Matplotlib 3.0 Cookbook

How to do it...

Here are the steps necessary to plot our graphs:

1. Define the figure and the two axes as follows:

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=[8, 4])

2. Load the winequality data and compute the correlation matrix using these commands:

wine_quality = pd.read_csv('winequality.csv', delimiter=';')corr_wine = wine_quality.corr()

3. Create an extended image with zeros, and insert the correlation matrix into it:

extended_image = np.zeros([100, 100], dtype="d")ny, nx = corr_wine.shapeextended_image[25:25 + ny, 25:25 + nx] = corr_wine

4. Plot the extended image with the given extent, that is, the x and y limits, as follows:

extent = [-2, 2, -3, 1]ax1.imshow(extended_image, extent=extent, interpolation="nearest",           origin="lower")