A Plotly is a Python library that is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot, and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library.
Contour Plots in Plotly
A contour plot has a function of two variables of curves along which the function has constant values so that these curves join the points with equal values. In contour plot, a 2d contour plot presents contour lines of a 2D numerical array z, i.e. interpolated lines of iso values of z.
Syntax: plotly.graph_objects.Contour(arg=None,colorbar=None, hoverinfo=None, x=None,y=None,**kwargs)
Parameters:
arg: dict of properties compatible with this constructor or an instance of plotly.graph_objects.Contour
colorbar: plotly.graph_objects.contour.ColorBar instance or dict with compatible properties
x: Sets the x coordinates.
y: Sets the y coordinates.
z: Sets the z coordinates.
hoverinfo: Determines which trace information appear on hover. If none or skip are set, no information is displayed upon hovering. But, if none is set, click and hover events are still fired.
Example:
Python3
import plotly.graph_objects as go feature_x = np.arange( 0 , 50 , 2 ) feature_y = np.arange( 0 , 50 , 3 ) # Creating 2-D grid of features [X, Y] = np.meshgrid(feature_x, feature_y) Z = np.cos(X / 2 ) + np.sin(Y / 4 ) fig = go.Figure(data = go.Contour(x = feature_x, y = feature_y, z = Z)) fig.show() |
Output:
Adding Colorscale
In plotly, the colorscale for the contour plot is used to add different colors and can be set using the colorscale parameter.
Example:
Python3
import plotly.graph_objects as go feature_x = np.arange( 0 , 50 , 2 ) feature_y = np.arange( 0 , 50 , 3 ) # Creating 2-D grid of features [X, Y] = np.meshgrid(feature_x, feature_y) Z = np.cos(X / 2 ) + np.sin(Y / 4 ) fig = go.Figure(data = go.Contour(x = feature_x, y = feature_y, z = Z, colorscale = 'rainbow' )) fig.show() |
Output:
Adding Labels on Contour Line
Labels can be added using the contours parameter that has a property called showlabels. It determines whether to label the contour lines with their values.
Example:
Python3
import plotly.graph_objects as go feature_x = np.arange( 0 , 50 , 2 ) feature_y = np.arange( 0 , 50 , 3 ) # Creating 2-D grid of features [X, Y] = np.meshgrid(feature_x, feature_y) Z = np.cos(X / 2 ) + np.sin(Y / 4 ) fig = go.Figure(data = go.Contour( x = feature_x, y = feature_y, z = Z, contours = dict ( coloring = 'lines' , showlabels = True ,) )) fig.show() |
Output:
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