diff --git a/DataAnalysis1.py b/DataAnalysis1.py
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index 0000000..e263647
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+++ b/DataAnalysis1.py
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+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+
+# 加载数据
+df = pd.read_csv('/mnt/豆瓣电影_20250510_173909.csv')
+
+# 将主演列中的空值填充为空字符串
+df['主演'] = df['主演'].fillna('')
+
+# 将主演列按斜杠分割并展开为新的行
+actors = df['主演'].str.split(' / ').explode()
+
+# 使用NumPy统计不同演员的参演数量
+unique_actors, counts = np.unique(actors, return_counts=True)
+
+# 创建DataFrame并排序
+actor_df = pd.DataFrame({'actor': unique_actors, 'count': counts})
+top_ten = actor_df.sort_values('count', ascending=False).head(10)
+
+# 准备饼图数据
+labels = top_ten['actor']
+sizes = top_ten['count']
+
+# 设置图片清晰度
+plt.rcParams['figure.dpi'] = 300
+
+# 设置中文字体
+plt.rcParams['font.sans-serif'] = ['WenQuanYi Zen Hei']
+
+# 绘制饼图
+plt.figure(figsize=(10, 8))
+plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90, pctdistance=0.85)
+
+# 画一个白色的圆在中间，使饼图成为环形图
+centre_circle = plt.Circle((0, 0), 0.70, fc='white')
+fig = plt.gcf()
+fig.gca().add_artist(centre_circle)
+
+# 设置标题
+plt.title('演员参演数量前十名占比', fontsize=14)
+
+# 确保饼图是圆形
+plt.axis('equal')
+plt.tight_layout()
+plt.show()
+
+# 打印统计结果
+print('演员参演数量前十名：')
+for idx, row in top_ten.iterrows():
+    print(f"{row['actor']}: {row['count']}部")
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