Plotting data with arbitrary center and x axis positive in both directions - python-3.x

Question

I’m writing a paper and I have data showing structural changes in my molecule. Those structural changes are inverting the d orbital arrangements.
To show a gradual inversion I’d like to plot a graphic showing the perfect structure (all bonds = 2.1) as the center of my x-axis and to the left what happens to the orbitals if I gradually change two bonds from 2.1 to 2.2. To the right the axis is, also, positive, starting from the center 2.1 and going to 2.2 (but showing what happens with a change to only one bond).
Here is a drawing to clarify my intention:
So far, the best that I could achieve is this:
plt.figure(figsize=(9, 8))
dxy = sns.stripplot(x="Bond", y="Energy(cm-1)", data=dfbd, jitter=False, dodge=False, size=44, marker="_", linewidth=2, hue="Orbital")
plt.ylabel("Energy (Eh)")
If you want to give it a try or have any insights on how to achieve this I'll be extremely grateful.
Here is the data in CSV:
,Type,Bond,Orbital,Energy(cm-1)
0,D4h,2.1,dyz,0.0
1,D4h,2.1,dyz,1.2
2,D4h,2.1,dxz,6.0
3,D4h,2.1,dx2-y2,6473.1
4,D4h,2.1,dz2,6491.1
5,D4h,2.12,dxz,0.0
6,D4h,2.12,dyz,62.9
7,D4h,2.12,dxy,84.3
8,D4h,2.12,dz2,6233.7
9,D4h,2.12,dx2-y2,6560.8
10,D4h,2.14,dxz,0.0
11,D4h,2.14,dyz,125.9
12,D4h,2.14,dxy,171.2
13,D4h,2.14,dz2,5992.8
14,D4h,2.14,dx2-y2,6650.5
15,D4h,2.16,dxz,0.0
16,D4h,2.16,dyz,184.7
17,D4h,2.16,dxy,254.8
18,D4h,2.16,dz2,5761.5
19,D4h,2.16,dx2-y2,6736.9
20,D4h,2.18,dxz,0.0
21,D4h,2.18,dyz,239.4
22,D4h,2.18,dxy,335.4
23,D4h,2.18,dz2,5539.6
24,D4h,2.18,dx2-y2,6820.6
25,D4h,2.2,dxz,0.0
26,D4h,2.2,dyz,290.4
27,D4h,2.2,dxy,413.0
28,D4h,2.2,dz2,5327.0
29,D4h,2.2,dx2-y2,6901.5
30,D4h*,2.1,dyz,0.0
31,D4h*,2.1,dyz,1.2
32,D4h*,2.1,dxz,6.0
33,D4h*,2.1,dx2-y2,6473.1
34,D4h*,2.1,dz2,6491.1
35,D4h*,2.12,dxz,0.0
36,D4h*,2.12,dyz,29.0
37,D4h*,2.12,dxy,39.1
38,D4h*,2.12,dz2,6359.1
39,D4h*,2.12,dx2-y2,6514.3
40,D4h*,2.14,dxz,0.0
41,D4h*,2.14,dyz,60.6
42,D4h*,2.14,dxy,82.5
43,D4h*,2.14,dz2,6239.0
44,D4h*,2.14,dx2-y2,6559.1
45,D4h*,2.16,dxz,0.0
46,D4h*,2.16,dyz,90.0
47,D4h*,2.16,dxy,124.3
48,D4h*,2.16,dz2,6123.8
49,D4h*,2.16,dx2-y2,6602.2
50,D4h*,2.18,dxz,0.0
51,D4h*,2.18,dyz,117.3
52,D4h*,2.18,dxy,164.5
53,D4h*,2.18,dz2,6013.3
54,D4h*,2.18,dx2-y2,6643.9
55,D4h*,2.2,dxz,0.0
56,D4h*,2.2,dyz,142.9
57,D4h*,2.2,dxy,203.2
58,D4h*,2.2,dz2,5907.6
59,D4h*,2.2,dx2-y2,6684.2

Answer 1

Following #ImportanceOfBeingErnest's comment, I would tend to go for the "fake axis" route, as it avoids mucking around with several axes, several labels, legends, etc...
df.loc[:,'fake_Bond'] = df.Bond
df.loc[df.Type=='D4h', 'fake_Bond'] = 2.0 + abs(df.loc[df.Type=='D4h', 'Bond'] - 2.2)
plt.figure(figsize=(9, 8))
dxy = sns.stripplot(x="fake_Bond", y="Energy(cm-1)", data=df, jitter=False, dodge=False, size=44, marker="_", linewidth=2, hue="Orbital")
plt.ylabel("Energy (Eh)")
dxy.set_xticklabels(np.concatenate([np.linspace(2.2,2.1,6),np.linspace(2.12,2.2,5)]))
dxy.set_xlabel("D4h $\longleftarrow$ Bond $\longrightarrow$ D4h*")