3d Clustering in Python/v3

How to cluster points in 3d with alpha shapes in plotly and Python

Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.

New to Plotly?¶

Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!

3D Clustering with Alpha Shapes¶

In [5]:

import plotly.plotly as py
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/alpha_shape.csv')
df.head()

scatter = dict(
    mode = "markers",
    name = "y",
    type = "scatter3d",
    x = df['x'], y = df['y'], z = df['z'],
    marker = dict( size=2, color="rgb(23, 190, 207)" )
)
clusters = dict(
    alphahull = 7,
    name = "y",
    opacity = 0.1,
    type = "mesh3d",
    x = df['x'], y = df['y'], z = df['z']
)
layout = dict(
    title = '3d point clustering',
    scene = dict(
        xaxis = dict( zeroline=False ),
        yaxis = dict( zeroline=False ),
        zaxis = dict( zeroline=False ),
    )
)
fig = dict( data=[scatter, clusters], layout=layout )
# Use py.iplot() for IPython notebook
py.iplot(fig, filename='3d point clustering')

Out[5]:

Reference¶

See https://plotly.com/python/reference/#mesh3d for more information regarding subplots!