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

The sample data is as follows:

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]

Using the sample code from the documentation

fig = go.Figure(data=[go.Sankey(
    node = dict(
      pad = 15,
      thickness = 20,
      line = dict(color = "black", width = 0.5),
      label = unique_list,
      color = "blue"
    ),
    link = dict(
      source = sources,
      target = targets,
      value = values
  ))])

fig.show()

This outputs the following sankey diagram

However, I would like to get all the values which end in the same number in the same vertical column, just like how the leftmost column has all of it's nodes ending with a 0. I see in the docs that it is possible to move the node positions, however I was wondering if there was a cleaner way to do it other than manually inputting x and y values. Any help appreciated.

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:

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:

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()