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How to plot on secondary Y-Axis with Plotly Express in Python?

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  • Last Updated : 18 Feb, 2022

Perquisites: Python Ploty

In this article, we will learn how to plot on secondary y-Axis with plotly express. 

One of the most deceptively-powerful features of Plotly data visualization is the ability for a viewer to quickly analyze a sufficient amount of information about data when pointing the cursor over the point label appears. It provides us the easiest way to read and analyze information from the document. Multi-Axis charts are used to plot data points from a query along two or more axes. Here we will discuss different methods to plot multiple y-axis in plotly express to make it more clear.

Syntax: yaxis=dict(title=”yaxis title”, overlaying=”y”, side=”left”, position=[0-1])

Parameters:

  • title: str, (name of the axis)
  • overlaying: str, (name of the bars are plotted over one another)
  • side: [‘top’, ‘bottom’, ‘left’, ‘right’]
  • position: int/float, [in range between 0-1].

Example 1: Two Y-Axis

In this example, we are taking two data plots, the first one is Bar chart and another is a Scatter chart. Update_layout the properties of the figure’s layout with a dict and/or with keyword arguments, In which we will define consecutive secondary yaxis (i.e yaxis, yaxis2 ) with the help of the above-given syntax for each axis.

Python3




import plotly.graph_objects as go
 
fig = go.Figure()
 
fig.add_trace(go.Bar(x=[1, 2, 3], y=[40, 50, 60],
                     name="yaxis1 data", yaxis='y'))
 
fig.add_trace(go.Scatter(x=[2, 3, 4], y=[4, 5, 6],
                      name="yaxis2 data", yaxis="y2"))
 
# Create axis objects
fig.update_layout(xaxis=dict(domain=[0.3, 0.7]),
    #create 1st y axis             
    yaxis=dict(
        title="yaxis title",
        titlefont=dict(color="#1f77b4"),
        tickfont=dict(color="#1f77b4")),
                   
    #create 2nd y axis      
    yaxis2=dict(title="yaxis2 title",overlaying="y",
                side="left",position=0.15))
 
# title
fig.update_layout(
    title_text="Geeksforgeeks - Three y-axes",
    width=800,
)
 
fig.show()

 

 

Output:

 

Example 2: Three Y-axis

 

In this example, we are taking three data plots, the first one is Bar chart and another is a Scatter chart and the last one is another Bar Chart. Update_layout the properties of the figure’s layout with a dict and/or with keyword arguments. In which we will define consecutive secondary y-axis (i.e yaxis, yaxis2, yaxis3… ) with the help of the above-given syntax for each axis

 

Python3




import plotly.graph_objects as go
 
fig = go.Figure()
 
fig.add_trace(go.Bar(x=[1, 2, 3], y=[4, 5, 6],
                     name="yaxis1 data", yaxis='y'))
 
fig.add_trace(go.Scatter(x=[2, 3, 5], y=[40, 50, 60],
                         name="yaxis2 data", yaxis="y2"))
 
fig.add_trace(go.Bar(x=[4, 5, 6], y=[40000, 50000, 60000],
                     name="yaxis3 data", yaxis="y3"))
 
# Create axis objects
fig.update_layout(xaxis=dict(domain=[0.3, 0.7]),
 
                  # create 1st y axis
                  yaxis=dict(
    title="yaxis title",
    titlefont=dict(color="#1f77b4"),
    tickfont=dict(color="#1f77b4")),
 
    # create 2nd y axis
    yaxis2=dict(title="yaxis2 title", overlaying="y",
                side="left", position=0.15),
 
    # create 3rd y axis
    yaxis3=dict(
        title="yaxis3 title",
        anchor="x", overlaying="y", side="right"))
 
 
# title
fig.update_layout(
    title_text="Geeksforgeeks - Three y-axes",
    width=800,
)
 
fig.show()

Output:

Example 3: Four Y-axis

In this example, we are taking two data plots of Bar charts and two plots of Scatters charts. Update_layout the properties of the figure’s layout with a dict and/or with keyword arguments. In which we will define consecutive secondary y-axis (i.e yaxis, yaxis2, yaxis3, yaxis4 ) with the help of above-given syntax for each axis

Python3




import plotly.graph_objects as go
 
fig = go.Figure()
 
fig.add_trace(go.Bar(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.Bar(
    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="Four y-axes",
    width=800,
)
 
fig.show()

Output:


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