jupyter | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
import plotly.graph_objects as go
import pandas as pd
# Read data from a csv
z_data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/api_docs/mt_bruno_elevation.csv')
fig = go.Figure(data=[go.Surface(z=z_data.values)])
fig.update_layout(title='Mt Bruno Elevation', autosize=False,
width=500, height=500,
margin=dict(l=65, r=50, b=65, t=90))
fig.show()
Display and customize contour data for each axis using the contours
attribute (reference).
import plotly.graph_objects as go
import pandas as pd
# Read data from a csv
z_data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/api_docs/mt_bruno_elevation.csv')
fig = go.Figure(data=[go.Surface(z=z_data.values)])
fig.update_traces(contours_z=dict(show=True, usecolormap=True,
highlightcolor="limegreen", project_z=True))
fig.update_layout(title='Mt Bruno Elevation', autosize=False,
scene_camera_eye=dict(x=1.87, y=0.88, z=-0.64),
width=500, height=500,
margin=dict(l=65, r=50, b=65, t=90)
)
fig.show()
import plotly.graph_objects as go
import numpy as np
z1 = np.array([
[8.83,8.89,8.81,8.87,8.9,8.87],
[8.89,8.94,8.85,8.94,8.96,8.92],
[8.84,8.9,8.82,8.92,8.93,8.91],
[8.79,8.85,8.79,8.9,8.94,8.92],
[8.79,8.88,8.81,8.9,8.95,8.92],
[8.8,8.82,8.78,8.91,8.94,8.92],
[8.75,8.78,8.77,8.91,8.95,8.92],
[8.8,8.8,8.77,8.91,8.95,8.94],
[8.74,8.81,8.76,8.93,8.98,8.99],
[8.89,8.99,8.92,9.1,9.13,9.11],
[8.97,8.97,8.91,9.09,9.11,9.11],
[9.04,9.08,9.05,9.25,9.28,9.27],
[9,9.01,9,9.2,9.23,9.2],
[8.99,8.99,8.98,9.18,9.2,9.19],
[8.93,8.97,8.97,9.18,9.2,9.18]
])
z2 = z1 + 1
z3 = z1 - 1
fig = go.Figure(data=[
go.Surface(z=z1),
go.Surface(z=z2, showscale=False, opacity=0.9),
go.Surface(z=z3, showscale=False, opacity=0.9)
])
fig.show()
Dash is an Open Source Python library which can help you convert plotly figures into a reactive, web-based application. Below is a simple example of a dashboard created using Dash. Its source code can easily be deployed to a PaaS.
from IPython.display import IFrame
IFrame(src= "https://dash-simple-apps.plotly.host/dash-3dsurfaceplot/", width="100%", height=950 ,frameBorder="0")
from IPython.display import IFrame
IFrame(src= "https://dash-simple-apps.plotly.host/dash-3dsurfaceplot/code", width="100%", height=500 ,frameBorder="0")
See https://plot.ly/python/reference/#surface for more information!