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Bubble charts in Python

How to make bubble charts in Python with Plotly.

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In [1]:

import plotly.express as px
df = px.data.gapminder()

fig = px.scatter(df.query("year==2007"), x="gdpPercap", y="lifeExp",
	         size="pop", color="continent",
                 hover_name="country", log_x=True, size_max=60)
fig.show()

In [2]:

import plotly.graph_objects as go

fig = go.Figure(data=[go.Scatter(
    x=[1, 2, 3, 4], y=[10, 11, 12, 13],
    mode='markers',
    marker_size=[40, 60, 80, 100])
])

fig.show()

In [3]:

import plotly.graph_objects as go

fig = go.Figure(data=[go.Scatter(
    x=[1, 2, 3, 4], y=[10, 11, 12, 13],
    mode='markers',
    marker=dict(
        color=['rgb(93, 164, 214)', 'rgb(255, 144, 14)',
               'rgb(44, 160, 101)', 'rgb(255, 65, 54)'],
        opacity=[1, 0.8, 0.6, 0.4],
        size=[40, 60, 80, 100],
    )
)])

fig.show()

In [4]:

import plotly.graph_objects as go

size = [20, 40, 60, 80, 100, 80, 60, 40, 20, 40]
fig = go.Figure(data=[go.Scatter(
    x=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
    y=[11, 12, 10, 11, 12, 11, 12, 13, 12, 11],
    mode='markers',
    marker=dict(
        size=size,
        sizemode='area',
        sizeref=2.*max(size)/(40.**2),
        sizemin=4
    )
)])

fig.show()

In [5]:

import plotly.graph_objects as go

fig = go.Figure(data=[go.Scatter(
    x=[1, 2, 3, 4], y=[10, 11, 12, 13],
    text=['A<br>size: 40', 'B<br>size: 60', 'C<br>size: 80', 'D<br>size: 100'],
    mode='markers',
    marker=dict(
        color=['rgb(93, 164, 214)', 'rgb(255, 144, 14)',  'rgb(44, 160, 101)', 'rgb(255, 65, 54)'],
        size=[40, 60, 80, 100],
    )
)])

fig.show()

In [6]:

import plotly.graph_objects as go

fig = go.Figure(data=[go.Scatter(
    x=[1, 3.2, 5.4, 7.6, 9.8, 12.5],
    y=[1, 3.2, 5.4, 7.6, 9.8, 12.5],
    mode='markers',
    marker=dict(
        color=[120, 125, 130, 135, 140, 145],
        size=[15, 30, 55, 70, 90, 110],
        showscale=True
        )
)])

fig.show()

In [7]:

import plotly.graph_objects as go
import plotly.express as px
import pandas as pd
import math

# Load data, define hover text and bubble size
data = px.data.gapminder()
df_2007 = data[data['year']==2007]
df_2007 = df_2007.sort_values(['continent', 'country'])

hover_text = []
bubble_size = []

for index, row in df_2007.iterrows():
    hover_text.append(('Country: {country}<br>'+
                      'Life Expectancy: {lifeExp}<br>'+
                      'GDP per capita: {gdp}<br>'+
                      'Population: {pop}<br>'+
                      'Year: {year}').format(country=row['country'],
                                            lifeExp=row['lifeExp'],
                                            gdp=row['gdpPercap'],
                                            pop=row['pop'],
                                            year=row['year']))
    bubble_size.append(math.sqrt(row['pop']))

df_2007['text'] = hover_text
df_2007['size'] = bubble_size
sizeref = 2.*max(df_2007['size'])/(100**2)

# Dictionary with dataframes for each continent
continent_names = ['Africa', 'Americas', 'Asia', 'Europe', 'Oceania']
continent_data = {continent:df_2007.query("continent == '%s'" %continent)
                              for continent in continent_names}

# Create figure
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=continent['text'],
        marker_size=continent['size'],
        ))

# Tune marker appearance and layout
fig.update_traces(mode='markers', marker=dict(sizemode='area',
                                              sizeref=sizeref, line_width=2))

fig.update_layout(
    title=dict(text='Life Expectancy v. Per Capita GDP, 2007'),
    xaxis=dict(
        title=dict(text='GDP per capita (2000 dollars)'),
        gridcolor='white',
        type='log',
        gridwidth=2,
    ),
    yaxis=dict(
        title=dict(text='Life Expectancy (years)'),
        gridcolor='white',
        gridwidth=2,
    ),
    paper_bgcolor='rgb(243, 243, 243)',
    plot_bgcolor='rgb(243, 243, 243)',
)
fig.show()

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter

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