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# Multiple Axes in Python

How to make a graph with multiple axes (dual y-axis plots, plots with secondary axes) in python.

New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

### 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¶

In :
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}]])

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

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

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()


#### Muliple Y-Axes Subplots¶

In :
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
go.Scatter(x=[1, 2, 3], y=[2, 52, 62], name="yaxis data"),
row=1, col=1, secondary_y=False)

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

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

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

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

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

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

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

In :
import plotly.graph_objects as go

fig = go.Figure()

x=[1, 2, 3],
y=[4, 5, 6],
name="yaxis1 data"
))

x=[2, 3, 4],
y=[40, 50, 60],
name="yaxis2 data",
yaxis="y2"
))

x=[4, 5, 6],
y=[40000, 50000, 60000],
name="yaxis3 data",
yaxis="y3"
))

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="yaxis title",
titlefont=dict(
color="#1f77b4"
),
tickfont=dict(
color="#1f77b4"
)
),
yaxis2=dict(
title="yaxis2 title",
titlefont=dict(
color="#ff7f0e"
),
tickfont=dict(
color="#ff7f0e"
),
anchor="free",
overlaying="y",
side="left",
position=0.15
),
yaxis3=dict(
title="yaxis3 title",
titlefont=dict(
color="#d62728"
),
tickfont=dict(
color="#d62728"
),
anchor="x",
overlaying="y",
side="right"
),
yaxis4=dict(
title="yaxis4 title",
titlefont=dict(
color="#9467bd"
),
tickfont=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()


#### Reference¶

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

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
]) 