[FIXED] Bar and line plot of the same color and line is behind the bars

Issue

I want to have a bar plot and a line plot on the same axis. The line plot should be above the bars, colors should cycle as would be expected with two consecutive calls to plt.plot().

import matplotlib.pyplot as plt
import math

if __name__ == "__main__":
    xs = range(1,10)
    data = [0.3, 0.2, 0.1, 0.05, 0.05, 0.11, 0.09, 0.05, 0.07]
    benfords = [math.log10(float(d + 1)/d) for d in xs]

    plt.bar(xs, data, ec='black', label='Data1')
    plt.plot(xs, benfords, linestyle='--', marker='o', label="Benford's")

    plt.xlabel('Digit')
    plt.ylabel('Frequency')

    plt.legend()
    plt.show()

This code generates this:

Also adding zorder=1 and zorder=2 (or with any two consecutive numbers like 3 and 4 etc.) doesn't help. When bar is replaced with plot two line plot of different colors appear as expected.

Python version: 2.7.8 Matplotlib version: 2.2.5 OS: Windows 10 x64

Solution

This answer is a follow-up to a comment by the OP

Why doesn't it cycle further by the prop_cycler?

The reason why is, even if the prop_cycle is loosely defined as a property of the axes (you retrieve it using plt.rcParams['axes.prop_cycle']), in reality the axes.bar method and the axes.plot method, during initialization, instantiate separate copies of the cycler so, by default (as Matplotlib 3.4), the bars and the lines both start from blue

In [15]: fig, ax = plt.subplots()
    ...: ax.bar((1,2,3), (5,4,6), label='b1')
    ...: ax.bar((1,2,3), (2,3,2), label='b2')
    ...: ax.plot((1,2,3),(9,6,8), label='l1')
    ...: ax.plot((1,2,3),(6,8,7), label='l2')
    ...: plt.legend()
    ...: plt.show()

Of course you can explicitly specify the color of each different set of bars, or of each line, but if you want to mix in the same axes bars and lines whose colors (and optionally other properties) obey a single, shared cycle, you must instantiate an appropriate itertools.cycle object by calling the axes prop_cycle

In [16]: fig, ax = plt.subplots()
    ...: pc = plt.rcParams['axes.prop_cycle']() # we CALL the prop_cycle
    ...: npc = lambda: next(pc)
    ...: ax.bar((1,2,3), (5,4,6), label='b1', **npc())
    ...: ax.bar((1,2,3), (2,3,2), label='b2', **npc())
    ...: ax.plot((1,2,3),(9,6,8), label='l1', **npc())
    ...: ax.plot((1,2,3),(6,8,7), label='l2', **npc())
    ...: plt.legend()
    ...: plt.show()

Answered By - gboffi