jupytext_version: 1.2.1

version: 3.7.3

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_objects as go

fig = go.Figure(go.Scatter(

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

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

hovertemplate =

'<i>Price</i>: $%{y:.2f}'+

'<br><b>X</b>: %{x}<br>'+

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

text = ['Custom text {}'.format(i + 1) for i in range(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_objects as go

fig = go.Figure(go.Pie(

name = "",

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

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

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

hovertemplate = "%{label}: <br>Popularity: %{percent} </br> %{text}"

))

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_objects as go

import plotly.express as px

import pandas as 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, row in 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 continent in continent_names}

fig = go.Figure()

for continent_name, continent in continent_data.items():

fig.add_trace(go.Scatter(

x=continent['gdpPercap'],

y=continent['lifeExp'],

name=continent_name,

text=df_2007['continent'],

hovertemplate=

"<b>%{text}</b><br><br>" +

"GDP per Capita: %{y:$,.0f}<br>" +

"Life Expectation: %{x:.0%}<br>" +

"Population: %{marker.size:,}" +

"<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_objects as 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"]},

hovertemplate =

"<b>%{marker.symbol} </b><br><br>" +

"longitude: %{lon}<br>" +

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

fig.update_layout(

mapbox = {

'accesstoken': token,

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

showlegend = False)

fig.show()