Using Plotly’s make_subplots to Build Multi‑Plot Figures with Shared Axes

Useful answer

Plotly’s make_subplots function lets you quickly assemble a grid of plots with optional shared X or Y axes, reducing boilerplate layout code.

How it works

The function returns a Figure object that already contains a grid layout defined by rows and cols. When you set shared_xaxes=True or shared_yaxes=True, the corresponding axes of all subplots are linked so that zooming or panning in one subplot updates the others. You then add traces to specific cells using add_trace and supplying the row and col arguments.

Worked example

import plotly.graph_objects as go
from plotly.subplots import make_subplots

# Create a 2×2 grid with shared X and Y axes
fig = make_subplots(
    rows=2, cols=2,
    shared_xaxes=True,
    shared_yaxes=True
)

# Add a scatter trace to each subplot
for i in range(1, 5):
    fig.add_trace(
        go.Scatter(x=[0, 1, 2], y=[i, i*2, i*3], name=f'Trace {i}'),
        row=(i-1)//2 + 1,
        col=(i-1)%2 + 1
    )

fig.show()

The loop calculates the correct row and col indices for each trace, ensuring the four scatter plots fill the grid.

Limits

• Performance can degrade when the number of subplots grows large (roughly >50) because each subplot adds DOM nodes, slowing rendering and interaction.
• Shared‑axis settings must be supplied when the figure is created; they cannot be toggled later without rebuilding the Figure object.
• When exporting static images, the optional kaleido engine is required for fig.write_image(); without it the call will raise an error even though fig.show() may still work in a notebook.

Common mistakes

• Omitting shared_xaxes or shared_yaxes when synchronization is desired, resulting in independent axes.
• Mis‑calculating the row and col indices, which places traces in unintended cells or raises an IndexError.
• Attempting to add a trace created with plotly.express directly to a make_subplots figure; such traces must be extracted (e.g., fig_express.data) before adding.