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¶
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 & deploy apps like this with Dash Enterprise.
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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"
)
),
tickfont=dict(
color="#1f77b4"
)
),
yaxis2=dict(
title=dict(
text="yaxis2 title",
font=dict(
color="#ff7f0e"
)
),
tickfont=dict(
color="#ff7f0e"
),
anchor="free",
overlaying="y",
side="left",
position=0.15
),
yaxis3=dict(
title=dict(
text="yaxis3 title",
font=dict(
color="#d62728"
)
),
tickfont=dict(
color="#d62728"
),
anchor="x",
overlaying="y",
side="right"
),
yaxis4=dict(
title=dict(
text="yaxis4 title",
font=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()
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
With overlayed axes, each axis by default has its own number of ticks. You can sync the number of ticks on a cartesian axis with another one it overlays by setting tickmode="sync". In this example, we sync the ticks on the "Total bill amount" axis with the "Total number of diners" axis that it overlays.
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.
What About Dash?¶
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.add_trace( ... )
# fig.update_layout( ... )
from dash import Dash, dcc, html
app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])
app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter
