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# Sankey Diagram in Python

How to make Sankey Diagrams in Python with Plotly.

A Sankey diagram is a flow diagram, in which the width of arrows is proportional to the flow quantity.

### Basic Sankey Diagram¶

Sankey diagrams visualize the contributions to a flow by defining source to represent the source node, target for the target node, value to set the flow volum, and label that shows the node name.

In [1]:
import plotly.graph_objects as go

fig = go.Figure(data=[go.Sankey(
node = dict(
thickness = 20,
line = dict(color = "black", width = 0.5),
label = ["A1", "A2", "B1", "B2", "C1", "C2"],
color = "blue"
),
source = [0, 1, 0, 2, 3, 3], # indices correspond to labels, eg A1, A2, A2, B1, ...
target = [2, 3, 3, 4, 4, 5],
value = [8, 4, 2, 8, 4, 2]
))])

fig.update_layout(title_text="Basic Sankey Diagram", font_size=10)
fig.show()


### More complex Sankey diagram¶

In [2]:
import plotly.graph_objects as go
import urllib, json

url = 'https://raw.githubusercontent.com/plotly/plotly.js/master/test/image/mocks/sankey_energy.json'
response = urllib.request.urlopen(url)
fig = go.Figure(data=[go.Sankey(
valueformat = ".0f",
valuesuffix = "TWh",
# Define nodes
node = dict(
thickness = 15,
line = dict(color = "black", width = 0.5),
label =  data['data'][0]['node']['label'],
color =  data['data'][0]['node']['color']
),
))])

fig.update_layout(title_text="Energy forecast for 2050<br>Source: Department of Energy & Climate Change, Tom Counsell via <a href='https://bost.ocks.org/mike/sankey/'>Mike Bostock</a>",
font_size=10)
fig.show()


### Style Sankey Diagram¶

This example also uses hovermode to enable multiple tooltips.

In [3]:
import plotly.graph_objects as go
import urllib, json

url = 'https://raw.githubusercontent.com/plotly/plotly.js/master/test/image/mocks/sankey_energy.json'
response = urllib.request.urlopen(url)

fig = go.Figure(data=[go.Sankey(
valueformat = ".0f",
valuesuffix = "TWh",
node = dict(
thickness = 15,
line = dict(color = "black", width = 0.5),
label =  data['data'][0]['node']['label'],
color =  data['data'][0]['node']['color']
),
))])

fig.update_layout(
hovermode = 'x',
title="Energy forecast for 2050<br>Source: Department of Energy & Climate Change, Tom Counsell via <a href='https://bost.ocks.org/mike/sankey/'>Mike Bostock</a>",
font=dict(size = 10, color = 'white'),
plot_bgcolor='black',
paper_bgcolor='black'
)

fig.show()


### Define Node Position¶

The following example sets node.x and node.y to place nodes in the specified locations, except in the snap arrangement (default behaviour when node.x and node.y are not defined) to avoid overlapping of the nodes, therefore, an automatic snapping of elements will be set to define the padding between nodes via nodepad. The other possible arrangements are: 1) perpendicular 2) freeform 3) fixed

In [4]:
import plotly.graph_objects as go

fig = go.Figure(go.Sankey(
arrangement = "snap",
node = {
"label": ["A", "B", "C", "D", "E", "F"],
"x": [0.2, 0.1, 0.5, 0.7, 0.3, 0.5],
"y": [0.7, 0.5, 0.2, 0.4, 0.2, 0.3],