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How to hide legend with Plotly Express and Plotly in Python?

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  • Last Updated : 19 Dec, 2021

In this article, we will learn How to hide legend with Plotly Express and Plotly. Here we will discuss two different methods for hiding legend in plotly and plotly express, using two different examples for each to make it more clear.

Syntax: For legend:

  • fig.update_traces(showlegend=False)
  • fig.update(layout_showlegend=False)

Example 1:

In this example, we are hiding legend in Plotly Express with the help of method fig.update_traces(showlegend=False), bypassing the show legend parameter as False.

Python3




# importing packages
import plotly.express as px
  
# using the gapminder dataset
df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", color="sex"
                 symbol="smoker", facet_col="time",
                 labels={"sex": "Gender", "smoker": "Smokes"})
  
# hiding legend in pyplot express.
fig.update_traces(showlegend=False)
  
fig.show()


Output:

Example 2:

In this example, we are hiding legend in Plotly with the help of method fig.update(layout_showlegend=False), by passing the showlegend parameter as False.

Python3




import plotly.graph_objects as go
  
# using the Figure dataset
fig = go.Figure()
  
fig.add_trace(go.Line(name="first", x=["a", "b"], y=[1,3]))
fig.add_trace(go.Line(name="second", x=["a", "b"], y=[2,1]))
fig.add_trace(go.Line(name="third", x=["a", "b"], y=[1,2]))
fig.add_trace(go.Line(name="fourth", x=["a", "b"], y=[2,3]))
  
  
# hiding legend in pyplot express.
fig.update(layout_showlegend=False)
  
fig.show()


Output:

Example 3:

In this example, we are hiding legend in Plotly Express with the help of method fig.update_traces(showlegend=False), by passing the layout_showlegend parameter as False.

Python3




import plotly.express as px
  
# using the iris dataset
df = px.data.iris()
  
# plotting the line chart
fig = px.line(df, y="sepal_width", line_dash='species',
            color='species')
  
# hiding legend in pyplot express.
fig.update_traces(showlegend=False)
  
# showing the plot
fig.show()


Output:


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