如何在pandas的df.plot.barh水平堆叠条形图中高亮最大数值条

你可以在生成条形图之后遍历每一个条形块对象，判断其数值是否为全局最大占比，仅保留最大值条形的原有配色，其余全部改为灰色即可，修改后的完整代码如下：

import matplotlib.pyplot as mpl
import matplotlib.cm as mcm
import pandas as pd
import numpy as np
from typing import List, Tuple

def read_to_df(file_path: str) -> pd.DataFrame:
    return pd.read_excel(file_path, index_col = 0)

def color_to_hex(color: Tuple[float]) -> str:
    color = [i * 255 if i * 255 <= 255 else i * 255 - 1
             for i in color[:-1]]
    color = [int(round(i)) for i in color]
    return "#%02x%02x%02x" % tuple(color)

def cmap_to_colors(cmap: str,
                   amount: int) -> List[str]:
    cmap = mcm.get_cmap(cmap)
    colors = [color_to_hex(cmap(i))
              for i in np.linspace(0, 1, amount)]
    return colors

def main() -> None:
    df = read_to_df("age_dist_median_six.xlsx")
    df_age_only = df.drop(["median", "youngest", "oldest"], axis = 1)
    # 翻转 dataframe 行顺序匹配绘图顺序
    df_age_only = df_age_only.iloc[::-1]
    # 生成原配色方案
    colors = cmap_to_colors("viridis", 6)
    barh = df_age_only.plot.barh(stacked = True, color = colors,
                                 width = 0.95, xticks = np.linspace(0, 100, 11),
                                 figsize = (10, 15))
    # -----------------新增高亮逻辑开始-----------------
    # 计算所有年龄占比的全局最大值
    max_ratio = df_age_only.max().max()
    # 按patch排列顺序展开所有数值（pandas堆叠条形的patch按列优先排列）
    all_ratios = df_age_only.values.T.flatten()
    # 遍历修改颜色
    for patch, ratio in zip(barh.patches, all_ratios):
        if ratio != max_ratio:
            # 非最大值条形统一设为灰色
            patch.set_facecolor('#999999')
    # -----------------新增高亮逻辑结束-----------------
    barh.legend(bbox_to_anchor=(1, 1))
    barh.margins(x = 0)
    mpl.savefig("stacked_six_viridis_highlight.png")

if __name__ == "__main__":
    main()

如果你需要按每支队伍内部的最大占比单独高亮，只需要把全局最大值的计算逻辑替换为按行取最大值即可。

内容的提问来源于stack exchange，提问作者Gleb Ryabov