如何在 Pandas 中创建多索引

How to create a multi-index in Pandas

提问by Ray

Question

题

There are two questions that look similar but they're not the same question: hereand here. They both call a method of GroupBy, such as count()or aggregate(), which I know returns a DataFrame. What I'm asking is how to convert the GroupBy(class pandas.core.groupby.DataFrameGroupBy) object itself into a DataFrame. I'll illustrate below.

有两个问题看起来很相似，但它们不是同一个问题：here和here。它们都调用 的方法GroupBy，例如count()or aggregate()，我知道它返回一个DataFrame. 我要问的是如何将GroupBy（类pandas.core.groupby.DataFrameGroupBy）对象本身转换为DataFrame. 下面我来举例说明。

Example

例子

Construct an example DataFrameas follows.

构造一个例子DataFrame如下。

data_list = []
for name in ["sasha", "asa"]:
    for take in ["one", "two"]:
        row = {"name": name, "take": take, "score": numpy.random.rand(), "ping": numpy.random.randint(10, 100)}
        data_list.append(row)
data = pandas.DataFrame(data_list)

The above DataFrameshould look like the following (with different numbers obviously).

上面DataFrame应该如下所示（显然数字不同）。

    name  ping     score take
0  sasha    72  0.923263  one
1  sasha    14  0.724720  two
2    asa    76  0.774320  one
3    asa    71  0.128721  two

What I want to do is to group by the columns "name" and "take" (in that order), so that I can get a DataFrameindexed by the multiindex constructed from the columns "name" and "take", like below.

我想要做的是按列“name”和“take”（按该顺序）进行分组，这样我就可以获得DataFrame由“name”和“take”列构造的多索引索引，如下所示。

               score  ping
 name take        
sasha  one  0.923263    72
       two  0.724720    14
  asa  one  0.774320    76
       two  0.128721    71

How do I achieve that? If I do grouped = data.groupby(["name", "take"]), then groupedis a pandas.core.groupby.DataFrameGroupByinstance. What is the correct way of doing this?

我如何做到这一点？如果我这样做grouped = data.groupby(["name", "take"])，那么grouped就是一个pandas.core.groupby.DataFrameGroupBy实例。这样做的正确方法是什么？

回答by jezrael

You need set_index:

你需要set_index：

data = data.set_index(['name','take'])
print (data)
            ping     score
name  take                
sasha one     46  0.509177
      two     77  0.828984
asa   one     51  0.637451
      two     51  0.658616