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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()
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))
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()
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 https://plotly.com/python/reference/scatter3d/ for more information and chart attribute options!