Sankey diagram
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 volume, and label that shows the node name.
import plotly.graph_objects as go
fig = go.Figure(data=[go.Sankey(
node = dict(
pad = 15,
thickness = 20,
line = dict(color = "black", width = 0.5),
label = ["A1", "A2", "B1", "B2", "C1", "C2"],
color = "blue"
),
link = dict(
source = [0, 1, 0, 2, 3, 3], # indices correspond to labels, eg A1, A2, A1, 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 with colored links¶
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)
data = json.loads(response.read())
# override gray link colors with 'source' colors
opacity = 0.4
# change 'magenta' to its 'rgba' value to add opacity
data['data'][0]['node']['color'] = ['rgba(255,0,255, 0.8)' if color == "magenta" else color for color in data['data'][0]['node']['color']]
data['data'][0]['link']['color'] = [data['data'][0]['node']['color'][src].replace("0.8", str(opacity))
for src in data['data'][0]['link']['source']]
fig = go.Figure(data=[go.Sankey(
valueformat = ".0f",
valuesuffix = "TWh",
# Define nodes
node = dict(
pad = 15,
thickness = 15,
line = dict(color = "black", width = 0.5),
label = data['data'][0]['node']['label'],
color = data['data'][0]['node']['color']
),
# Add links
link = dict(
source = data['data'][0]['link']['source'],
target = data['data'][0]['link']['target'],
value = data['data'][0]['link']['value'],
label = data['data'][0]['link']['label'],
color = data['data'][0]['link']['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()
Sankey Diagram in Dash¶
Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.
Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.
```python hide_code=true from IPython.display import IFrame snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/' IFrame(snippet_url + 'sankey-diagram', width='100%', height=630)
### Style Sankey Diagram
This example also uses [hovermode](https://plotly.com/python/reference/layout/#layout-hovermode) to enable multiple tooltips.
```python
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)
data = json.loads(response.read())
fig = go.Figure(data=[go.Sankey(
valueformat = ".0f",
valuesuffix = "TWh",
node = dict(
pad = 15,
thickness = 15,
line = dict(color = "black", width = 0.5),
label = data['data'][0]['node']['label'],
color = data['data'][0]['node']['color']
),
link = dict(
source = data['data'][0]['link']['source'],
target = data['data'][0]['link']['target'],
value = data['data'][0]['link']['value'],
label = data['data'][0]['link']['label']
))])
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()
Hovertemplate and customdata of Sankey diagrams¶
Links and nodes have their own hovertemplate, in which link- or node-specific attributes can be displayed. To add more data to links and nodes, it is possible to use the customdata attribute of link and nodes, as in the following example. For more information about hovertemplate and customdata, please see the tutorial on hover text.
import plotly.graph_objects as go
fig = go.Figure(data=[go.Sankey(
node = dict(
pad = 15,
thickness = 20,
line = dict(color = "black", width = 0.5),
label = ["A1", "A2", "B1", "B2", "C1", "C2"],
customdata = ["Long name A1", "Long name A2", "Long name B1", "Long name B2",
"Long name C1", "Long name C2"],
hovertemplate='Node %{customdata} has total value %{value}<extra></extra>',
color = "blue"
),
link = dict(
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],
customdata = ["q","r","s","t","u","v"],
hovertemplate='Link from node %{source.customdata}<br />'+
'to node%{target.customdata}<br />has value %{value}'+
'<br />and data %{customdata}<extra></extra>',
))])
fig.update_layout(title_text="Basic Sankey Diagram", font_size=10)
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
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],
'pad':10}, # 10 Pixels
link = {
"source": [0, 0, 1, 2, 5, 4, 3, 5],
"target": [5, 3, 4, 3, 0, 2, 2, 3],
"value": [1, 2, 1, 1, 1, 1, 1, 2]}))
fig.show()
Reference¶
See https://plotly.com/python/reference/sankey for more information and options!