Pandas 链索引的替代方法是什么? [英] What's the alternative to pandas chain indexing?

问题描述

我正在参加一个在线课程来学习 Python，并且讲师告诉我们链索引不是一个好主意.然而，他没有说出合适的替代品是什么.

I'm taking an online class to learn python and the instructor taught us that chain indexing was not a good idea. However, he failed to tell is the appropriate alternative to use.

假设我有一个 Pandas 数据框，其行索引为 ['1', '2', '3']，列的名称为 ['a', 'b','c'].

Suppose I have a Pandas data frame with rows indexed as ['1', '2', '3'] and columns with names ['a', 'b', 'c'].

使用命令 df['1']['a'] 提取在第一行和第一列中找到的值的合适替代方法是什么?

What's the appropriate alternative to using the command df['1']['a'] to extract the value found in the first row and first column?

推荐答案

使用 多轴索引，例如

df.loc['a', '1']

当您使用 df['1']['a'] 时，您首先访问系列对象 s = df['1']，然后访问系列元素s['a']，导致两个__getitem__调用，这两个调用都严重过载(处理很多场景，比如切片，布尔掩码索引，等等).

When you use df['1']['a'], you are first accessing the series object s = df['1'], and then accessing the series element s['a'], resulting in two __getitem__ calls, both of which are heavily overloaded (handle a lot of scenarios, like slicing, boolean mask indexing, and so on).

使用 df.loc 索引器效率更高.

It's much more efficient to use the df.loc indexer.

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