如何在Pandas中按条件高亮两行：B列含a的行及对应ID行

需求说明 #

• 高亮DataFrame中B列所有值为"a"的单元格
• 当B列某行被高亮时，对应行的ID列单元格也需同步高亮

原实现代码（仅满足条件1） #

import pandas as pd
import numpy as np
data = {'ID':[1,2,3,4,5,6,7,8,9,10],
        'B':["a","b","c","a","e","f","a","h","c","a"],
        'C': [5,7,8,9,12,3,60,55,20,14]
       }
df = pd.DataFrame(data=data)
(df
    .style
    .apply(lambda x: np.where(x == "a", 'background-color : red', ''),axis=1, 
     subset=["B"])
)

优化后代码（满足两个条件） #

方案一：简洁版 #

直接指定联动列范围，通过行级判断实现同步高亮：

import pandas as pd
import numpy as np

data = {'ID':[1,2,3,4,5,6,7,8,9,10],
        'B':["a","b","c","a","e","f","a","h","c","a"],
        'C': [5,7,8,9,12,3,60,55,20,14]
       }
df = pd.DataFrame(data=data)

(df
 .style
 .apply(lambda row: ['background-color: red' if row['B'] == 'a' else '' for _ in row],
        axis=1, subset=['ID', 'B'])
)

方案二：灵活扩展版 #

适合后续需要新增更多联动列的场景，维护性更强：

import pandas as pd
import numpy as np

data = {'ID':[1,2,3,4,5,6,7,8,9,10],
        'B':["a","b","c","a","e","f","a","h","c","a"],
        'C': [5,7,8,9,12,3,60,55,20,14]
       }
df = pd.DataFrame(data=data)

def highlight_linked_cols(df):
    # 筛选出B列为"a"的行掩码
    highlight_mask = df['B'] == 'a'
    # 初始化空样式矩阵
    style_matrix = pd.DataFrame('', index=df.index, columns=df.columns)
    # 为目标行的指定列设置高亮样式
    style_matrix.loc[highlight_mask, ['ID', 'B']] = 'background-color: red'
    return style_matrix

df.style.apply(highlight_linked_cols, axis=None)

实现逻辑说明 #

• 方案一：逐行判断B列值，若符合条件则给当前行的ID、B列统一添加红色背景样式
• 方案二：先生成全行样式模板，再通过掩码精准定位需要高亮的行和列，批量设置样式，便于后续扩展联动列范围

内容的提问来源于stack exchange，提问作者Hansson