diff --git a/doc/examples/plot_rag.py b/doc/examples/plot_rag.py
new file mode 100644
index 00000000..d0ed3089
--- /dev/null
+++ b/doc/examples/plot_rag.py
@@ -0,0 +1,69 @@
+"""
+=======================
+Region Adjacency Graphs
+=======================
+
+This example demonstrates the use of `merge_nodes` function of a Region
+Adjacency Graph (RAG). When a new node is formed by merging two nodes, the edge
+weight of all the edges incident on it can be updated by a user defined
+function `weight_func`.
+
+The default behaviour is to use the smaller edge weight incase of a conflict.
+THe example below also shows how to use a custom function to take the larger
+weight instead.
+
+"""
+from skimage.graph import rag
+import networkx as nx
+from matplotlib import pyplot as plt
+
+
+def max_edge(g, src, dst, neighbor):
+    try:
+        w1 = g.edge[src][neighbor]['weight']
+    except KeyError:
+        w1 = None
+
+    try:
+        w2 = g.edge[dst][neighbor]['weight']
+    except KeyError:
+        w2 = None
+
+    if w1 is None:
+        return w2
+    elif w2 is None:
+        return w1
+    else:
+        return max(w1, w2)
+
+
+def display(g, title):
+    pos = nx.circular_layout(g)
+    plt.figure()
+    plt.title(title)
+    nx.draw(g, pos)
+    nx.draw_networkx_edge_labels(g, pos, font_size=20)
+
+
+g = rag.RAG()
+g.add_edge(1, 2, weight=10)
+g.add_edge(2, 3, weight=20)
+g.add_edge(3, 4, weight=30)
+g.add_edge(4, 1, weight=40)
+g.add_edge(1, 3, weight=50)
+
+# Assigning dummy labels.
+for n in g.nodes():
+    g.node[n]['labels'] = [n]
+
+gc = g.copy()
+
+display(g, "Original Graph")
+
+g.merge_nodes(1, 3)
+display(g, "Merged with default (min)")
+
+gc.merge_nodes(1, 3, weight_func=max_edge)
+display(gc, "Merged with max")
+
+plt.show()
diff --git a/doc/examples/plot_rag_meancolor.py b/doc/examples/plot_rag_meancolor.py
index 129814e2..11aca77c 100644
--- a/doc/examples/plot_rag_meancolor.py
+++ b/doc/examples/plot_rag_meancolor.py
@@ -11,7 +11,6 @@ difference in mean color. We then join regions with similar mean color.
 
 from skimage import graph, data, io, segmentation, color
 from matplotlib import pyplot as plt
-from skimage import color
 
 
 img = data.coffee()