如何从“单元"获取值. “分组依据"目的? [英] How to get values from a "cell" of a "groupby" object?

问题描述

假设我具有以下数据框:

Assume that I have the following data frame:

     A    B  C   D
0  foo  one  1  10
1  bar  one  2  20
2  foo  two  3  30
3  bar  one  4  40
4  foo  two  5  50
5  bar  two  6  60
6  foo  one  7  70
7  foo  two  8  80

现在我可以按第一列进行分组:grouped = df.groupby('A').结果，我得到以下DataFrameGroupBy对象:

Now I can group by the first column: grouped = df.groupby('A'). As a result I get the following DataFrameGroupBy object:

     A            B                 C              D
0  foo  [one,two,two,one,two]  [1,3,5,7,8]  [10,30,50,70,80]
1  bar  [one,one,two]          [2,4,6]      [20,40,60]

现在，我想从特定单元格访问值.我该怎么做?例如，我想从列'D'和'A'=='foo'行(第一行)中获取值.换句话说，我想获取[10,30,50,70,80].有可能吗?

Now I would like to access the values from a particular cell. How can I do it? For example I want to get the values from the column 'D' and the row where 'A'=='foo' (the first row). In other words I want to get [10,30,50,70,80]. Is it possible?

推荐答案

您是否正在考虑这样的事情?

Are you thinking of something like this?

>>> df
     A    B  C   D
0  foo  one  1  10
1  bar  one  2  20
2  foo  two  3  30
3  bar  one  4  40
4  foo  two  5  50
5  bar  two  6  60
6  foo  one  7  70
7  foo  two  8  80
>>> df.groupby("A").get_group("foo")["D"]
0    10
2    30
4    50
6    70
7    80
Name: D
>>> df.groupby("A").get_group("foo")["D"].tolist()
[10, 30, 50, 70, 80]

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