Matplotlib bar charts: Aligning two different y ax

I have two sets of data in a barchart which have very different axes: one is very negative (-7500) and one is slightly positive (+5).

How can I have the two y axes aligned at 0, yet still be a good size? Using set_ylim means you can't see the second data set.

Current code I'm using:

A165H = [-4915, -7037]
B167H = [-6927, -4105]
B186H = [-5597, 0]
CH =[0, 0] 
ConH = [0, 0]

# Lists of dS values

A165S = [6.28,-4.91]
B167S = [-3.25, 6.7]
B186S = [3.93, 0]
CS = [0, 0]
ConS = [0, 0]

N1H = [A165H[0], B167H[0], B186H[0], CH[0], ConH[0]]
N1S = [A165S[0], B167S[0], B186S[0], CS[0], ConS[0]]
print(N1H)
print(N1S)

N2H = [A165H[1], B167H[1], B186H[1], CH[1], ConH[1]]
N2S = [A165S[1], B167S[1], B186S[1], CS[1], ConS[1]]


width = 0.35
fig, ax1 = plt.subplots()
ind = np.arange(len(N1H))
rects1 = ax1.bar(ind, N1H, width, color = 'b')
ax1.set_xticks(ind+width)
ax1.set_xticklabels(('A165', 'B167', 'B186', 'C', 'Con'))
ax1.set_ylabel('dH', color='b')
for tl in ax1.get_yticklabels():
    tl.set_color('b')


ax2 = ax1.twinx()
rects2 = ax2.bar(ind + width, N1S, width, color = 'r')
ax2.set_ylabel('dS', color='r')
for tl in ax2.get_yticklabels():
   tl.set_color('r')

plt.show()

Here is my standard image

EDIT:

using the align_yaxis() from this question only shows me the negative values of the second data set:

If I had carried on reading the the other post I would have found the adjust_yaxis which solved my problem

The code given on that answer:

def align_yaxis(ax1, v1, ax2, v2):
"""adjust ax2 ylimit so that v2 in ax2 is aligned to v1 in ax1"""
_, y1 = ax1.transData.transform((0, v1))
_, y2 = ax2.transData.transform((0, v2))
adjust_yaxis(ax2,(y1-y2)/2,v2)
adjust_yaxis(ax1,(y2-y1)/2,v1)

def adjust_yaxis(ax,ydif,v):
    """shift axis ax by ydiff, maintaining point v at the same location"""
    inv = ax.transData.inverted()
    _, dy = inv.transform((0, 0)) - inv.transform((0, ydif))
    miny, maxy = ax.get_ylim()
    miny, maxy = miny - v, maxy - v
    if -miny>maxy or (-miny==maxy and dy > 0):
        nminy = miny
        nmaxy = miny*(maxy+dy)/(miny+dy)
    else:
        nmaxy = maxy
        nminy = maxy*(miny+dy)/(maxy+dy)
    ax.set_ylim(nminy+v, nmaxy+v)