human
I am working on the file "Notebook/sitemap_visualization_tool.ipynb".
The first task is:
In this example, we split the string into a list of substrings as separated by the dashes and check if the list has more than 3 elements.
Working with Pandas DataFrames in Python can seem very complicated - especially for those new to Python - but the rewards are great.
Visualizing sitemap
Storing data in tables is the only reasonable option, but it's not always the best way to view the data. This is especially true when sharing it with others.
The sitemap dataframe we've generated can be nicely visualized using graphviz, where paths are illustrated with nodes and edges. The nodes contain site page layers and the edges are labelled by the number of sub-pages existing within that path.
Can you write Python code for it?
 ... Give me a the Python code you requested?
assistant
#Here is the Python code you requested.

def make_sitemap_graph(df, layers=3, limit=50, size='8,5'):
    ''' Make a sitemap graph up to a specified layer depth.
    
    sitemap_layers : DataFrame
        The dataframe created by the peel_layers function 
        containing sitemap information.
    
    layers : int
        Maximum depth to plot.
        
    limit : int
        The maximum number node edge connections. Good to set this
        low for visualizing deep into site maps.
    '''
    
    
    # Check to make sure we are not trying to plot too many layers
    if layers > len(df) - 1:
        layers = len(df)-1
        print('There are only %d layers available to plot, setting layers=%d'
              % (layers, layers))
    
    
    # Initialize graph
    f = graphviz.Digraph('sitemap', filename='sitemap_graph_%d_layer' % layers)
    f.body.extend(['rankdir=LR', 'size="%s"' % size])
    
    
    def add_branch(f, names, vals, limit, connect_to=''):
        ''' Adds a set of nodes and edges to nodes on the previous layer. '''
        
        # Get the currently existing node names
        node_names = [item.split('"')[1] for item in f.body if 'label' in item]
        
        # Only add a new branch it it will connect to a previously created node
        if connect_to:
            if connect_to in node_names:
                for name, val in list(zip(names, vals))[:limit]:
                    f.node(name='%s-%s' % (connect_to, name), label=name)
                    f.edge(connect_to, '%s-%s' % (connect_to, name), label='{:,}'.format(val))
        

    f.attr('node', shape='rectangle') # Plot nodes as rectangles
    
    # Add the first layer of nodes
    for name, counts in df.groupby(['0'])['counts'].sum().reset_index()\
                          .sort_values(['counts'], ascending=False).values:
        f.node(name=name, label='{} ({:,})'.format(name, counts))
    
    if layers == 0:
        return f
    
    f.attr('node', shape='oval') # Plot nodes as ovals
    f.graph_attr.update()
    
    # Loop over each layer adding nodes...