In Python Plotly is called "plotly.py". It is a free and open source plotting library built on top of "plotly.js". It supports over 40 unique chart types. This library is mainly used for financial, geographical, scientific, 3D and data analysis applications.
It can be used to draw various types of charts and graphs, such as scatter plots, line plots, bar plots, box plots, histograms, pie charts, area charts, box plots, histograms, heat maps, Subplots, multiple axes, etc.
Execute the following command at the command prompt to install the plotly module. This is an easy way to install the latest Plotly package from PyPi.
pip install plotly
Contour plot is used to visualize three-dimensional data in a two-dimensional surface by plotting constant z slices, called contours.
It is plotted with the help of the contour function (Z) which is a function of two inputs X and Y (X and Y axis coordinates).
Z = fun(x,y)
The ploty module provides a function called Contour for drawing contour plots.
plotly.graph_objects provides a method contour() to draw contour plots. This function has more than 50 parameters, here we only discuss a few parameters.
plotly.graph_objects.Contour(z=None,x=None,y=None,arg=None,colorbar=None,hoverinfo=None,x=None,y=Non,**kwargs)
z: None by default, a two-dimensional list of values used to calculate contours (z data).
x: x coordinate, default set to None.
y: y coordinate, default set to None.
Plot a contour plot using a two-dimensional array as the z function.
In this example, we will draw a simple contour plot using a 2D array.
import plotly.graph_objects as go fig = go.Figure(data = go.Contour(z=[[4.3, 0.2], [-1.3, 0.9], [-0.32, 7.3], [4.6, 0.203]])) fig.show()
Here the 4X2 array represents the z function.
Draw a contour plot using X and Y coordinates and the z function (2D array).
In this example, we will plot a contour plot using a 2D array and X and Y coordinates.
import plotly.graph_objects as go fig = go.Figure(data = go.Contour(z=[[4.3, 9, 0.2], [-1.3, 2.3, 0.9], [-0.32, 7.3, 0.23], [4.6, 0.203, 0.34]], x=[-8, -3, -2,-1, 0.23], # horizontal axis y=[0, 2, 5, 7, 3]# vertical axis )) fig.show()
The x and y coordinates here represent the horizontal axis and vertical axis respectively.
Use numpy to draw a contour map. Here we will use the numpy.meshgrid() function to generate arrays of X and Y coordinates.
z function will calculate the sum of the square roots of the x and y values using the numpy.sqrt() function.
import numpy as np import plotly.graph_objects as go xlist = np.linspace(-3.0, 3.0, 100) ylist = np.linspace(-3.0, 3.0, 100) # create a mesh X, Y = np.meshgrid(xlist, ylist) Z = np.sqrt(X**2 + Y**2) trace = go.Contour(x = xlist, y = ylist, z = Z) data = [trace] fig = go.Figure(data) fig.show()
The color scale is a parameter of the plotly.graph_objects.Contour() function, used to set the color scale.
Let's take an example and set the palette name string "Earth" as the colorscale parameter.
import plotly.graph_objects as go import numpy as np def f(x, y): return np.sin(x) ** 10 + np.cos(10 + y * x) * np.cos(x) xlist = np.linspace(-3.0, 3.0, 100) ylist = np.linspace(-3.0, 3.0, 100) # A mesh is created with the given co-ordinates by this numpy function X, Y = np.meshgrid(xlist, ylist) Z = f(X,Y) fig = go.Figure(go.Contour(x = xlist, y = ylist, z = Z, colorscale='Earth')) fig.show()
We plotted contour plots using different z functions.
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