如何从Pandas DataFrame的每一行中选择特定的列? [英] How can I select a specific column from each row in a Pandas DataFrame?

问题描述

我有一个采用以下格式的DataFrame:

I have a DataFrame in this format:

    a   b   c
0   1   2   3
1   4   5   6
2   7   8   9
3   10  11  12
4   13  14  15

和类似这样的数组，其列名称为:

and an array like this, with column names:

['a', 'a', 'b', 'c', 'b']

，我希望提取数据数组，每行一个值.列名称数组指定我要从每一行中选择哪一列.在这里，结果将是:

and I’m hoping to extract an array of data, one value from each row. The array of column names specifies which column I want from each row. Here, the result would be:

[1, 4, 8, 12, 14]

这是否可以作为对Pandas的单个命令，还是需要迭代?我尝试使用索引

Is this possible as a single command with Pandas, or do I need to iterate? I tried using indexing

i = pd.Index(['a', 'a', 'b', 'c', 'b'])
i.choose(df)

但是我遇到了段错误，由于缺少文档，所以无法诊断.

but I got a segfault, which I couldn’t diagnose because the documentation is lacking.

推荐答案

您可以使用

You could use lookup, e.g.

>>> i = pd.Series(['a', 'a', 'b', 'c', 'b'])
>>> df.lookup(i.index, i.values)
array([ 1,  4,  8, 12, 14])

如果需要，其中i.index可能与range(len(i))不同.

where i.index could be different from range(len(i)) if you wanted.

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