def from_pandas_edgelist(df,
source="source",
destination="destination",
edge_attr=None,
create_using=Graph,
renumber=True):
"""
Initialize a graph from the edge list. It is an error to call this
method on an initialized Graph object. Source argument is source
column name and destination argument is destination column name.
By default, renumbering is enabled to map the source and destination
vertices into an index in the range [0, V) where V is the number
of vertices. If the input vertices are a single column of integers
in the range [0, V), renumbering can be disabled and the original
external vertex ids will be used.
If weights are present, edge_attr argument is the weights column name.
Parameters
----------
input_df : pandas.DataFrame
A DataFrame that contains edge information
source : str or array-like
source column name or array of column names
destination : str or array-like
destination column name or array of column names
edge_attr : str or None
the weights column name. Default is None
renumber : bool
Indicate whether or not to renumber the source and destination
vertex IDs. Default is True.
create_using: cugraph.DiGraph or cugraph.Graph
Indicate whether to create a directed or undirected graph
Returns
-------
G : cugraph.DiGraph or cugraph.Graph
graph containing edges from the pandas edgelist
Examples
--------
>>> df = pandas.read_csv('datasets/karate.csv', delimiter=' ',
>>> dtype=['int32', 'int32', 'float32'], header=None)
>>> G = cugraph.Graph()
>>> G.from_pandas_edgelist(df, source='0', destination='1',
edge_attr='2', renumber=False)
"""
if create_using is Graph:
G = Graph()
elif create_using is DiGraph:
G = DiGraph()
else:
raise Exception("create_using supports Graph and DiGraph")
G.from_pandas_edgelist(df,
source=source,
destination=destination,
edge_attr=edge_attr,
renumber=renumber)
return G
def from_pandas_edgelist(df,
source="source",
destination="destination",
edge_attr=None,
create_using=Graph,
renumber=True):
"""
Initialize a graph from the edge list. It is an error to call this
method on an initialized Graph object. Source argument is source
column name and destination argument is destination column name.
By default, renumbering is enabled to map the source and destination
vertices into an index in the range [0, V) where V is the number
of vertices. If the input vertices are a single column of integers
in the range [0, V), renumbering can be disabled and the original
external vertex ids will be used.
If weights are present, edge_attr argument is the weights column name.
Parameters
----------
df : pandas.DataFrame
A DataFrame that contains edge information
source : str or array-like, optional (default='source')
source column name or array of column names
destination : str or array-like, optional (default='destination')
destination column name or array of column names
edge_attr : str or None, optional (default=None)
the weights column name.
renumber : bool, optional (default=True)
Indicate whether or not to renumber the source and destination
vertex IDs.
create_using: cugraph.DiGraph or cugraph.Graph, optional (default=Graph)
Indicate whether to create a directed or undirected graph
Returns
-------
G : cugraph.DiGraph or cugraph.Graph
graph containing edges from the pandas edgelist
Examples
--------
>>> # Download dataset from
>>> # https://github.com/rapidsai/cugraph/datasets/...
>>> df = pd.read_csv(datasets_path / 'karate.csv', delimiter=' ',
... 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)
"""
if create_using is Graph:
G = Graph()
elif create_using is DiGraph:
G = DiGraph()
else:
raise Exception("create_using supports Graph and DiGraph")
G.from_pandas_edgelist(df,
source=source,
destination=destination,
edge_attr=edge_attr,
renumber=renumber)
return G