plot 从 pandas dataframe 具有负值和正值

Question

I have a dataframe which looks like this:

MM Initial Energy   MM Initial Angle    QM Energy   QM Angle
0   13.029277   120.0   18.048  120.0
1   11.173115   125.0   15.250  125.0
2   9.411475    130.0   12.668  130.0
3   7.762888    135.0   10.309  135.0
4   6.239025    140.0   8.180   140.0
5   4.853004    145.0   6.286   145.0
6   3.617394    150.0   4.633   150.0
7   2.544760    155.0   3.226   155.0
8   1.646335    160.0   2.070   160.0
9   0.934298    165.0   1.166   165.0
10  0.419003    170.0   0.519   170.0
11  0.105913    175.0   0.130   175.0
12  0.000000    -180.0  0.000   -180.0
13  0.105988    -175.0  0.130   -175.0
14  0.420029    -170.0  0.519   -170.0
15  0.937312    -165.0  1.166   -165.0
16  1.650080    -160.0  2.070   -160.0
17  2.548463    -155.0  3.227   -155.0
18  3.621227    -150.0  4.633   -150.0
19  4.856266    -145.0  6.286   -145.0
20  6.236939    -140.0  8.180   -140.0
21  7.760035    -135.0  10.309  -135.0
22  9.409117    -130.0  12.669  -130.0
23  11.170671   -125.0  15.251  -125.0
24  13.033293   -120.0  18.048  -120.0

I want to plot the data with Angles on the x-axis and energy on the y. This sounds fairly simple, however what happens is that pandas or matplotlib sorts the X-axis values in a such a manner that my plot looks split. This is what it looks like:

However, this is how I want it:

My code is as follows:

df=pd.read_fwf('scan_c1c2c3h31_orig.txt', header=None, prefix='X')

df.rename(columns={'X0':'MM Initial Energy',
                          'X1':'MM Initial Angle',
                          'X2':'QM Energy', 'X3':'QM Angle'}, 
                 inplace=True)

df=df.sort_values(by=['MM Initial Angle'], axis=0, ascending=True)
df=df.reset_index(drop=False)

df2=pd.read_fwf('scan_c1c2c3h31.txt', header=None, prefix='X')
df2.rename(columns={'X0':'MM Energy',
                          'X1':'MM Angle',
                          'X2':'QM Energy', 'X3':'QM Angle'}, 
                 inplace=True)
df2=df2.sort_values(by=['MM Angle'], axis=0, ascending=True)
df2=df2.reset_index(drop=False)
df
df2
ax = plt.axes()

df.plot(y="MM Initial Energy", x="MM Initial Angle", color='red', linestyle='dashed',linewidth=2.0, ax=ax, fontsize=20, legend=True)

df2.plot(y="MM Energy", x="MM Angle", color='red', ax=ax, linewidth=2.0, fontsize=20, legend=True)

df2.plot(y="QM Energy", x="QM Angle", color='blue', ax=ax, linewidth=2.0, fontsize=20, legend=True)

plt.ylim(-0.05, 6)

ax.xaxis.set_major_locator(MultipleLocator(20))
ax.xaxis.set_minor_locator(MultipleLocator(10))
ax.yaxis.set_minor_locator(MultipleLocator(0.5))

plt.xlabel('Angles (Degrees)', fontsize=25)
plt.ylabel('Energy (kcal/mol)', fontsize=25)

What I am doing is, sorting the dataframe by 'MM Angles'/'MM Initial Angles' to avoid plot "scarambling" due to repeating values in the y-axis.The angles vary from -180 to 180, where I want the -180 and +180 next to each other.

I have tried sorting the negative values in ascending order and positive values in descending order as suggested in this post , but I still get the same plot where x axis ranges from -180 to +180. I have also tried matplotlib axis spines to recenter the plot, and I have also tried inverting the x-axis as suggested in this post , but still get the same plot. Additionally, I have also tried suggestion in this another post . Any help will be appreciated.

Answer 1

If you don't need to rescale the plot, I would plot against the positive angles 0-360 and manually re-label the ticks:

fig, ax = plt.subplots()
(df.assign(Angle=df['MM Initial Angle']%360)
   .plot(x='Angle', y=['QM Energy','MM Initial Energy'], ax=ax)
)

ax.xaxis.set_major_locator(MultipleLocator(20))

x_ticks = ax.get_xticks()
x_ticks = [t-360 if t>180 else t for t in x_ticks]
ax.set_xticklabels(x_ticks)
plt.plot()

Output: