# Contour Plots in Python

How to make Contour plots in Python with Plotly.

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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.

### Basic Contour Plot¶

A 2D contour plot shows the contour lines of a 2D numerical array z, i.e. interpolated lines of isovalues of z.

In [1]:
import plotly.graph_objects as go

fig = go.Figure(data =
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]]
))
fig.show()


### Setting X and Y Coordinates in a Contour Plot¶

In [2]:
import plotly.graph_objects as go

fig = go.Figure(data =
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
x=[-9, -6, -5 , -3, -1], # horizontal axis
y=[0, 1, 4, 5, 7] # vertical axis
))
fig.show()


### Colorscale for Contour Plot¶

In [3]:
import plotly.graph_objects as go

fig = go.Figure(data =
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
colorscale='Electric',
))
fig.show()


### Customizing Size and Range of a Contour Plot's Contours¶

In [4]:
import plotly.graph_objects as go

fig = go.Figure(data =
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
colorscale='Hot',
contours=dict(
start=0,
end=8,
size=2,
),
))

fig.show()


### Customizing Spacing Between X and Y Axis Ticks¶

In [5]:
import plotly.graph_objects as go

fig = go.Figure(data =
go.Contour(
z= [[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
dx=10,
x0=5,
dy=10,
y0=10,
)
)

fig.show()


### Connect the Gaps Between None Values in the Z Matrix¶

In [6]:
import plotly.graph_objs as go
from plotly.subplots import make_subplots

fig = make_subplots(rows=2, cols=2, subplot_titles=('connectgaps = False',
'connectgaps = True'))
z = [[None, None, None, 12, 13, 14, 15, 16],
[None, 1, None, 11, None, None, None, 17],
[None, 2, 6, 7, None, None, None, 18],
[None, 3, None, 8, None, None, None, 19],
[5, 4, 10, 9, None, None, None, 20],
[None, None, None, 27, None, None, None, 21],
[None, None, None, 26, 25, 24, 23, 22]]

fig.add_trace(go.Contour(z=z, showscale=False), 1, 1)
fig.add_trace(go.Contour(z=z, showscale=False, connectgaps=True), 1, 2)
fig.add_trace(go.Heatmap(z=z, showscale=False, zsmooth='best'), 2, 1)
fig.add_trace(go.Heatmap(z=z, showscale=False, connectgaps=True, zsmooth='best'), 2, 2)

fig['layout']['yaxis1'].update(title='Contour map')
fig['layout']['yaxis3'].update(title='Heatmap')

fig.show()


### Smoothing the Contour lines¶

In [7]:
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np

z =   [[2, 4, 7, 12, 13, 14, 15, 16],
[3, 1, 6, 11, 12, 13, 16, 17],
[4, 2, 7, 7, 11, 14, 17, 18],
[5, 3, 8, 8, 13, 15, 18, 19],
[7, 4, 10, 9, 16, 18, 20, 19],
[9, 10, 5, 27, 23, 21, 21, 21],
[11, 14, 17, 26, 25, 24, 23, 22]]

fig = make_subplots(rows=1, cols=2,
subplot_titles=('Without Smoothing', 'With Smoothing'))

fig.add_trace(go.Contour(z=z, line_smoothing=0), 1, 1)
fig.add_trace(go.Contour(z=z, line_smoothing=0.85), 1, 2)

fig.show()


### Smooth Contour Coloring¶

In [8]:
import plotly.graph_objects as go

fig = go.Figure(data=
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
# heatmap gradient coloring is applied between each contour level
contours_coloring='heatmap' # can also be 'lines', or 'none'
)
)

fig.show()


### Contour Line Labels¶

In [9]:
import plotly.graph_objects as go

fig = go.Figure(data=
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
contours=dict(
coloring ='heatmap',
showlabels = True, # show labels on contours
labelfont = dict( # label font properties
size = 12,
color = 'white',
)
)))

fig.show()


### Contour Lines¶

In [10]:
import plotly.graph_objects as go

fig = go.Figure(data=
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
contours_coloring='lines',
line_width=2,
)
)

fig.show()


### Custom Contour Plot Colorscale¶

In [11]:
import plotly.graph_objects as go

# Valid color strings are CSS colors, rgb or hex strings
colorscale = [[0, 'gold'], [0.5, 'mediumturquoise'], [1, 'lightsalmon']]

fig = go.Figure(data =
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
colorscale=colorscale)
)

fig.show()


### Color Bar Title¶

In [12]:
import plotly.graph_objects as go

fig = go.Figure(data=
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
colorbar=dict(
title='Color bar title', # title here
titleside='right',
titlefont=dict(
size=14,
family='Arial, sans-serif')
)))

fig.show()


### Color Bar Size for Contour Plots¶

In the example below, both the thickness (given here in pixels) and the length (given here as a fraction of the plot height) are set.

In [13]:
import plotly.graph_objects as go

fig = go.Figure(data=
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
colorbar=dict(
thickness=25,
thicknessmode='pixels',
len=0.6,
lenmode='fraction',
outlinewidth=0
)
))

fig.show()


### Styling Color Bar Ticks for Contour Plots¶

In [14]:
import plotly.graph_objects as go

fig = go.Figure(data =
go.Contour(
z=[[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5., 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10]],
colorbar=dict(nticks=10, ticks='outside',
ticklen=5, tickwidth=1,
showticklabels=True,
tickangle=0, tickfont_size=12)
))

fig.show()


#### Reference¶

See https://plotly.com/python/reference/contour/ for more information and chart attribute options!

### What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

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( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter