Plot misclassfied values in matplotlib
Well since the points would be shown when the target is zero and the predicted value is $1$, then all the plots would be located in the same place and would overlap. So I think you can give a random value for these points and then plot them. 

If the white space is the density of $(0,0)$ values and depicts the ratio of $(0,0)$ points, then you should change the size of the figure or the points. Do you want to do so?

import numpy as np
import matplotlib.pyplot as plt
predicted = list([random.choice([0,1]) for i in range(100)])
target = np.zeros(100)

#adding a random value to the predicted and random values
randomed_predicted = [random.random() for i in range(predicted.count(1))]
randomed_target = [random.random() for i in range(len(randomed_predicted))]
plt.figure(figsize=(5,5))
plt.gca().axes.get_yaxis().set_visible(False) #hiding the yaxis labels
plt.gca().axes.get_xaxis().set_visible(False) #hiding the xaxis labels 
plt.scatter(randomed_target, randomed_predicted, c="black")