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