update docstring and examples

python/cugraph/cugraph/dask/centrality/katz_centrality.py

@@ -125,6 +125,7 @@ def katz_centrality(input_graph,
     >>> import cugraph.dask as dcg
     >>> ... Init a DASK Cluster
     >>    see https://docs.rapids.ai/api/cugraph/stable/dask-cugraph.html
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
     >>> chunksize = dcg.get_chunksize(input_data_path)
     >>> ddf = dask_cudf.read_csv(input_data_path, chunksize=chunksize,
                                  delimiter=' ',

python/cugraph/cugraph/dask/community/louvain.py

@@ -58,6 +58,7 @@ def louvain(input_graph, max_iter=100, resolution=1.0):
     >>> import cugraph.dask as dcg
     >>> ... Init a DASK Cluster
     >>    see https://docs.rapids.ai/api/cugraph/stable/dask-cugraph.html
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
     >>> chunksize = dcg.get_chunksize(input_data_path)
     >>> ddf = dask_cudf.read_csv('datasets/karate.csv', chunksize=chunksize,
                                  delimiter=' ',

python/cugraph/cugraph/dask/link_analysis/pagerank.py

@@ -115,6 +115,7 @@ def pagerank(input_graph,
     >>> import cugraph.dask as dcg
     >>> ... Init a DASK Cluster
     >>    see https://docs.rapids.ai/api/cugraph/stable/dask-cugraph.html
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
     >>> chunksize = dcg.get_chunksize(input_data_path)
     >>> ddf = dask_cudf.read_csv(input_data_path, chunksize=chunksize,
                                  delimiter=' ',

python/cugraph/cugraph/dask/traversal/bfs.py

@@ -88,6 +88,7 @@ def bfs(graph,
     >>> import cugraph.dask as dcg
     >>> ... Init a DASK Cluster
     >>    see https://docs.rapids.ai/api/cugraph/stable/dask-cugraph.html
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
     >>> chunksize = dcg.get_chunksize(input_data_path)
     >>> ddf = dask_cudf.read_csv(input_data_path, chunksize=chunksize,
                                  delimiter=' ',

python/cugraph/cugraph/linear_assignment/lap.py

@@ -65,6 +65,7 @@ def hungarian(G, workers, epsilon=None):
 
     Examples
     --------
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
     >>> M = cudf.read_csv('datasets/bipartite.csv', delimiter=' ',
     >>>                   dtype=['int32', 'int32', 'float32'], header=None)
     >>> G = cugraph.Graph()

python/cugraph/cugraph/link_prediction/jaccard.py

@@ -58,7 +58,7 @@ def jaccard(input_graph, vertex_pair=None):
     >>>                   dtype=['int32', 'int32', 'float32'], header=None)
     >>> G = cugraph.Graph()
     >>> G.from_cudf_edgelist(gdf, source='0', destination='1')
-    >>> pairs = cugraph.get_two_hop_neighbors(G)
+    >>> pairs = G.get_two_hop_neighbors()
     >>> df = cugraph.jaccard(G, pairs)
 
     But please remember that cugraph will fill the dataframe with the entire

python/cugraph/cugraph/link_prediction/woverlap.py

@@ -35,8 +35,15 @@ def overlap_w(input_graph, weights, vertex_pair=None):
         as an edge list (edge weights are not used for this algorithm). The
         adjacency list will be computed if not already present.
 
-    weights : cudf.Series
+    weights : cudf.DataFrame
         Specifies the weights to be used for each vertex.
+        Vertex should be represented by multiple columns for multi-column
+        vertices.
+
+        weights['vertex'] : cudf.Series
+            Contains the vertex identifiers
+        weights['weight'] : cudf.Series
+            Contains the weights of vertices
 
     vertex_pair : cudf.DataFrame
         A GPU dataframe consisting of two columns representing pairs of

python/cugraph/cugraph/structure/convert_matrix.py

@@ -233,11 +233,14 @@ def from_pandas_edgelist(df,
 
     Examples
     --------
+    >>  Download dataset from
+    >>  https://github.com/rapidsai/cugraph/datasets/...
     >>> df = pandas.read_csv('datasets/karate.csv', delimiter=' ',
-    >>>                   dtype=['int32', 'int32', 'float32'], header=None)
+    >>>                 header=None, names=["0", "1", "2"],
+    >>>                 dtype={"0": "int32", "1": "int32", "2": "float32"})
     >>> G = cugraph.Graph()
     >>> G.from_pandas_edgelist(df, source='0', destination='1',
-                               edge_attr='2', renumber=False)
+                             edge_attr='2', renumber=False)
     """
     if create_using is Graph:
         G = Graph()

python/cugraph/cugraph/structure/graph_classes.py

@@ -292,8 +292,11 @@ def from_pandas_edgelist(
 
         Examples
         --------
+        >>  Download dataset from
+        >>  https://github.com/rapidsai/cugraph/datasets/...
         >>> df = pandas.read_csv('datasets/karate.csv', delimiter=' ',
-        >>>                   dtype=['int32', 'int32', 'float32'], header=None)
+        >>>                 header=None, names=["0", "1", "2"],
+        >>>                 dtype={"0": "int32", "1": "int32", "2": "float32"})
         >>> G = cugraph.Graph()
         >>> G.from_pandas_edgelist(df, source='0', destination='1',
                                  edge_attr='2', renumber=False)

python/cugraph/cugraph/structure/symmetrize.py

@@ -53,15 +53,11 @@ def symmetrize_df(df, src_name, dst_name, multi=False, symmetrize=True):
 
     Examples
     --------
-    >>> import cugraph.dask as dcg
-    >>> Comms.initialize()
-    >>> chunksize = dcg.get_chunksize(input_data_path)
-    >>> ddf = dask_cudf.read_csv(input_data_path, chunksize=chunksize,
-                                 delimiter=' ',
-                                 names=['src', 'dst', 'weight'],
-                                 dtype=['int32', 'int32', 'float32'])
-    >>> sym_ddf = cugraph.symmetrize_ddf(ddf, "src", "dst", "weight")
-    >>> Comms.destroy()
+    >>> from cugraph.structure.symmetrize import symmetrize_df
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
+    >>> M = cudf.read_csv('datasets/karate.csv', delimiter=' ',
+    >>>                   dtype=['int32', 'int32', 'float32'], header=None)
+    >>> sym_df = symmetrize(M, '0', '1')
     """
     #
     #  Now append the columns.  We add sources to the end of destinations,
@@ -127,9 +123,17 @@ def symmetrize_ddf(df, src_name, dst_name, weight_name=None):
 
     Examples
     --------
-    >>> M = cudf.read_csv('datasets/karate.csv', delimiter=' ',
-    >>>                   dtype=['int32', 'int32', 'float32'], header=None)
-    >>> sym_df = cugraph.symmetrize(M, '0', '1')
+    >>> import cugraph.dask as dcg
+    >>> from cugraph.structure.symmetrize import symmetrize_ddf
+    >>> ... Init a DASK Cluster
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
+    >>> chunksize = dcg.get_chunksize(input_data_path)
+    >>> ddf = dask_cudf.read_csv(input_data_path, chunksize=chunksize,
+                                 delimiter=' ',
+                                 names=['src', 'dst', 'weight'],
+                                 dtype=['int32', 'int32', 'float32'])
+    >>> sym_ddf = symmetrize_ddf(ddf, "src", "dst", "weight")
+    >>> Comms.destroy()
     """
     if weight_name:
         ddf2 = df[[dst_name, src_name, weight_name]]
@@ -180,12 +184,14 @@ def symmetrize(source_col, dest_col, value_col=None, multi=False,
 
     Examples
     --------
+    >>> from cugraph.structure.symmetrize import symmetrize
+    >>  Download dataset from https://github.com/rapidsai/cugraph/datasets/...
     >>> M = cudf.read_csv('datasets/karate.csv', delimiter=' ',
     >>>                   dtype=['int32', 'int32', 'float32'], header=None)
     >>> sources = cudf.Series(M['0'])
     >>> destinations = cudf.Series(M['1'])
     >>> values = cudf.Series(M['2'])
-    >>> src, dst, val = cugraph.symmetrize(sources, destinations, values)
+    >>> src, dst, val = symmetrize(sources, destinations, values)
     """
 
     input_df = None