没有任何内置函数可以直接在 pandas 中执行此操作，但是通过获取 的数组集合AxesSubplot，对其进行迭代以检索 matplotlib 补丁，您可以获得所需的结果。

以下是一些可以使用的虚拟数据：

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(low=0, high=3, size=(1000,16)))

现在，这里的魔法：

import matplotlib.pyplot as plt

# Plot and retrieve the axes
axes = df.hist(figsize=(12,6), sharex=True, sharey=True)

# Define a different color for the first three bars
colors = ["#e74c3c", "#2ecc71", "#3498db"]

for i, ax in enumerate(axes.reshape(-1)):
    # Define a counter to ensure that if we have more than three bars with a value,
    # we don't try to access out-of-range element in colors
    k = 0

    # Optional: remove grid, and top and right spines
    ax.grid(False)
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)

    for rect in ax.patches:
        # If there's a value in the rect and we have defined a color
        if rect.get_height() > 0 and k < len(colors):
            # Set the color
            rect.set_color(colors[k])
            # Increment the counter
            k += 1

plt.show()

就我而言，我想根据 x 轴更改 bin 的颜色。与 Julien Marrec 的回答一起，这可以通过rect.get_x().

ax = df.Confidence.plot.hist(bins=25, rwidth=0.7)

for rect in ax.patches:
    if rect.get_x() >= 0.5:
        rect.set_color('#55a868')