豆瓣电影top250国家分布可视化
时间: 2023-09-01 11:12:58 浏览: 232
好的,我推荐使用Python中的数据分析库pandas和可视化库matplotlib来完成这个任务。以下是大致的步骤:
1. 从豆瓣电影Top250页面爬取数据,并将数据存储为CSV格式;
2. 使用pandas读取CSV文件,进行数据清洗和处理,统计各个国家的电影数量;
3. 使用matplotlib绘制条形图或者饼图来展示各个国家的电影数量。
你需要具备一定的Python编程基础和网络爬虫知识。以下是参考代码:
```python
import pandas as pd
import matplotlib.pyplot as plt
# 读取CSV文件
df = pd.read_csv('douban_top250.csv')
# 数据清洗和处理
df['country'] = df['info'].str.extract('\/\s(.+?)\s\/', expand=False)
df['country'] = df['country'].apply(lambda x: x.split('/')[0])
country_counts = df['country'].value_counts()
# 绘制条形图
plt.bar(country_counts.index, country_counts.values)
plt.xticks(rotation=45)
plt.xlabel('Country')
plt.ylabel('Number of Movies')
plt.title('Distribution of Douban Top250 Movies by Country')
plt.show()
# 绘制饼图
plt.pie(country_counts.values, labels=country_counts.index, autopct='%1.1f%%')
plt.axis('equal')
plt.title('Distribution of Douban Top250 Movies by Country')
plt.show()
```
这段代码做了以下几件事情:
1. 使用pandas的read_csv函数读取CSV文件,并将电影信息中的国家提取出来,存储到新的列`country`中;
2. 使用`value_counts()`函数统计各个国家的电影数量;
3. 绘制条形图和饼图来展示各个国家的电影数量。
注意:上述代码只是一个简单的示例,实际的项目中还需要考虑更多的数据清洗和处理工作,例如处理缺失值、异常值等。
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