Perquisites: Python Plotly
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 gofig = 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 objectsfig.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))# titlefig.update_layout( title_text="GeeksforLazyroar - 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 gofig = 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 objectsfig.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"))# titlefig.update_layout( title_text="GeeksforLazyroar - 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 gofig = 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 objectsfig.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 propertiesfig.update_layout( title_text="Four y-axes", width=800,)fig.show() |
Output:
