Python爬取3万＋条球员记录，看看中国和其它国家的差别！

一直想做一篇和足球数据分析相关的文章，结合python的爬虫和数据分析，这里和大家分享一篇直播吧3万多足球运动的数据分析，数据内容挺多的，只是从其中提取部分进行比较和分析。可视化部分用到的是pyechart。

1、分析直播吧球员数据页面：

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1）从域名看（https://data.zhibo8.cc/html/player.html?player_id=1），player_id这个参数代表了每个球员的编号，这里看了一下，最高编号大概到9万多，中间会有断层。爬虫的基本步骤就是循环获取每个球员页面的数据即可。

2）然后再查看每个球员页面的数据如何获取，一般这类数据都是通过json格式传入的，所以只需要获取该域名的json数据即可。通过右键copy该json的域名是：https://db.qiumibao.com/f/index/player?pid=1，好了，下一步就是直接跑代码了。

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2、运行爬虫代码：

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就短短十几行代码，就把3万+条球员记录存到DataFrame里面：

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注：如果某条记录报错，可以直接从下一条记录再开始运行即可

3、数据分析

3.1 通过年龄分析球员

爬取到的数据有33102条，通过查看这批球员的年龄分布，查看是否都是现役球员。

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通过图表可以发现，球员主要集中在20-30岁之间，非常符合现役职业球员的分布。

当然了，最主要还是看我们中国球员的年龄分布：

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好像有点反规律哦，为什么23岁以下的球员芳儿比23，25的球员多呢？是不是因为U23政策，哈哈。

3.2 哪个国家的球员最多

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排名前15位的国家，令人意外的是日本球员居然排名第五。这个数量只能代表各个国家的顶级联赛职业球员数量，无法代表实际足球人口，这个比较可惜。

3.3 分析球员的进球数据

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其中，梅西598，C罗600，可见梅罗独一档有多恐怖，排名第三的伊布只有428，而且伊布比他们还大好几岁。

3.4 三大球王数据对比

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