A Counter Plot graph is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format.
That is, given a function of two variables 𝑧 = 𝑓 (𝑥, 𝑦) a contour plot is a set of lines connecting points where the function has the same particular value.
These are useful for exploring the potential relationship and optimization areas within datasets.
Process to Create a Contour Plot graph
1. Prepare Your Data:
Your data should consist of three main components: x values, y values, and z values.
The x and y values represent the grid, and the z values are the function values at each point in the grid.
2. Grid the Data:
Often, the data is scattered, and you need to create a regular grid where each point has a corresponding z value.
Tools like NumPy can help in creating this grid.
3. Compute the Contour Lines:
Using the gridded data, compute the contours where each line represents a constant z value.
4. Plot the Contour Lines:
Finally, plot these contours using tools like Matplotlib in Python.
3D and Wireframe Counter plot graph
1. 3D Contour Plot:
This plot shows the contours lifted up to the height they represent, creating a 3D perspective.
It helps visualize the function's topography by showing how the surface rises and falls.
2. Wireframe Contour Plot:
Similar to a wireframe 3D plot but for contours.
It displays the mesh structure without solid faces, allowing you to see the underlying structure and how the surface varies.
