Python:Plotly .Contour()

In Plotly, the .Contour() function creates a contour plot, which represents 3D surface data in a 2D projection using contour lines or filled color regions. This function is useful for visualizing gradual variations in a dataset over a 2D plane, such as temperature distributions, elevation maps, and probability density functions.

Syntax

plotly.graph_objects.Contour(z=None, x=None, y=None, colorscale=None, contours=None, ...)

• z: A 2D array (list or NumPy array) representing the values to be contoured.
• x: A 1D or 2D array defining the x-coordinates corresponding to z values.
• y: A 1D or 2D array defining the y-coordinates corresponding to z values.
• colorscale: Defines the color scheme of the contour plot (e.g., "Viridis", "Jet", etc.).
• contours: Controls the contour levels with a dictionary containing:
  • start: The starting value of the contours.
  • end: The ending value of the contours.
  • size: The step size between contour levels.

Note: The ellipsis (…) in the syntax indicates that there can be additional optional parameters beyond those listed here.

Example

The following example demonstrates the usage of the .Contour() function:

import plotly.graph_objects as go

# Define x and y coordinates
x = [-2, -1, 0, 1, 2]
y = [-2, -1, 0, 1, 2]

# Define a 2D list for z values
z = [[0.1, 0.2, 0.3, 0.2, 0.1],
     [0.2, 0.4, 0.6, 0.4, 0.2],
     [0.3, 0.6, 1.0, 0.6, 0.3],
     [0.2, 0.4, 0.6, 0.4, 0.2],
     [0.1, 0.2, 0.3, 0.2, 0.1]]

# Create a contour plot
fig = go.Figure(data=[go.Contour(z=z,  # Data values for contour levels
                                 x=x,  # X-coordinates
                                 y=y,  # Y-coordinates
                                 colorscale="Viridis",  # Color scheme
                                 contours=dict(start=0, end=1, size=0.1))])   # Define contour levels

# Display the plot
fig.show()

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The above code generates the following output: