From the issue report, this plot works with kine="line". Why do we need all this logic for scatter but it just work for line?

You are right - I was trying to solve the issue as an edge case, on top of the piece that was causing this inconsistency of coloring between ScatterPlot and LinePlot.

The source of the issue is that matplotlib handles ploting both line and scatter plots. Matplotlib has its own way of color-cycling when no color is defined. Here is an example:

plt.plot([1, 2, 3], [1, 2, 3])
plt.plot([4, 5, 6], [4, 5, 6])
plt.plot([7, 8, 9], [7, 8, 9])
# This results in having 3 different colors, one for each of the plots above

Similarly

plt.scatter(0, 0)
plt.scatter(1, 1)
plt.scatter(2, 2)
# This results in having 3 different colors, one for each of the points above

However, the reason for this inconsistency between ScatterPlot and LinePlot behaviours is that LinePlot doesn't pass any color in kwds to ax.plot when calling
df.groupby("layer").plot(x='x', y='y', ax= plt.gca(), kind='line')
While ScatterPlot explicitly defines the c= argument in ax.scatter when calling
df.groupby("layer").plot(x='x', y='y', ax= plt.gca(), kind='scatter')

The solution for the source issue is to set c_values = None when no color is passed to ScatterPlot; When self.c is None and self.color is None