When working with data visualization in Python, Plotly is a powerful library that provides interactive and visually appealing plots. One common requirement is to add a secondary axis to a plot, which allows us to display two different scales on the same plot. In this article, we will explore three different ways to achieve this in Plotly Python.

Option 1: Using the `make_subplots` function

The `make_subplots` function in Plotly allows us to create subplots with shared or independent axes. We can utilize this function to create a plot with a secondary axis. Here’s how:

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

# Create subplots with shared x-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])

# Add traces to the plot
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6], name="Primary Axis"))
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[10, 20, 30], name="Secondary Axis"), secondary_y=True)

# Set axis labels
fig.update_xaxes(title_text="X-axis")
fig.update_yaxes(title_text="Primary Axis", secondary_y=False)
fig.update_yaxes(title_text="Secondary Axis", secondary_y=True)

# Show the plot
fig.show()

This code snippet creates a subplot with a shared x-axis and a secondary y-axis. We add two traces to the plot, one for the primary axis and another for the secondary axis. By setting the `secondary_y` parameter to `True` for the secondary axis trace, Plotly automatically assigns it to the secondary y-axis. We can then update the axis labels using the `update_xaxes` and `update_yaxes` functions.

Option 2: Using the `add_trace` function

Another way to add a secondary axis in Plotly is by using the `add_trace` function. Here’s an example:

import plotly.graph_objects as go

# Create a figure
fig = go.Figure()

# Add the primary axis trace
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6], name="Primary Axis"))

# Add the secondary axis trace
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[10, 20, 30], name="Secondary Axis"))

# Create the secondary y-axis
fig.update_layout(yaxis2=dict(overlaying="y", side="right"))

# Show the plot
fig.show()

In this approach, we create a figure and add two traces to it, one for the primary axis and another for the secondary axis. To create the secondary y-axis, we use the `update_layout` function and specify the `yaxis2` parameter with the desired configuration. The `overlaying` parameter set to “y” ensures that the secondary axis overlays the primary axis, and the `side` parameter set to “right” positions the secondary axis on the right side of the plot.

Option 3: Using the `make_subplots` function with shared x-axis

Similar to option 1, we can also use the `make_subplots` function to create a plot with a secondary axis. However, in this approach, we create subplots with a shared x-axis instead of a shared y-axis. Here’s an example:

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

# Create subplots with shared x-axis
fig = make_subplots(rows=2, cols=1, shared_xaxes=True)

# Add traces to the subplots
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6], name="Primary Axis"), row=1, col=1)
fig.add_trace(go.Scatter(x=[1, 2, 3], y=[10, 20, 30], name="Secondary Axis"), row=2, col=1)

# Set axis labels
fig.update_xaxes(title_text="X-axis", row=2, col=1)
fig.update_yaxes(title_text="Primary Axis", row=1, col=1)
fig.update_yaxes(title_text="Secondary Axis", row=2, col=1)

# Show the plot
fig.show()

In this option, we create subplots with shared x-axes using the `make_subplots` function. We add the primary axis trace to the first subplot and the secondary axis trace to the second subplot. By specifying the `row` and `col` parameters, we assign the traces to the respective subplots. Finally, we update the axis labels using the `update_xaxes` and `update_yaxes` functions.

After exploring these three options, the best approach depends on the specific requirements of your plot. If you need more flexibility in terms of layout and customization, option 2 might be the most suitable. However, if you prefer a simpler and more concise solution, options 1 and 3 provide a straightforward way to add a secondary axis. Ultimately, it’s important to choose the option that best fits your needs and coding style.