import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap, BoundaryNorm, Normalize, LogNorm
import pandas as pd

x = np.linspace(0, 3 * np.pi, 500)
y = np.sin(x)
dydx = np.linspace(0, 3 * np.pi, 500) +1  # first derivative
df= pd.DataFrame({'x':x,'y':y,'dydx':dydx})
points = np.array([df['x'], df['y']]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
fig, axs = plt.subplots()

# Create a continuous norm to map from data points to colors
norm = LogNorm(df['dydx'].min(), df['dydx'].max())
lc = LineCollection(segments, cmap='viridis', norm=norm)
# Set the values used for colormapping
lc.set_array(df['dydx'])
lc.set_linewidth(2)
line = axs.add_collection(lc)
fig.colorbar(line, ax=axs)
axs.set_xlim(x.min(), x.max())
axs.set_ylim(-1.1, 1.1)
plt.show()