3D Scatter Plots in Python
How to make 3D scatter plots in Python with Plotly.
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 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
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))
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
Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.
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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
Like the 2D scatter plot
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()
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()
See function reference for
px.scatter_3d() or https://plotly.com/python/reference/scatter3d/ for more information and chart attribute options!
What About Dash?¶
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( ... ) import dash import dash_core_components as dcc import dash_html_components as html app = dash.Dash() app.layout = html.Div([ dcc.Graph(figure=fig) ]) app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter