import numpy as np
import pandas as pd
from matplotlib.colors import LogNorm, Normalize
from matplotlib.collections import LineCollection
import matplotlib.pyplot as plt
x=np.arange(1, 11)
y=np.arange(1, 11)
z=pd.Series(np.logspace(-5.0, 9, num=10))

points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)

norms = [plt.Normalize(vmin=z.min(), vmax=z.max()),
         LogNorm(vmin=z.min(), vmax=z.max()),
         Normalize(vmin=z.min(), vmax=z.max())]

# the different cases I tried: 
for norm in norms:
    print(f"Trying: {type(norm)}")
    fig, ax = plt.subplots(constrained_layout=True)
    try:
        lc = LineCollection(segments, cmap='viridis', norm=norm)
        
        lc.set_array(z)
        lc.set_linewidth(10)
        line = ax.add_collection(lc)
        fig.colorbar(line, ax=ax)
        
        ax.plot(x, y)
        fig.show()
    except TypeError as e:   
        print(e)
    plt.clf()

# and finally the part that causes the issue: 
norm = LogNorm(vmin=z.min(), vmax=z.max())
fig, ax = plt.subplots(constrained_layout=True)
lc = LineCollection(segments, cmap='viridis', norm=norm)

lc.set_array(z)
lc.set_linewidth(10)
line = ax.add_collection(lc)
fig.colorbar(line, ax=ax)
        
ax.plot(x, y)
fig.show()

import numpy as np
import pandas as pd
from matplotlib.colors import LogNorm, Normalize
from matplotlib.collections import LineCollection
import matplotlib.pyplot as plt
x=np.arange(1, 11)
y=np.arange(1, 11)
### now z is set as an np.array
z=np.logspace(-5.0, 9, num=10)

points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)

norm = LogNorm(vmin=z.min(), vmax=z.max())

fig, ax = plt.subplots(constrained_layout=True)
lc = LineCollection(segments, cmap='viridis', norm=norm)

lc.set_array(z)
lc.set_linewidth(10)
line = ax.add_collection(lc)
fig.colorbar(line, ax=ax)
        
ax.plot(x, y)
fig.show()