Plotly: How to set node positions in a Sankey Diagram?

In go.Sankey() set arrangement="snap" and adjust x and y positions in x=<list> and y=<list>. The following setup will place your nodes as requested.

Plot:

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Please note that the y-values are not explicitly set in this example. As soon as there are more than one node for a common x-value, the y-values will be adjusted automatically for all nodes to be displayed in the same vertical position. If you do want to set all positions explicitly, just set arrangement="fixed"

Edit:

I’ve added a custom function nodify() that assigns identical x-positions to label names that have a common ending such as '0' in ['home0', 'page_a0', 'page_b0']. Now, if you as an example change page_c1 to page_c2 you’ll get this:

enter image description here

Complete code:

import plotly.graph_objects as go
unique_list = ['home0', 'page_a0', 'page_b0', 'page_a1', 'page_b1', 
               'page_c1', 'page_b2', 'page_a2', 'page_c2', 'page_c3']
sources = [0, 0, 1, 2, 2, 3, 3, 4, 4, 7, 6]
targets = [3, 4, 4, 3, 5, 6, 8, 7, 8, 9, 9]
values = [2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2]


def nodify(node_names):
    node_names = unique_list
    # uniqe name endings
    ends = sorted(list(set([e[-1] for e in node_names])))
    
    # intervals
    steps = 1/len(ends)

    # x-values for each unique name ending
    # for input as node position
    nodes_x = {}
    xVal = 0
    for e in ends:
        nodes_x[str(e)] = xVal
        xVal += steps

    # x and y values in list form
    x_values = [nodes_x[n[-1]] for n in node_names]
    y_values = [0.1]*len(x_values)
    
    return x_values, y_values

nodified = nodify(node_names=unique_list)

# plotly setup
fig = go.Figure(data=[go.Sankey(
      arrangement="snap",
      node = dict(
      pad = 15,
      thickness = 20,
      line = dict(color = "black", width = 0.5),
      label = unique_list,
      color = "blue",
     x=nodified[0],
     y=nodified[1]
    ),
    link = dict(
      source = sources,
      target = targets,
      value = values
  ))])

fig.show()

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