November 2023
Intermediate to advanced
512 pages
11h 53m
Chinese
Content preview from 利用 Python 进行数据分析：原书第 3 版
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296
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第
10
章
10.1 GroupBy
机制
Hadley Wickham
（
R
语言中许多热门包的作者）创造了一个用于描述分组运算的术语“拆
分-应用-联合”（
split-apply-combine
）。首先，
pandas
对象（无论是
Series
、
DataFrame
还是其他）中的数据会根据你所提供的单键或多键拆分为多组。拆分操作是在对象的特
定轴上执行的。例如，
DataFrame
可以在其行（axis="index"）或列（axis="columns"）
上进行分组。其次，将一个函数应用到各个分组，并产生一个新值。最后，所有这些函
数的执行结果会联合为最终的结果对象。结果对象的形式一般取决于对数据所执行的操
作。图
10-1
对简单的聚合过程做了大致说明。
图 10-1：分组聚合图示
每个分组键可以有多种形式，并且类型不必相同：
·
值列表或值数组，其长度与待分组的轴一样。
·
在 DataFrame 中指明列名的值。
·
字典或 Series，给出待分组轴上的值与分组名之间的对应关系。
·
可以在轴索引或索引各标签上调用的函数。
注意，后三种都是快捷方式，用于产生一组用于拆分对象的值数组。如果觉得它们看起
来很抽象，也不用担心，本章将给出与这些方法有关的大量示例。首先来看下面这个
数据聚合与分组操作
|
297
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