3D Bubble Charts in Python
How to make 3D Bubble Charts in Python with Plotly. Three examples of 3D Bubble Charts.
New to Plotly?
Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
3d Bubble chart with Plotly Express¶
import plotly.express as px
import numpy as np
df = px.data.gapminder()
fig = px.scatter_3d(df, x='year', y='continent', z='pop', size='gdpPercap', color='lifeExp',
hover_data=['country'])
fig.update_layout(scene_zaxis_type="log")
fig.show()
Simple Bubble Chart¶
import plotly.graph_objects as go
import pandas as pd
# Get Data: this ex will only use part of it (i.e. rows 750-1500)
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv')
start, end = 750, 1500
fig = go.Figure(data=go.Scatter3d(
x=df['year'][start:end],
y=df['continent'][start:end],
z=df['pop'][start:end],
text=df['country'][start:end],
mode='markers',
marker=dict(
sizemode='diameter',
sizeref=750,
size=df['gdpPercap'][start:end],
color = df['lifeExp'][start:end],
colorscale = 'Viridis',
colorbar_title = 'Life<br>Expectancy',
line_color='rgb(140, 140, 170)'
)
))
fig.update_layout(height=800, width=800,
title='Examining Population and Life Expectancy Over Time')
fig.show()
Bubble Chart Sized by a Variable¶
Plot planets' distance from sun, density, and gravity with bubble size based on planet size
import plotly.graph_objects as go
planets = ['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune', 'Pluto']
planet_colors = ['rgb(135, 135, 125)', 'rgb(210, 50, 0)', 'rgb(50, 90, 255)',
'rgb(178, 0, 0)', 'rgb(235, 235, 210)', 'rgb(235, 205, 130)',
'rgb(55, 255, 217)', 'rgb(38, 0, 171)', 'rgb(255, 255, 255)']
distance_from_sun = [57.9, 108.2, 149.6, 227.9, 778.6, 1433.5, 2872.5, 4495.1, 5906.4]
density = [5427, 5243, 5514, 3933, 1326, 687, 1271, 1638, 2095]
gravity = [3.7, 8.9, 9.8, 3.7, 23.1, 9.0, 8.7, 11.0, 0.7]
planet_diameter = [4879, 12104, 12756, 6792, 142984, 120536, 51118, 49528, 2370]
# Create trace, sizing bubbles by planet diameter
fig = go.Figure(data=go.Scatter3d(
x = distance_from_sun,
y = density,
z = gravity,
text = planets,
mode = 'markers',
marker = dict(
sizemode = 'diameter',
sizeref = 750, # info on sizeref: https://plotly.com/python/reference/scatter/#scatter-marker-sizeref
size = planet_diameter,
color = planet_colors,
)
))
fig.update_layout(width=800, height=800, title = 'Planets!',
scene = dict(xaxis=dict(title='Distance from Sun', titlefont_color='white'),
yaxis=dict(title='Density', titlefont_color='white'),
zaxis=dict(title='Gravity', titlefont_color='white'),
bgcolor = 'rgb(20, 24, 54)'
))
fig.show()
Edit the Colorbar¶
Plot planets' distance from sun, density, and gravity with bubble size based on planet size
import plotly.graph_objects as go
planets = ['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune', 'Pluto']
temperatures = [167, 464, 15, -20, -65, -110, -140, -195, -200, -225]
distance_from_sun = [57.9, 108.2, 149.6, 227.9, 778.6, 1433.5, 2872.5, 4495.1, 5906.4]
density = [5427, 5243, 5514, 3933, 1326, 687, 1271, 1638, 2095]
gravity = [3.7, 8.9, 9.8, 3.7, 23.1, 9.0, 8.7, 11.0, 0.7]
planet_diameter = [4879, 12104, 12756, 6792, 142984, 120536, 51118, 49528, 2370]
# Create trace, sizing bubbles by planet diameter
fig = go.Figure(go.Scatter3d(
x = distance_from_sun,
y = density,
z = gravity,
text = planets,
mode = 'markers',
marker = dict(
sizemode = 'diameter',
sizeref = 750, # info on sizeref: https://plotly.com/python/reference/scatter/#scatter-marker-sizeref
size = planet_diameter,
color = temperatures,
colorbar_title = 'Mean<br>Temperature',
colorscale=[[0, 'rgb(5, 10, 172)'], [.3, 'rgb(255, 255, 255)'], [1, 'rgb(178, 10, 28)']]
)
))
fig.update_layout(width=800, height=800, title = 'Planets!',
scene = dict(xaxis=dict(title='Distance from Sun', titlefont_color='white'),
yaxis=dict(title='Density', titlefont_color='white'),
zaxis=dict(title='Gravity', titlefont_color='white'),
bgcolor = 'rgb(20, 24, 54)'
))
fig.show()
Reference¶
See https://plotly.com/python/reference/scatter3d/ and https://plotly.com/python/reference/scatter/#scatter-marker-sizeref
for more information and chart attribute options!
What About Dash?¶
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_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter