Hover Text and Formatting in Python-Plotly Last Updated : 06 Jul, 2022 Comments Improve Suggest changes Like Article Like Report Prerequisites: Python Plotly In this article, we will explore how to Hover Text and Formatting in Python. It is a useful approach to Hover Text and Formatting as it allows to reveal a large amount of data about complex information. One of the most deceptively-powerful features of 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. Example 1: Default The default setting is layout.hovermode='closest', wherein a single hover label appears for the point directly underneath the cursor. Python3 import plotly.express as px df = px.data.gapminder().query("continent=='Oceania'") fig = px.line(df, x="year", y="lifeExp", color="country") fig.update_traces(mode="markers+lines") fig.show() Output: Example 2: x unified If layout.hovermode='x' , a single hover label appears per trace, for points at the same x value as the cursor. Python3 import plotly.express as px df = px.data.gapminder().query("continent=='Oceania'") fig = px.line(df, x="year", y="lifeExp", color="country") fig.update_traces(mode="markers+lines", hovertemplate=None) fig.update_layout(hovermode="x unified") fig.show() Output: Example 3: y unified If layout.hovermode='y' , a single hover label appears per trace, for points at the same y value as the cursor. Python3 import plotly.express as px df = px.data.gapminder().query("continent=='Oceania'") fig = px.line(df, x="year", y="lifeExp", color="country") fig.update_traces(mode="markers+lines", hovertemplate=None) fig.update_layout(hovermode="y unified") fig.show() Output: Text Formatting Example 1: user_defined hovertemplate GDP: %{x} <br>Life Expectancy: %{y} Here, GDP and Expectancy is used as naming convention about the data whereas %{ <variable>} which allows to revel a large amount of data about complex information. Python3 import plotly.express as px df_2007 = px.data.gapminder().query("year==2007") fig = px.scatter(df_2007, x="gdpPercap", y="lifeExp", log_x=True, color='continent') fig.update_traces(hovertemplate='GDP: %{x} <br>Life Expectancy: %{y}') fig.show() Output: Example 2: user_defined hovertemplate %{label}: <br>Popularity: %{percent} </br> %{text} Here, Label, Percent, and Text is used as naming convention about the data whereas %{ <variable>} which allows to revel a large amount of data about complex information. Python3 import plotly.graph_objects as go fig = go.Figure(go.Pie( name = "", values = [2, 5, 3, 2.5], labels = ["R", "Python", "Java Script", "Matlab"], text = ["R", "Python", "JS", "Matlab"], hovertemplate = "%{label}: <br>Popularity: %{percent} </br> %{text}" )) fig.show() Output: Comment More infoAdvertise with us Next Article How to apply different titles for each different subplots using Plotly in Python? skrg141 Follow Improve Article Tags : Python Python-Plotly Practice Tags : python Similar Reads Plotly tutorial Plotly library in Python is an open-source library that can be used for data visualization and understanding data simply and easily. Plotly supports various types of plots like line charts, scatter plots, histograms, box plots, etc. So you all must be wondering why Plotly is over other visualization 15+ min read Introduction to Plotly-online using Python The plotly library is an interactive open-source library. 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