import pandas as pd import matplotlib.pyplot as plt

读取CSV文件

df = pd.read_csv('专家打分.csv', encoding='gbk')

你的数据

clusters = { 'Cluster 0': [12, 15, 17, 24, 30, 35, 38, 40, 41, 43, 44, 47, 53, 54, 62, 63, 69, 70, 71, 72, 76, 78, 79, 80, 83, 84, 87, 89, 97], 'Cluster 1': [11, 13, 16, 18, 19, 22, 26, 34, 57, 61, 67, 73, 74, 85, 86, 91, 94, 96], 'Cluster 2': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14, 20, 21, 23, 25, 27, 28, 29, 31, 32, 33, 36, 37, 39, 42, 45, 46, 48, 49, 50, 51, 52, 55, 56, 58, 59, 60, 64, 65, 66, 68, 75, 77, 81, 82, 88, 90, 92, 93, 95] }

对每个类别选出对应专家序号的行，并绘制直方图

for cluster, data in clusters.items(): for expert_id in data: # 选择对应专家序号的行 selected_row = df[df['专家序号'] == expert_id] # 对每个选中的专家，绘制其所有列的直方图 fig, ax = plt.subplots() selected_row.iloc[0, 1:].dropna().astype(float).hist(ax=ax) # 从第一列开始，去掉空值，转换为浮点数 ax.set_title(f'Expert {expert_id} in {cluster}') plt.xlabel('Score') plt.ylabel('Frequency') plt.savefig(f'Expert_{expert_id}in{cluster}.png') plt.close(fig)