How to plot multiple figures as subplots in Python Plotly?

Plotly is an open-source Python library for creating interactive charts. You can use the make_subplots feature available in Plotly to combine multiple figures into subplots within a single layout.

In this tutorial, we will use plotly.graph_objects and plotly.subplots to create multiple subplots. The make_subplots() function allows you to specify the grid layout, while append_trace() adds individual plots to specific positions.

Basic Subplot Creation

Here's how to create a simple subplot layout with three scatter plots ?

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

# Create subplot grid: 3 rows, 1 column
fig = make_subplots(rows=3, cols=1)

# Add first scatter plot to row 1
fig.append_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 6, 7, 8, 9],
    name='Plot 1'
), row=1, col=1)

# Add second scatter plot to row 2  
fig.append_trace(go.Scatter(
    x=[3, 4, 5, 6, 7],
    y=[10, 11, 12, 9, 8],
    name='Plot 2'
), row=2, col=1)

# Add third scatter plot to row 3
fig.append_trace(go.Scatter(
    x=[4, 5, 6, 7, 8],
    y=[6, 7, 8, 9, 10],
    name='Plot 3'
), row=3, col=1)

# Update layout
fig.update_layout(height=600, title_text="Multiple Subplots Example")
fig.show()

Multiple Columns Layout

You can also create subplots with multiple rows and columns ?

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

# Create 2x2 subplot grid
fig = make_subplots(
    rows=2, cols=2,
    subplot_titles=('Plot 1', 'Plot 2', 'Plot 3', 'Plot 4')
)

# Top-left
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]), row=1, col=1)

# Top-right  
fig.add_trace(go.Bar(x=['A', 'B', 'C'], y=[1, 3, 2]), row=1, col=2)

# Bottom-left
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[2, 4, 3]), row=2, col=1)

# Bottom-right
fig.add_trace(go.Bar(x=['X', 'Y', 'Z'], y=[3, 1, 4]), row=2, col=2)

fig.update_layout(height=500, title_text="2x2 Subplot Grid")
fig.show()

Key Parameters

Conclusion

Use make_subplots() to create grid layouts and append_trace() or add_trace() to position plots. This approach allows you to combine different chart types and create comprehensive dashboard-style visualizations in Plotly.