text: from d3graph.d3graph import d3graph
  
  from d3graph.utils.adjmat_vec import (
      vec2adjmat,
      adjmat2vec,
      )
  
  __author__ = 'Erdogan Tasksen'
  __email__ = 'erdogant@gmail.com'
  __version__ = '0.1.7'
  
  # module level doc-string
  __doc__ = """
  d3graph
  =======================================================================================
  
  Description
  ------------
  d3graph is a python library that is build on d3js and creates interactive and stand-alone networks.
  The input data is a simple adjacency matrix for which the columns and indexes are the nodes and elements>0 the edges.
  The ouput is a html file that is interactive and stand alone.
  
  Examples
  --------
  >>> # Load some libraries
  >>> import pandas as pd
  >>> import numpy as np
  >>> import networkx as nx
  >>> from d3graph import d3graph
  >>> 
  >>> # Easy Example
  >>> G = nx.karate_club_graph()
  >>> adjmat = nx.adjacency_matrix(G).todense()
  >>> adjmat = pd.DataFrame(index=range(0,adjmat.shape[0]), data=adjmat, columns=range(0,adjmat.shape[0]))
  >>> # Make the interactive graph
  >>> results = d3graph(adjmat)
  >>>
  >>> # Example with more parameters
  >>> G = nx.karate_club_graph()
  >>> adjmat = nx.adjacency_matrix(G).todense()
  >>> adjmat=pd.DataFrame(index=range(0,adjmat.shape[0]), data=adjmat, columns=range(0,adjmat.shape[0]))
  >>> adjmat.columns=adjmat.columns.astype(str)
  >>> adjmat.index=adjmat.index.astype(str)
  >>> adjmat.iloc[3,4]=5
  >>> adjmat.iloc[4,5]=6
  >>> adjmat.iloc[5,6]=7
  >>>
  >>> # Create dataset
  >>> df = pd.DataFrame(index=adjmat.index)
  >>> df['degree']=np.array([*G.degree()])[:,1]
  >>> df['other info']=np.array([*G.degree()])[:,1]
  >>> node_size=df.degree.values*2
  >>> node_color=[]
  >>> for i in range(0,len(G.nodes)):
  >>>     node_color.append(G.nodes[i]['club'])
  >>>     node_name=node_color
  >>>
  >>> # Make some graphs
  >>> out = d3graph(adjmat, df=df, node_size=node_size)
  >>> out = d3graph(adjmat, df=df, node_color=node_size, node_size=node_size)
  >>> out = d3graph(adjmat, df=df, node_color=node_size, node_size=node_size, edge_distance=1000)
  >>> out = d3graph(adjmat, df=df, node_color=node_size, node_size=node_size, charge=1000)
  >>> out = d3graph(adjmat, df=df, node_color=node_name, node_size=node_size, node_size_edge=node_size, node_color_edge='#00FFFF', cmap='Set1', collision=1, charge=250)
  >>>
  >>> # Example with conversion to adjacency matrix
  >>> G = nx.karate_club_graph()
  >>> adjmat = nx.adjacency_matrix(G).todense()
  >>> adjmat = pd.DataFrame(index=range(0,adjmat.shape[0]), data=adjmat, columns=range(0,adjmat.shape[0]))
  >>> import d3graph
  >>> # Convert adjacency matrix to vector with source and target
  >>> vec = d3graph.adjmat2vec(adjmat)
  >>> # Convert vector (source and target) to adjacency matrix.
  >>> adjmat1 = d3graph.vec2adjmat(vec['source'], vec['target'], vec['weight'])
  >>> # Check
  >>> np.all(adjmat==adjmat1.astype(int))
  
  """
  