Import the data from "Q5 Data.mat" on eClass. We have already imported scipy.io as sio so that we can use SciPy's loadmat function. Unfortunately, the CSVS we've been using up to now are not well-suited for 3D matrices of data. If you print your data after importing it, you may notice that there's a header followed by some data. However, the MAT file is being stored as a dictionary rather than a list, so we can't just index into it using myData[0] or myData[1];we need to use the correct key instead as in myData['correctKey']. Dictionaries will tell you what keys are stored in them if you use myData. keys(). Look at the keys available to you, and use the correct key to store just the data array to a new variable. This is now a regular matrix and you can index into it as you usually would. myMatrix[0, 0] should get you a list in the form [x, y, z] where x and y are just the x and y coordinates on the sheet of paper, and z is the voltage at that point. Plot a 3D surface plot of the data and a contour plot of the data. You can use either plt.contour or plt.contourf for the contour plot, but contourf is more fun to look at. Because the data array pulled from the MAT file is an M*N*3 matrix, if we slice it correctly, we qan get the three, 2D matrices that we need as both types of plots are expecting three arguments-X, Y, and Z-each of which is a 2D matrix. We don't require axis labels this time for either plot, though you may want to try adding them.