import pytest import networkx as nx from networkx.utils import edges_equal, graphs_equal, nodes_equal np = pytest.importorskip("numpy") pd = pytest.importorskip("pandas") class TestConvertPandas: def setup_method(self): self.rng = np.random.RandomState(seed=5) ints = self.rng.randint(1, 11, size=(3, 2)) a = ["A", "B", "C"] b = ["D", "A", "E"] df = pd.DataFrame(ints, columns=["weight", "cost"]) df[0] = a # Column label 0 (int) df["b"] = b # Column label 'b' (str) self.df = df mdf = pd.DataFrame([[4, 16, "A", "D"]], columns=["weight", "cost", 0, "b"]) self.mdf = pd.concat([df, mdf]) def test_exceptions(self): G = pd.DataFrame(["a"]) # adj pytest.raises(nx.NetworkXError, nx.to_networkx_graph, G) G = pd.DataFrame(["a", 0.0]) # elist pytest.raises(nx.NetworkXError, nx.to_networkx_graph, G) df = pd.DataFrame([[1, 1], [1, 0]], dtype=int, index=[1, 2], columns=["a", "b"]) pytest.raises(nx.NetworkXError, nx.from_pandas_adjacency, df) def test_from_edgelist_all_attr(self): Gtrue = nx.Graph( [ ("E", "C", {"cost": 9, "weight": 10}), ("B", "A", {"cost": 1, "weight": 7}), ("A", "D", {"cost": 7, "weight": 4}), ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", True) assert graphs_equal(G, Gtrue) # MultiGraph MGtrue = nx.MultiGraph(Gtrue) MGtrue.add_edge("A", "D", cost=16, weight=4) MG = nx.from_pandas_edgelist(self.mdf, 0, "b", True, nx.MultiGraph()) assert graphs_equal(MG, MGtrue) def test_from_edgelist_multi_attr(self): Gtrue = nx.Graph( [ ("E", "C", {"cost": 9, "weight": 10}), ("B", "A", {"cost": 1, "weight": 7}), ("A", "D", {"cost": 7, "weight": 4}), ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", ["weight", "cost"]) assert graphs_equal(G, Gtrue) def test_from_edgelist_multi_attr_incl_target(self): Gtrue = nx.Graph( [ ("E", "C", {0: "C", "b": "E", "weight": 10}), ("B", "A", {0: "B", "b": "A", "weight": 7}), ("A", "D", {0: "A", "b": "D", "weight": 4}), ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", [0, "b", "weight"]) assert graphs_equal(G, Gtrue) def test_from_edgelist_multidigraph_and_edge_attr(self): # example from issue #2374 edges = [ ("X1", "X4", {"Co": "zA", "Mi": 0, "St": "X1"}), ("X1", "X4", {"Co": "zB", "Mi": 54, "St": "X2"}), ("X1", "X4", {"Co": "zB", "Mi": 49, "St": "X3"}), ("X1", "X4", {"Co": "zB", "Mi": 44, "St": "X4"}), ("Y1", "Y3", {"Co": "zC", "Mi": 0, "St": "Y1"}), ("Y1", "Y3", {"Co": "zC", "Mi": 34, "St": "Y2"}), ("Y1", "Y3", {"Co": "zC", "Mi": 29, "St": "X2"}), ("Y1", "Y3", {"Co": "zC", "Mi": 24, "St": "Y3"}), ("Z1", "Z3", {"Co": "zD", "Mi": 0, "St": "Z1"}), ("Z1", "Z3", {"Co": "zD", "Mi": 14, "St": "X3"}), ] Gtrue = nx.MultiDiGraph(edges) data = { "O": ["X1", "X1", "X1", "X1", "Y1", "Y1", "Y1", "Y1", "Z1", "Z1"], "D": ["X4", "X4", "X4", "X4", "Y3", "Y3", "Y3", "Y3", "Z3", "Z3"], "St": ["X1", "X2", "X3", "X4", "Y1", "Y2", "X2", "Y3", "Z1", "X3"], "Co": ["zA", "zB", "zB", "zB", "zC", "zC", "zC", "zC", "zD", "zD"], "Mi": [0, 54, 49, 44, 0, 34, 29, 24, 0, 14], } df = pd.DataFrame.from_dict(data) G1 = nx.from_pandas_edgelist( df, source="O", target="D", edge_attr=True, create_using=nx.MultiDiGraph ) G2 = nx.from_pandas_edgelist( df, source="O", target="D", edge_attr=["St", "Co", "Mi"], create_using=nx.MultiDiGraph, ) assert graphs_equal(G1, Gtrue) assert graphs_equal(G2, Gtrue) def test_from_edgelist_one_attr(self): Gtrue = nx.Graph( [ ("E", "C", {"weight": 10}), ("B", "A", {"weight": 7}), ("A", "D", {"weight": 4}), ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", "weight") assert graphs_equal(G, Gtrue) def test_from_edgelist_int_attr_name(self): # note: this also tests that edge_attr can be `source` Gtrue = nx.Graph( [("E", "C", {0: "C"}), ("B", "A", {0: "B"}), ("A", "D", {0: "A"})] ) G = nx.from_pandas_edgelist(self.df, 0, "b", 0) assert graphs_equal(G, Gtrue) def test_from_edgelist_invalid_attr(self): pytest.raises( nx.NetworkXError, nx.from_pandas_edgelist, self.df, 0, "b", "misspell" ) pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist, self.df, 0, "b", 1) # see Issue #3562 edgeframe = pd.DataFrame([[0, 1], [1, 2], [2, 0]], columns=["s", "t"]) pytest.raises( nx.NetworkXError, nx.from_pandas_edgelist, edgeframe, "s", "t", True ) pytest.raises( nx.NetworkXError, nx.from_pandas_edgelist, edgeframe, "s", "t", "weight" ) pytest.raises( nx.NetworkXError, nx.from_pandas_edgelist, edgeframe, "s", "t", ["weight", "size"], ) def test_from_edgelist_no_attr(self): Gtrue = nx.Graph([("E", "C", {}), ("B", "A", {}), ("A", "D", {})]) G = nx.from_pandas_edgelist(self.df, 0, "b") assert graphs_equal(G, Gtrue) def test_from_edgelist(self): # Pandas DataFrame G = nx.cycle_graph(10) G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges)) edgelist = nx.to_edgelist(G) source = [s for s, t, d in edgelist] target = [t for s, t, d in edgelist] weight = [d["weight"] for s, t, d in edgelist] edges = pd.DataFrame({"source": source, "target": target, "weight": weight}) GG = nx.from_pandas_edgelist(edges, edge_attr="weight") assert nodes_equal(G.nodes(), GG.nodes()) assert edges_equal(G.edges(), GG.edges()) GW = nx.to_networkx_graph(edges, create_using=nx.Graph) assert nodes_equal(G.nodes(), GW.nodes()) assert edges_equal(G.edges(), GW.edges()) def test_to_edgelist_default_source_or_target_col_exists(self): G = nx.path_graph(10) G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges)) nx.set_edge_attributes(G, 0, name="source") pytest.raises(nx.NetworkXError, nx.to_pandas_edgelist, G) # drop source column to test an exception raised for the target column for u, v, d in G.edges(data=True): d.pop("source", None) nx.set_edge_attributes(G, 0, name="target") pytest.raises(nx.NetworkXError, nx.to_pandas_edgelist, G) def test_to_edgelist_custom_source_or_target_col_exists(self): G = nx.path_graph(10) G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges)) nx.set_edge_attributes(G, 0, name="source_col_name") pytest.raises( nx.NetworkXError, nx.to_pandas_edgelist, G, source="source_col_name" ) # drop source column to test an exception raised for the target column for u, v, d in G.edges(data=True): d.pop("source_col_name", None) nx.set_edge_attributes(G, 0, name="target_col_name") pytest.raises( nx.NetworkXError, nx.to_pandas_edgelist, G, target="target_col_name" ) def test_to_edgelist_edge_key_col_exists(self): G = nx.path_graph(10, create_using=nx.MultiGraph) G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges())) nx.set_edge_attributes(G, 0, name="edge_key_name") pytest.raises( nx.NetworkXError, nx.to_pandas_edgelist, G, edge_key="edge_key_name" ) def test_from_adjacency(self): nodelist = [1, 2] dftrue = pd.DataFrame( [[1, 1], [1, 0]], dtype=int, index=nodelist, columns=nodelist ) G = nx.Graph([(1, 1), (1, 2)]) df = nx.to_pandas_adjacency(G, dtype=int) pd.testing.assert_frame_equal(df, dftrue) @pytest.mark.parametrize("graph", [nx.Graph, nx.MultiGraph]) def test_roundtrip(self, graph): # edgelist Gtrue = graph([(1, 1), (1, 2)]) df = nx.to_pandas_edgelist(Gtrue) G = nx.from_pandas_edgelist(df, create_using=graph) assert graphs_equal(Gtrue, G) # adjacency adj = {1: {1: {"weight": 1}, 2: {"weight": 1}}, 2: {1: {"weight": 1}}} Gtrue = graph(adj) df = nx.to_pandas_adjacency(Gtrue, dtype=int) G = nx.from_pandas_adjacency(df, create_using=graph) assert graphs_equal(Gtrue, G) def test_from_adjacency_named(self): # example from issue #3105 data = { "A": {"A": 0, "B": 0, "C": 0}, "B": {"A": 1, "B": 0, "C": 0}, "C": {"A": 0, "B": 1, "C": 0}, } dftrue = pd.DataFrame(data, dtype=np.intp) df = dftrue[["A", "C", "B"]] G = nx.from_pandas_adjacency(df, create_using=nx.DiGraph()) df = nx.to_pandas_adjacency(G, dtype=np.intp) pd.testing.assert_frame_equal(df, dftrue) def test_edgekey_with_multigraph(self): df = pd.DataFrame( { "source": {"A": "N1", "B": "N2", "C": "N1", "D": "N1"}, "target": {"A": "N2", "B": "N3", "C": "N1", "D": "N2"}, "attr1": {"A": "F1", "B": "F2", "C": "F3", "D": "F4"}, "attr2": {"A": 1, "B": 0, "C": 0, "D": 0}, "attr3": {"A": 0, "B": 1, "C": 0, "D": 1}, } ) Gtrue = nx.MultiGraph( [ ("N1", "N2", "F1", {"attr2": 1, "attr3": 0}), ("N2", "N3", "F2", {"attr2": 0, "attr3": 1}), ("N1", "N1", "F3", {"attr2": 0, "attr3": 0}), ("N1", "N2", "F4", {"attr2": 0, "attr3": 1}), ] ) # example from issue #4065 G = nx.from_pandas_edgelist( df, source="source", target="target", edge_attr=["attr2", "attr3"], edge_key="attr1", create_using=nx.MultiGraph(), ) assert graphs_equal(G, Gtrue) df_roundtrip = nx.to_pandas_edgelist(G, edge_key="attr1") df_roundtrip = df_roundtrip.sort_values("attr1") df_roundtrip.index = ["A", "B", "C", "D"] pd.testing.assert_frame_equal( df, df_roundtrip[["source", "target", "attr1", "attr2", "attr3"]] ) def test_edgekey_with_normal_graph_no_action(self): Gtrue = nx.Graph( [ ("E", "C", {"cost": 9, "weight": 10}), ("B", "A", {"cost": 1, "weight": 7}), ("A", "D", {"cost": 7, "weight": 4}), ] ) G = nx.from_pandas_edgelist(self.df, 0, "b", True, edge_key="weight") assert graphs_equal(G, Gtrue) def test_nonexisting_edgekey_raises(self): with pytest.raises(nx.exception.NetworkXError): nx.from_pandas_edgelist( self.df, source="source", target="target", edge_key="Not_real", edge_attr=True, create_using=nx.MultiGraph(), ) def test_to_pandas_adjacency_with_nodelist(): G = nx.complete_graph(5) nodelist = [1, 4] expected = pd.DataFrame( [[0, 1], [1, 0]], dtype=int, index=nodelist, columns=nodelist ) pd.testing.assert_frame_equal( expected, nx.to_pandas_adjacency(G, nodelist, dtype=int) ) def test_to_pandas_edgelist_with_nodelist(): G = nx.Graph() G.add_edges_from([(0, 1), (1, 2), (1, 3)], weight=2.0) G.add_edge(0, 5, weight=100) df = nx.to_pandas_edgelist(G, nodelist=[1, 2]) assert 0 not in df["source"].to_numpy() assert 100 not in df["weight"].to_numpy()