matrices = [np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]]),
np.array( [[13, 0, 1, 0, 2, 0],[ 0, 50, 2, 0, 10, 0],[ 0, 13, 16, 0, 0, 3],[ 0, 0, 0, 13, 1, 0],[ 0, 40, 0, 1, 15, 0],[ 0, 0, 0, 0, 0, 20]])]
fig = plt.figure(tight_layout=True)
ax = fig.add_gridspec(3,3)
ax_list = [] #list containing axes objects
for i in range(9):
ax_list.append(fig.add_subplot(ax[i%3,i//3]))
df_cm = DataFrame(matrices[i], index=range(1,7), columns=range(1,7))
pretty_plot_confusion_matrix(df_cm, ax_list[i], annot=True, cmap="Oranges", fmt='.2f', fz=7,
lw=0.5, cbar=False, show_null_values=0, pred_val_axis='y')
plt.show()