I have a function that inputs a string (the name of the dataframe we're visualizing) and returns two histograms that visualize that data. The first plot (on the left) is the raw data, the one on the right is it after being normalized (same, just plotted using the matplotlib parameter density=True). But as you can see, this leads to transparency issues when the plots overlap. This is my code for this particular plot:

plt.rcParams["figure.figsize"] = [12, 8]
plt.rcParams["figure.autolayout"] = True

ax0_1 = plt.subplot(121)
_,bins,_ = ax0_1.hist(filtered_0,alpha=1,color='b',bins=15,label='All apples')
ax0_1.hist(filtered_1,alpha=0.9,color='gold',bins=bins,label='Less than two apples')
ax0_1.set_title('Condition 0 vs Condition 1: ' '{}'.format(apple_data),fontsize=14)
ax0_1.set_xlabel('{}'.format(apple_data),fontsize=13)
ax0_1.set_ylabel('Frequency',fontsize=13)
ax0_1.grid(axis='y',linewidth=0.4)
ax0_1.tick_params(axis='x',labelsize=13)
ax0_1.tick_params(axis='y',labelsize=13)


ax0_1_norm = plt.subplot(122)
_,bins,_ = ax0_1_norm.hist(filtered_0,alpha=1,color='b',bins=15,label='All apples',density=True)
ax0_1_norm.hist(filtered_1,alpha=0.9,color='gold',bins=bins,label='Less than two apples',density=True)
ax0_1_norm.set_title('Condition 0 vs Condition 1: ' '{} - Normalized'.format(apple_data),fontsize=14)
ax0_1_norm.set_xlabel('{}'.format(apple_data),fontsize=13)
ax0_1_norm.set_ylabel('Frequency',fontsize=13)
ax0_1_norm.legend(bbox_to_anchor=(2, 0.95)) 
ax0_1_norm.grid(axis='y',linewidth=0.4)
ax0_1_norm.tick_params(axis='x',labelsize=13)
ax0_1_norm.tick_params(axis='y',labelsize=13)
plt.tight_layout(pad=0.5)
plt.show()