matplotlib Plotting smooth line with nans

[mikisDeWitte]

Hello,

I want to automate a chart (we call it snake charts, screenshot below) that so far we've been building in Excel.
It's a scatter plot with smoothed lines in between where the y-values are just rankings (1-2-3-4...) so that we can determine the order of the attributes.
It turns out that snake charts are not conventional (apparantly we made this thing up?) and I can't figure out how to smooth the line, knowing that we have nan's in the list.
My chart is ready, except for the lines between the dots, those should be smoothed if they can be (if they're connecting more than 2 dots)

I've read a lot of options on how to smooth lines, including that I should "mask" nan's
here: https://stackoverflow.com/questions/5283...ith-pyplot
and here: https://www.adamsmith.haus/python/answer...-in-python
and here: https://www.geeksforgeeks.org/how-to-plo...atplotlib/
and here: https://matplotlib.org/devdocs/gallery/l..._demo.html

...but none of those options seem to be able to solve my issue. Does anyone know how I can do this?
Note: in practice I can have 5 values, then a nan, and then 5 more values. So I can't simply skip the first nan.

import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import pandas as pd
import numpy as np 

data = pd.DataFrame({"brand": ["a", "a", "a", "a", "b", "b", "b", "b"],
                     "attribute": ["attr1", "attr2", "attr3", "attr4", "attr1", "attr2", "attr3", "attr4"],
                     "score": [np.nan, 0.55, 0.25, 0.15, 0.26, 0.45, 0.20, 0.15],
                     "order": [1, 2, 3, 4, 1, 2, 3, 4]})

colours= pd.DataFrame({"brand": ["a", "b"], "hex_color": ["#859F84", "#F57921"]})

element_column = "brand"
elements = data[element_column].unique().tolist()

for element in elements:
    x = data.loc[data[element_column] == element, "score"]
    y = data.loc[data[element_column] == element, "order"]
    colour = colours.loc[colours[element_column] == element, "hex_color"].item()    
    y = np.ma.masked_where(np.isnan(y), y)
    plt.scatter(x, y, c=colour)
    plt.plot(x, y, c=colour)

labels = data[['attribute', 'order']].drop_duplicates().copy()
plt.yticks(labels["order"], labels["attribute"])
plt.show()

What I want: