如何在Seaborn柱状图中为不同hue分组配置独立调色板

原生Seaborn的barplot的palette参数仅支持按hue类别统一分配颜色，不直接支持x和hue双维度的自定义配色，可通过以下两种方案实现需求：

最优方案：单次调用barplot实现 #

保留Seaborn原生分组错位逻辑，调用后手动修改柱子和误差棒颜色，同时自定义图例：

import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.patches import Patch

data = sns.load_dataset('attention')

# 按柱子绘制顺序定义颜色：solutions=1的divided、focused → solutions=2的divided、focused...
color_order = ["darkred", "red", "darkgreen", "green", "darkblue", "blue"]
# 每个柱子对应1条误差竖线、2个端帽，共3个line对象，复制颜色顺序匹配
err_color_order = [c for c in color_order for _ in range(3)]

sns.set(style='ticks', context='notebook', font_scale=1.2)
fig, ax = plt.subplots(figsize=(7, 5), dpi=96)

# 基础调用barplot，固定hue顺序保证柱子顺序和我们定义的颜色一致
sns.barplot(
    x="solutions", y="score", hue="attention",
    hue_order=["divided", "focused"],
    capsize=.1, ax=ax, data=data
)

# 修改柱子填充色
for patch, color in zip(ax.patches, color_order):
    patch.set_facecolor(color)

# 修改误差棒颜色
for line, color in zip(ax.lines, err_color_order):
    line.set_color(color)

# 自定义符合需求的图例
legend_elements = [
    Patch(facecolor='dimgray', label='divided'),
    Patch(facecolor='lightgray', label='focused')
]
ax.legend(handles=legend_elements, title='attention')

sns.despine(top=True, right=True)
plt.tight_layout()
plt.show()

次优方案：多次调用barplot实现 #

手动控制柱子偏移避免重叠，添加label参数自动生成图例：

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

data = sns.load_dataset('attention')

bar_width = 0.35  # 单组柱子宽度，两组总宽度小于1保留间距
base_x = np.arange(3)  # solutions三个取值的基准x坐标

sns.set(style='ticks', context='notebook', font_scale=1.5)
fig, ax = plt.subplots(figsize=(7, 5), dpi=96)

# 绘制divided分组，向左偏移半个宽度
sns.barplot(
    x=base_x - bar_width/2, y="score",
    palette=['darkred', 'darkgreen', 'darkblue'], 
    capsize=.1, ax=ax, width=bar_width,
    data=data.query('attention=="divided"'),
    label='divided'
)
# 绘制focused分组，向右偏移半个宽度
sns.barplot(
    x=base_x + bar_width/2, y="score",
    palette=['red', 'green', 'blue'], 
    capsize=.1, ax=ax, width=bar_width,
    data=data.query('attention=="focused"'),
    label='focused'
)

# 还原x轴标签为solutions取值
ax.set_xticks(base_x)
ax.set_xticklabels([1,2,3])
ax.set_xlabel('solutions')

ax.legend(title='attention')
sns.despine(top=True, right=True)
plt.tight_layout()
plt.show()

内容的提问来源于stack exchange，提问作者TSeymour