Suggestion for getting a type of plot

Question

I am planning to use python to get a plot like this .

But, I am only able to get this,

So, I would appreciate it if someone helps me with these issues, (Maybe how to format the data)

1. How to have lower X-axis values highlighted like in the original plot

2. Also, how to add the info to the legends. Please check the code below and looking forward to your suggestions. Numpy and Matplotlib are being used.

   x = [192, 188/4, 168/24, 144/48, 96/96]
   ys = [[2.20, 0.758, 0.691], [1.44, 0.708, 0.733], [0.491, 0.379, 0.440], [0.349, 0.350, 0.165], [0.199, 0.157, 0.163]]
   
   print(len(x), len(ys))
   colors = [["r", "y", "g"], ["r", "y", "g"], ["r", "y", "g"], ["r", "y", "g"], ["r", "y", "g"]]
   print(colors)
   
   for y, x, c in zip(ys, x, colors):
   #     print(y, [x])
   #     print([x]*len(y))
       plt.scatter([x]*len(y), y, color = c)    
   
   
   plt.xticks([192, 188/4, 168/24, 144/48, 96/96])
   plt.xlabel("Si/Al Ratio")
   plt.ylabel("Diff Coeff (Ang**2)")
   # plt.legend(['Water_Cubic{}'.format(i) for i in [12, 24, 48]], loc=2, bbox_to_anchor=(1.05, 1), borderaxespad=0., fontsize=11)
   plt.title("Si/Al vs Diff Coeff at 300k for Water Content (12, 24, 48)")
   

Answer 1

Charged you code a bit to hopefully get you closer:

import numpy as np

X = [192, 188/4, 168/24, 144/48, 96/96]
Ys = [[2.20, 0.758, 0.691], [1.44, 0.708, 0.733], [0.491, 0.379, 0.440], [0.349, 0.350, 0.165], [0.199, 0.157, 0.163]]
colors = ['r','y','g']

# convert to 2D numpy array
Ys_ = np.asarray(Ys).T

for i, y in enumerate(Ys_):
    plt.scatter(X, y, color=colors[i])    


plt.xticks([192, 188/4, 168/24, 144/48, 96/96])
plt.xlabel("Si/Al Ratio")
plt.ylabel("Diff Coeff (Ang**2)")
# plt.legend(['Water_Cubic{}'.format(i) for i in [12, 24, 48]], loc=2, bbox_to_anchor=(1.05, 1), borderaxespad=0., fontsize=11)
plt.title("Si/Al vs Diff Coeff at 300k for Water Content (12, 24, 48)")