how to plot class labels using a distribution list

I have a dataset with train and test sets and three classes A,B,and C. I want to create a plot in which I show the distribution of data labels in each class for TRAIN and TEST sets separately (these are binary class labels 0 and 1). Ideally, I would like to show TRAIN and TEST stats in different colours, maybe in a bar chart. These are the values:

a_train = [40,75]
a_test = [10,19]

b_train=[41,75]
b_test=[10,19]

c_train=[51,75]
c_test=[12,19]

I have tried to use pyplot but was confused how to create the plot:

import numpy as np                                                               
import matplotlib.pyplot as plt

top=[(['A',[[40,75],[10,19]]]),('B',[[41,75],[10,19]]),('C',[[51,75],[12,19]])]

labels, ys = zip(*top)
xs = np.arange(len(labels)) 
width = 1

plt.bar(xs, ys, width, align='center')

plt.xticks(xs, labels) 
plt.yticks(ys)

which gives this error:

ValueError: shape mismatch: objects cannot be broadcast to a single shape

Answer

labels = ['a_train', 'a_test', 'b_train', 'b_test','c_train','c_test']
Positive = [40,         10,        41,      10,       51,       12]
Negative = [75,         19,        75,      19,       75,       19]

x = np.arange(len(labels))
width = 0.30  # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(x - width/2, Positive, width, label='Positive')
rects2 = ax.bar(x + width/2, Negative, width, label='Negative')

ax.set_ylabel('Values')
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()

plt.show()

Result

Image