Question

我有一个如下所示的DataFrame：

    age  gender  count
0    10  Female      1
1    10    Male      1
2    12  Female      2
3    13  Female      3
4    13    Male      2
5    14  Female      1
6    14    Male     10
7    15  Female      9
8    15    Male     12
9    16  Female      8
10   16    Male     24
11   17  Female      7
12   17    Male     16
13   18  Female      6
14   18    Male      3
15   19  Female      2
16   19    Male      1
17   20    Male      1
18   21  Female      1
19   22    Male      2
20   23    Male      1

我想将一些年龄聚集在一起。像这样：

    age     gender  count
0    10     Female      1
1    10       Male      1
2    12     Female      2
3    13     Female      3
4    13       Male      2
5    14     Female      1
6    14       Male     10
7    15     Female      9
8    15       Male     12
9    16     Female      8
10   16       Male     24
11   17-19  Female     15
12   17-19    Male     20
17   20-23    Male      4
18   20-23  Female      1

到目前为止，我已经制作了垃圾箱，然后用pd.cut对它们进行了攻击（？这里的正确用语），然后对它们进行分组，如下所示：

bins = np.array([8,9,10,11,12,13,14,15,16,17,20,25,30...]) #these bins don't reflect the example I provided
groups = df.groupby(pd.cut(df.age, bins))

但是，我无法从这些组中提取正确的数据框，我觉得它很接近，但我不知道如何继续。当我groups.first()和groups.last()时，我可以看到我想要的信息就在那里，只是模糊不清。有什么建议吗？

Answer 1

您想要groupby性别以及年龄段。使用sum汇总并删除空行（dropna）以获得所需内容。

groups = df.groupby((pd.cut(df.age, bins), 'gender'))
output = groups.sum().dropna()

Python Pandas：将我的索引聚合到一个年龄范围

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