def METHOD_NAME(G, **kwargs):
	""" 
	clusteringPerDegree(G, **kwargs)
	Plots the local clustering coefficient for nodes with specific degree.
	Parameters
	----------
	G : networkit.Graph
		The input graph.
	`**kwargs` : `**kwargs`
		Input parameter currently not used.
	"""
	if not have_seaborn:
		raise MissingDependencyError("seaborn")
	if not have_pandas:
		raise MissingDependencyError("pandas")
	degs = centrality.DegreeCentrality(G).run().scores()
	cc = centrality.LocalClusteringCoefficient(G).run().scores()
	data = pandas.DataFrame({"deg": degs, "cc" : cc})
	data = data.groupby("deg", as_index=False).mean()
	jointplot = seaborn.jointplot("deg", "cc", data, kind="reg", ylim=(0, 1), **kwargs)