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jupytext_version:1.2.1

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display_name:Python 3

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version:3.7.3

plotly:

description:How to use hover text and formatting in Python with Plotly.

display_as:file_settings

fig.show()

To customize the tooltip on your graph you can use[hovertemplate](https://plot.ly/python/reference/#pie-hovertemplate), which is a template string used for rendering the information that appear on hoverbox.

This template string can include`variables` in %{variable} format,`numbers` in[d3-format's syntax](https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#d3_forma), and`date` in[d3-time-fomrat's syntax](https://github.com/d3/d3-3.x-api-reference/blob/master/Time-Formatting.md#format).

Hovertemplate customize the tooltip text vs.[texttemplate](https://plot.ly/python/reference/#pie-texttemplate) which customizes the text that appears on your chart.

import plotly.graph_objectsas go

fig= go.Figure(go.Scatter(

x= [1,2,3,4,5],

y= [2.02825,1.63728,6.83839,4.8485,4.73463],

'<b>%{text}</b>',

text= ['Custom text{}'.format(i+1)for iinrange(5)],

showlegend=False))

fig.add_trace(go.Scatter(

x= [1,2,3,4,5],

y= [3.02825,2.63728,4.83839,3.8485,1.73463],

hovertemplate='Price: %{y:$.2f}<extra></extra>',

showlegend=False))

fig.update_layout(title="Set hover text with hovertemplate")

fig.show()

import plotly.graph_objectsas go

fig= go.Figure(go.Pie(

name="",

values= [2,5,3,2.5],

labels= ["R","Python","Java Script","Matlab"],

text= ["textA","TextB","TextC","TextD"],

))

fig.show()

The following example shows how to format hover template.[Here](https://plot.ly/python/v3/hover-text-and-formatting/#dash-example) is an example to see how to format hovertemplate in Dash.

import plotly.graph_objectsas go

import plotly.expressas px

import pandasas pd

import math

data= px.data.gapminder()

df_2007= data[data['year']==2007]

df_2007= df_2007.sort_values(['continent','country'])

bubble_size= []

for index, rowin df_2007.iterrows():

bubble_size.append(math.sqrt(row['pop']))

df_2007['size']= bubble_size

continent_names= ['Africa','Americas','Asia','Europe','Oceania']

continent_data= {continent:df_2007.query("continent == '%s'"%continent)

for continentin continent_names}

fig= go.Figure()

for continent_name, continentin continent_data.items():

fig.add_trace(go.Scatter(

x=continent['gdpPercap'],

y=continent['lifeExp'],

name=continent_name,

text=df_2007['continent'],

"<extra></extra>",

marker_size=continent['size'],

))

fig.update_traces(

mode='markers',

marker={'sizemode':'area',

'sizeref':10})

fig.update_layout(

xaxis={

'title':'GDP per capita',

'type':'log'},

yaxis={'title':'Life Expectancy (years)'})

fig.show()

import plotly.graph_objectsas go

token=open(".mapbox_token").read()# you need your own token

fig= go.Figure(go.Scattermapbox(

name="",

mode="markers+text+lines",

lon= [-75,-80,-50],

lat= [45,20,-20],

marker= {'size':20,'symbol': ["bus","harbor","airport"]},

"latitude: %{lat}<br>" ))

fig.update_layout(

mapbox= {

'accesstoken': token,

'style':"outdoors",'zoom':1},

showlegend=False)

fig.show()

Seehttps://plot.ly/python/reference/ for more information and chart attribute options!