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利用 Python 进行数据分析:原书第 3 版
book

利用 Python 进行数据分析:原书第 3 版

by Wes McKinney
November 2023
Intermediate to advanced
512 pages
11h 53m
Chinese
China Machine Press
Content preview from 利用 Python 进行数据分析:原书第 3 版
436
|
13
13-12:对各党派总出资额最高的职业
数据分析案例
|
437
13.5.2
对出资额进行分桶
另一种实用的分析是根据出资额的大小,利用 cut 函数将数据离散化到多个桶中:
现在可以根据候选人姓名以及分箱标签,对
Obama
Romney
的数据进行分组,以得到
资助规模的柱状图:
438
|
13
从这个数据中可以看出,在小额赞助方面,
Obama
获得的数量比
Romney
多得多。你还
可以对出资额求和并在桶内进行标准化,对两位候选人的各个赞助额度的总额百分比进
行可视化(如图
13-13
):
13-13:两位候选人收到的各种捐赠额度的总额比例
数据分析案例
|
439
我排除了两个最大的分箱,因为它们不是由个人赞助的。
还可以通过许多方式对该分析过程做提炼和改进。比如,可以根据赞助人的姓名和邮编 ...
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Publisher Resources

ISBN: 9787111726722