3d-scatter-plots.md

jupyter

jupytext kernelspec language_info plotly notebook_metadata_filter text_representation all extension format_name format_version jupytext_version .md markdown 1.3 1.14.1 display_name language name Python 3 python python3 codemirror_mode file_extension mimetype name nbconvert_exporter pygments_lexer version name version ipython 3 .py text/x-python python python ipython3 3.8.8 description display_as language layout name order page_type permalink thumbnail How to make 3D scatter plots in Python with Plotly. 3d_charts python base 3D Scatter Plots 2 example_index python/3d-scatter-plots/ thumbnail/3d-scatter.jpg

3D scatter plot with Plotly Express

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Like the 2D scatter plot px.scatter, the 3D function px.scatter_3d plots individual data in three-dimensional space.

import plotly.express as px
df = px.data.iris()
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
              color='species')
fig.show()

A 4th dimension of the data can be represented thanks to the color of the markers. Also, values from the species column are used below to assign symbols to markers.

import plotly.express as px
df = px.data.iris()
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
                    color='petal_length', symbol='species')
fig.show()

Style 3d scatter plot

It is possible to customize the style of the figure through the parameters of px.scatter_3d for some options, or by updating the traces or the layout of the figure through fig.update.

import plotly.express as px
df = px.data.iris()
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
              color='petal_length', size='petal_length', size_max=18,
              symbol='species', opacity=0.7)

# tight layout
fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
fig.show()

3d scatter plots in Dash

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.

from IPython.display import IFrame
snippet_url = 'https://python-docs-dash-snippets.herokuapp.com/python-docs-dash-snippets/'
IFrame(snippet_url + '3d-scatter-plots', width='100%', height=1200)

Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.

3D Scatter Plot with go.Scatter3d

Basic 3D Scatter Plot

If Plotly Express does not provide a good starting point, it is also possible to use the more generic go.Scatter3D class from plotly.graph_objects. Like the 2D scatter plot go.Scatter, go.Scatter3d plots individual data in three-dimensional space.

import plotly.graph_objects as go
import numpy as np

# Helix equation
t = np.linspace(0, 10, 50)
x, y, z = np.cos(t), np.sin(t), t

fig = go.Figure(data=[go.Scatter3d(x=x, y=y, z=z,
                                   mode='markers')])
fig.show()

3D Scatter Plot with Colorscaling and Marker Styling

import plotly.graph_objects as go
import numpy as np

# Helix equation
t = np.linspace(0, 20, 100)
x, y, z = np.cos(t), np.sin(t), t

fig = go.Figure(data=[go.Scatter3d(
    x=x,
    y=y,
    z=z,
    mode='markers',
    marker=dict(
        size=12,
        color=z,                # set color to an array/list of desired values
        colorscale='Viridis',   # choose a colorscale
        opacity=0.8
    )
)])

# tight layout
fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
fig.show()

Reference

See function reference for px.scatter_3d() or https://plotly.com/python/reference/scatter3d/ for more information and chart attribute options!