
     "multipartite_layout",
     "arf_layout",
+    "arc_layout",
 ]
 
 
@@ -1219,6 +1220,50 @@ def arf_layout(
     return dict(zip(G.nodes(), p))
 
 
+def arc_layout(G: nx.Graph, subset_key="layer", radius=1, rotation=0) -> dict:
+    """Arc layout for networkx
+
+    Provides  a   layout  where  a  multipartite   graph  is
+    displayed  on a  unit circle.  This could  provide clear
+    visuals for data that is highly clustered.
+
+    Parameters
+    ----------
+    G : nx.Graph
+        Networkx (Di)Graph
+    subset_key : object
+        Node attribute to cluster the network on
+    radius : float
+        Radius of the unit circle
+    rotation : float
+        Rotation of the axes of the unit circle
+
+    Returns
+    -------
+    pos : dict
+        A dictionary of positions keyed by node.
+
+    Examples
+    --------
+    >>> subset_sizes = [5, 5, 4, 3, 2, 4, 4, 3]
+    >>> G = nx.complete_multipartite_graph(*subset_sizes)
+    >>> pos = nx.arf_layout(G, subset_key = "layer")
+    """
+    import numpy as np
+
+    attrs = nx.get_node_attributes(G, subset_key)
+    categories = set(attrs.values())
+    angles = np.linspace(0, 2 * np.pi, len(categories), 0) + rotation
+    pos = {}
+    for category, angle in zip(categories, angles):
+        # collect nodes
+        subset = [node for node, attr in attrs.items() if attr == category]
+        radii = np.linspace(0, radius, len(subset), 0)
+        for node, rad in zip(subset, radii):
+            pos[node] = rad * np.array([np.cos(angle), np.sin(angle)])
+    return pos
+
+
 def rescale_layout(pos, scale=1):
     """Returns scaled position array to (-scale, scale) in all axes.
 
diff --git a/networkx/drawing/tests/test_layout.py b/networkx/drawing/tests/test_layout.py
index 48d0e6d9d888..6bba0defdfbc 100644
--- a/networkx/drawing/tests/test_layout.py
+++ b/networkx/drawing/tests/test_layout.py
@@ -303,6 +303,15 @@ def test_multipartite_layout(self):
 
         pytest.raises(ValueError, nx.multipartite_layout, G, align="foo")
 
+    def test_arc_layout(self):
+        sizes = (0, 5, 7, 2, 8)
+        G = nx.complete_multipartite_graph(*sizes)
+
+        vpos = nx.arc_layout(G, subset_key="subset")
+        assert len(vpos) == len(G)
+
+        pytest.raises(TypeError, nx.multipartite_layout, G, radius="non-sensible input")
+
     def test_kamada_kawai_costfn_1d(self):
         costfn = nx.drawing.layout._kamada_kawai_costfn
 
@@ -448,6 +457,18 @@ def test_multipartite_layout_nonnumeric_partition_labels():
     assert len(pos) == len(G)
 
 
+def test_arc_layout_nonnumeric_paratition_labels():
+    """see gh-5123."""
+    g = nx.Graph()
+    g.add_node(0, subset="s0")
+    g.add_node(1, subset="s0")
+    g.add_node(2, subset="s1")
+    g.add_node(3, subset="s1")
+    g.add_edges_from([(0, 2), (0, 3), (1, 2)])
+    pos = nx.arc_layout(g, subset_key="subset")
+    assert len(pos) == len(g)
+
+
 def test_multipartite_layout_layer_order():
     """Return the layers in sorted order if the layers of the multipartite
     graph are sortable. See gh-5691"""