Python: Align bars between bin edges for a double histogram

Question

I am having trouble using the pyplot.hist function to plot 2 histograms on the same figure. For each binning interval, I want the 2 bars to be centered between the bins (Python 3.6 user). To illustrate, here is an example:

import numpy as np
from matplotlib import pyplot as plt

bin_width=1

A=10*np.random.random(100)
B=10*np.random.random(100)

bins=np.arange(0,np.round(max(A.max(),B.max())/bin_width)*bin_width+2*bin_width,bin_width)

fig = plt.figure()
ax = fig.add_subplot(111)

ax.hist(A,bins,color='Orange',alpha=0.8,rwidth=0.4,align='mid',label='A')

ax.hist(B,bins,color='Orange',alpha=0.8,rwidth=0.4,align='mid',label='B')

ax.legend()
ax.set_ylabel('Count')

I get this:

Histogram_1

A and B series are overlapping, which is not good. Knowing there are only 3 option for 'align', (centered on left bin, middle of 2 bins, centered on right bin), i see no other options than modifying the bins, by adding:

bins-=0.25*bin_width 

Before plotting A, and adding:

bins+=0.5*bin_width

Before plotting B. That gives me: Histogram

That's better! However, I had to modify the binning, so it is not the same for A and B.

I searched for a simple way to use the same bins, and then shift the 1st and 2nd plot so they are correctly displayed in the binning intervals, but I didn't find it. Any advice?

I hope I explained my problem clearly.

Answer 1

As previously was mentioned in the above comment you do not need a hist plot function. Use numpy histogram function and plot it results with bar function of matplotlib.

According to bins count and count of data types you can calculate bin width. Ticks you may adjust with xticks method:

import numpy as np
import matplotlib.pylab as plt

A=10*np.random.random(100)
B=10*np.random.random(100)

bins=20
# calculate heights and bins for both lists
ahist, abins = np.histogram(A, bins)
bhist, bbins = np.histogram(B, abins)

fig = plt.figure()
ax = fig.add_subplot(111)
# calc bin width for two lists
w = (bbins[1] - bbins[0])/3.
# plot bars
ax.bar(abins[:-1]-w/2.,ahist,width=w,color='r')
ax.bar(bbins[:-1]+w/2.,bhist,width=w,color='orange')
# adjsut xticks
plt.xticks(abins[:-1], np.arange(bins))

plt.show()