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How to make a graph with multiple axes (dual y-axis plots, plots with secondary axes) in python.
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python
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Multiple Axes
17
python/multiple-axes/
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Multiple Y Axes and Plotly Express

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Note: At this time, Plotly Express does not support multiple Y axes on a single figure. To make such a figure, use the make_subplots() function in conjunction with graph objects as documented below.

Two Y Axes

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

# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])

# Add traces
fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[40, 50, 60], name="yaxis data"),
    secondary_y=False,
)

fig.add_trace(
    go.Scatter(x=[2, 3, 4], y=[4, 5, 6], name="yaxis2 data"),
    secondary_y=True,
)

# Add figure title
fig.update_layout(
    title_text="Double Y Axis Example"
)

# Set x-axis title
fig.update_xaxes(title_text="xaxis title")

# Set y-axes titles
fig.update_yaxes(title_text="<b>primary</b> yaxis title", secondary_y=False)
fig.update_yaxes(title_text="<b>secondary</b> yaxis title", secondary_y=True)

fig.show()

Multiple axes 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 & publish apps like this with Dash Enterprise or Plotly Cloud.

from IPython.display import IFrame
snippet_url = 'https://python-docs-dash-snippets.herokuapp.com/python-docs-dash-snippets/'
IFrame(snippet_url + 'multiple-axes', width='100%', height=1200)

Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.

Multiple Y-Axes Subplots

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

fig = make_subplots(rows=2, cols=2,
                    specs=[[{"secondary_y": True}, {"secondary_y": True}],
                           [{"secondary_y": True}, {"secondary_y": True}]])

# Top left
fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[2, 52, 62], name="yaxis data"),
    row=1, col=1, secondary_y=False)

fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[40, 50, 60], name="yaxis2 data"),
    row=1, col=1, secondary_y=True,
)

# Top right
fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[2, 52, 62], name="yaxis3 data"),
    row=1, col=2, secondary_y=False,
)

fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[40, 50, 60], name="yaxis4 data"),
    row=1, col=2, secondary_y=True,
)

# Bottom left
fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[2, 52, 62], name="yaxis5 data"),
    row=2, col=1, secondary_y=False,
)

fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[40, 50, 60], name="yaxis6 data"),
    row=2, col=1, secondary_y=True,
)

# Bottom right
fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[2, 52, 62], name="yaxis7 data"),
    row=2, col=2, secondary_y=False,
)

fig.add_trace(
    go.Scatter(x=[1, 2, 3], y=[40, 50, 60], name="yaxis8 data"),
    row=2, col=2, secondary_y=True,
)

fig.show()

Multiple Axes

Low-level API for creating a figure with multiple axes

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[4, 5, 6],
    name="yaxis1 data"
))


fig.add_trace(go.Scatter(
    x=[2, 3, 4],
    y=[40, 50, 60],
    name="yaxis2 data",
    yaxis="y2"
))

fig.add_trace(go.Scatter(
    x=[4, 5, 6],
    y=[40000, 50000, 60000],
    name="yaxis3 data",
    yaxis="y3"
))

fig.add_trace(go.Scatter(
    x=[5, 6, 7],
    y=[400000, 500000, 600000],
    name="yaxis4 data",
    yaxis="y4"
))


# Create axis objects
fig.update_layout(
    xaxis=dict(
        domain=[0.3, 0.7]
    ),
    yaxis=dict(
        title=dict(
            text="yaxis title",
            font=dict(
                color="#1f77b4"
            )
        ),
    ),
    yaxis2=dict(
        title=dict(
            text="yaxis2 title",
            font=dict(
                color="#ff7f0e"
            )
        ),
        anchor="free",
        overlaying="y",
        side="left",
        position=0.15
    ),
    yaxis3=dict(
        title=dict(
            text="yaxis3 title",
            font=dict(
                color="#d62728"
            )
        ),
        anchor="x",
        overlaying="y",
        side="right"
    ),
    yaxis4=dict(
        title=dict(
            text="yaxis4 title",
            font=dict(
                color="#9467bd"
            )
        ),
        anchor="free",
        overlaying="y",
        side="right",
        position=0.85
    )
)

# Update layout properties
fig.update_layout(
    title_text="multiple y-axes example",
    width=800,
)

fig.show()

Automatically Shifting Axes

New in 5.12

To automatically reposition axes to avoid overlap with other axes with the same overlaying value, set autoshift=True. For autoshift to work on an axis, you'll also need to set anchor="free" on that axis.

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6], name="yaxis data"))

fig.add_trace(go.Scatter(x=[2, 3, 4], y=[40, 50, 60], name="yaxis2 data", yaxis="y2"))

fig.add_trace(
    go.Scatter(x=[4, 5, 6], y=[1000, 2000, 3000], name="yaxis3 data", yaxis="y3")
)

fig.add_trace(
    go.Scatter(x=[3, 4, 5], y=[400, 500, 600], name="yaxis4 data", yaxis="y4")
)


fig.update_layout(
    xaxis=dict(
        domain=[0.25, 0.75]
    ),
    yaxis=dict(
        title=dict(
            text="yaxis title"
        )
    ),
    yaxis2=dict(
        title=dict(
            text="yaxis2 title"
        ),
        overlaying="y",
        side="right"
    ),
    yaxis3=dict(
        title=dict(
            text="yaxis3 title"
        ),
        anchor="free",
        overlaying="y",
        autoshift=True
    ),
    yaxis4=dict(
        title=dict(
            text="yaxis4 title"
        ),
        anchor="free",
        overlaying="y",
        autoshift=True
    ),
)

fig.update_layout(
    title_text="Shifting y-axes with autoshift",
)

fig.show()

Shift Axes by a Specific Number of Pixels

New in 5.12

Set a shift value on an axis to shift an axis by that number of pixels. A positive value shifts an axis to the right. A negative value shifts it to the left. Here, we shift yaxis4 100 pixels further to the left.

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6], name="yaxis data"))

fig.add_trace(go.Scatter(x=[2, 3, 4], y=[40, 50, 60], name="yaxis2 data", yaxis="y2"))

fig.add_trace(
    go.Scatter(x=[4, 5, 6], y=[1000, 2000, 3000], name="yaxis3 data", yaxis="y3")
)

fig.add_trace(
    go.Scatter(x=[3, 4, 5], y=[400, 500, 600], name="yaxis4 data", yaxis="y4")
)


fig.update_layout(
    xaxis=dict(
        domain=[0.25, 0.75]
    ),
    yaxis=dict(
        title=dict(
            text="yaxis title"
        )
    ),
    yaxis2=dict(
        title=dict(
            text="yaxis2 title"
        ),
        overlaying="y",
        side="right"
    ),
    yaxis3=dict(
        title=dict(
            text="yaxis3 title"
        ),
        anchor="free",
        overlaying="y",
        autoshift=True
    ),
    yaxis4=dict(
        title=dict(
            text="yaxis4 title"
        ),
        anchor="free",
        overlaying="y",
        autoshift=True,
        shift=-100
    ),
)

fig.update_layout(
    title_text="Shifting y-axes by a specific number of pixels",
)

fig.show()

Sync Axes Ticks

New in 5.13

Set tickmode="sync" on an overlaying cartesian axis to draw its ticks and gridlines at the positions of the axis it overlays, labeled from its own range. The two axes then share one grid. In this example, the "Total bill amount" axis syncs its ticks with the "Total number of diners" axis that it overlays.

Changed in 7.0: tickmode defaults to "sync" on an overlaying axis. Earlier versions gave each axis its own independent grid. Set tickmode="auto" on the overlaying axis for that behavior.

import plotly.graph_objects as go
from plotly.data import tips

df = tips()

summed_values = df.groupby(by="day", as_index=False).sum(numeric_only=True)
day_order_mapping = {"Thur": 0, "Fri": 1, "Sat": 2, "Sun": 3}
summed_values["order"] = summed_values["day"].apply(lambda day: day_order_mapping[day])
summed_values = summed_values.sort_values(by="order")

days_of_week = summed_values["day"].values
total_bills = summed_values["total_bill"].values
number_of_diners = summed_values["size"].values


fig = go.Figure(
    data=go.Bar(
        x=days_of_week,
        y=number_of_diners,
        name="Total number of diners",
        marker=dict(color="paleturquoise"),
    )
)

fig.add_trace(
    go.Scatter(
        x=days_of_week,
        y=total_bills,
        yaxis="y2",
        name="Total bill amount",
        marker=dict(color="crimson"),
    )
)

fig.update_layout(
    legend=dict(orientation="h"),
    yaxis=dict(
        title=dict(text="Total number of diners"),
        side="left",
        range=[0, 250],
    ),
    yaxis2=dict(
        title=dict(text="Total bill amount"),
        side="right",
        range=[0, 2000],
        overlaying="y",
        tickmode="sync",
    ),
)

fig.show()

Reference

All of the y-axis properties are found here: https://plotly.com/python/reference/layout/yaxis/. For more information on creating subplots see the Subplots in Python section.