python - 带有 bin 计数的 Pandas groupby

Question

我有一个看起来像这样的 DataFrame：

+----------+---------+-------+
| username | post_id | views |
+----------+---------+-------+
| john     |       1 |     3 |
| john     |       2 |    23 |
| john     |       3 |    44 |
| john     |       4 |    82 |
| jane     |       7 |     5 |
| jane     |       8 |    25 |
| jane     |       9 |    46 |
| jane     |      10 |    56 |
+----------+---------+-------+

我想将其转换为计算属于某些垃圾箱的视图，如下所示：

+------+------+-------+-------+--------+
|      | 1-10 | 11-25 | 25-50 | 51-100 |
+------+------+-------+-------+--------+
| john |    1 |     1 |     1 |      1 |
| jane |    1 |     1 |     1 |      1 |
+------+------+-------+-------+--------+

我试过：

bins = [1, 10, 25, 50, 100]
groups = df.groupby(pd.cut(df.views, bins))
groups.username.count()

但它只给出聚合计数，而不是用户计数。如何按用户获取 bin 计数？

总计数（使用我的真实数据）如下所示：

impressions
(2500, 5000]         2332
(5000, 10000]        1118
(10000, 50000]        570
(50000, 10000000]      14
Name: username, dtype: int64

Answer 1

您可以按 bin和用户名进行分组，计算组大小，然后使用unstack()：

>>> groups = df.groupby(['username', pd.cut(df.views, bins)])
>>> groups.size().unstack()
views     (1, 10]  (10, 25]  (25, 50]  (50, 100]
username
jane            1         1         1          1
john            1         1         1          1