diff --git a/NAMESPACE b/NAMESPACE
index 26a2aad..ce3388b 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -221,6 +221,7 @@ export(graph_size)
 export(graph_unconn_count)
 export(group_biconnected_component)
 export(group_by)
+export(group_color)
 export(group_components)
 export(group_data)
 export(group_edge_betweenness)
@@ -519,6 +520,7 @@ importFrom(igraph,graph_from_adjacency_matrix)
 importFrom(igraph,graph_from_data_frame)
 importFrom(igraph,graph_from_edgelist)
 importFrom(igraph,graph_from_incidence_matrix)
+importFrom(igraph,greedy_vertex_coloring)
 importFrom(igraph,gsize)
 importFrom(igraph,harmonic_centrality)
 importFrom(igraph,has_eulerian_cycle)
diff --git a/NEWS.md b/NEWS.md
index 11beda4..b31c93e 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -31,6 +31,7 @@
 * Added `centrality_harmonic()` + deprecated `centrality_closeness_harmonic()`.
   The latter is an interface to netrankr while the former is a more efficient 
   and flexible igraph implementation.
+* Added `group_color()` as an interface to `greedy_vertex_coloring()` in igraph
 
 # tidygraph 1.2.3
 
diff --git a/R/group.R b/R/group.R
index e112c7f..b64fb27 100644
--- a/R/group.R
+++ b/R/group.R
@@ -203,6 +203,17 @@ group_biconnected_component <- function() {
   group <- rep(seq_along(ind), lengths(ind))[order(unlist(ind))][focus_ind(.G(), 'edges')]
   desc_enumeration(group)
 }
+#' @describeIn group_graph Groups nodes by their color using [igraph::greedy_vertex_coloring()]. Be aware that this is not a clustering algorithm as coloring specifically provide a color to each node so that no neighbors have the same color
+#' @importFrom igraph greedy_vertex_coloring
+#' @export
+group_color <- function() {
+  expect_nodes()
+  graph <- .G()
+  group <- greedy_vertex_coloring(graph)
+
+  group <- as.integer(group[focus_ind(.G(), 'nodes')])
+  desc_enumeration(group)
+}
 
 
 # HELPERS -----------------------------------------------------------------
diff --git a/man/centrality.Rd b/man/centrality.Rd
index 3717360..a1c51be 100644
--- a/man/centrality.Rd
+++ b/man/centrality.Rd
@@ -93,7 +93,12 @@ centrality_degree(
 
 centrality_edge_betweenness(weights = NULL, directed = TRUE, cutoff = NULL)
 
-centrality_harmonic(weights, mode = "out", normalized = FALSE, cutoff = NULL)
+centrality_harmonic(
+  weights = NULL,
+  mode = "out",
+  normalized = FALSE,
+  cutoff = NULL
+)
 
 centrality_manual(relation = "dist_sp", aggregation = "sum", ...)
 
diff --git a/man/group_graph.Rd b/man/group_graph.Rd
index 49f89ca..6fbe7c5 100644
--- a/man/group_graph.Rd
+++ b/man/group_graph.Rd
@@ -13,6 +13,7 @@
 \alias{group_spinglass}
 \alias{group_walktrap}
 \alias{group_biconnected_component}
+\alias{group_color}
 \title{Group nodes and edges based on community structure}
 \usage{
 group_components(type = "weak")
@@ -42,6 +43,8 @@ group_spinglass(weights = NULL, ...)
 group_walktrap(weights = NULL, steps = 4, n_groups = NULL)
 
 group_biconnected_component()
+
+group_color()
 }
 \arguments{
 \item{type}{The type of component to find. Either \code{'weak'} or \code{'strong'}}
@@ -112,6 +115,8 @@ grouping of edges supported is biconnected components.
 
 \item \code{group_biconnected_component()}: Group edges by their membership of the maximal binconnected components using \code{\link[igraph:biconnected_components]{igraph::biconnected_components()}}
 
+\item \code{group_color()}: Groups nodes by their color using \code{\link[igraph:greedy_vertex_coloring]{igraph::greedy_vertex_coloring()}}. Be aware that this is not a clustering algorithm as coloring specifically provide a color to each node so that no neighbors have the same color
+
 }}
 \examples{
 create_notable('tutte') \%>\%
diff --git a/tests/testthat/test-group.R b/tests/testthat/test-group.R
index 085bcf0..8c51ba7 100644
--- a/tests/testthat/test-group.R
+++ b/tests/testthat/test-group.R
@@ -20,6 +20,7 @@ test_that("grouping returns integer vector", {
   #expect_type(get_group(gr, group_optimal()), 'integer')
   expect_type(get_group(gr, group_spinglass()), 'integer')
   expect_type(get_group(gr, group_walktrap()), 'integer')
+  expect_type(get_group(gr, group_color()), 'integer')
   gr1 <- activate(gr, edges)
   expect_type(get_group(gr1, group_biconnected_component()), 'integer')
 
@@ -37,6 +38,7 @@ test_that("grouping returns integer of correct length", {
   #expect_length(get_group(gr, group_optimal()), igraph::gorder(gr))
   expect_length(get_group(gr, group_spinglass()), igraph::gorder(gr))
   expect_length(get_group(gr, group_walktrap()), igraph::gorder(gr))
+  expect_length(get_group(gr, group_color()), igraph::gorder(gr))
   gr1 <- activate(gr, edges)
   expect_length(get_group(gr1, group_biconnected_component()), igraph::gsize(gr1))
 
@@ -56,6 +58,7 @@ test_that("grouping requires correct activation", {
   #expect_error(get_group(gr1, group_optimal()))
   expect_error(get_group(gr1, group_spinglass()))
   expect_error(get_group(gr1, group_walktrap()))
+  expect_error(get_group(gr1, group_color()))
 
   skip_on_os('windows')
   expect_error(get_group(gr1, group_leading_eigen()))