I think a consistent way that will easily work for most cases, without having to worry about what is the distribution range for each of your datasets, will be to put the datasets together into a big one, determine the bins edges and then plot:
a=np.random.random(100)*0.5 #a uniform distribution
b=1-np.random.normal(size=100)*0.1 #a normal distribution
bins=np.histogram(np.hstack((a,b)), bins=40)[1] #get the bin edges
plt.hist(a, bins)
plt.hist(b, bins)
