Sankey Diagram

Intermediate

Learning Objectives

After completing this recipe, you will be able to:

Understand the structure and purpose of Sankey diagrams
Visualize data flows
Implement simple flow diagrams using Matplotlib

Note: Sankey diagrams are typically created using interactive libraries like Plotly, but here we cover examples using Matplotlib for static rendering.

0. Setup


import matplotlib.pyplot as plt
from matplotlib.sankey import Sankey
 
fig = plt.figure(figsize=(12, 6))
ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[], title="User Flow Sankey")
 
# Define flows and labels
flows = [100, -40, -30, -20, -10]
labels = ['Visit', 'Bounce', 'Search', 'Cart', 'Purchase']
orientations = [0, 1, 1, 0, 0]
 
sankey = Sankey(ax=ax, scale=0.01, offset=0.2, head_angle=150, format='%.0f', unit='%')
sankey.add(flows=flows, labels=labels, orientations=orientations,
           pathlengths=[0.25, 0.25, 0.25, 0.25, 0.25],
           patchlabel="Visitor Flow",
           alpha=0.6)
sankey.finish()
plt.show()

Sankey Diagram

2. Connecting Complex Flows

You can connect flows between two systems.


fig = plt.figure(figsize=(12, 6))
ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[], title="Complex Flow")
 
sankey = Sankey(ax=ax, unit=None)
# First flow
sankey.add(flows=[10, -3, -7], label='Input', orientations=[0, 0, 1])
# Second flow (connected to the first)
sankey.add(flows=[7, -2, -5], label='Output', prior=0, connect=(2, 0))
sankey.finish()
plt.show()

ℹ️

Complex flows can be represented by connecting them in this manner as shown above.