Python 带有 bin 计数的 Pandas groupby
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Pandas groupby with bin counts
提问by metersk
I have a DataFrame that looks like this:
我有一个如下所示的 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 |
+----------+---------+-------+
and I would like to transform it to count views that belong to certain bins like this:
我想将其转换为计算属于这样的某些垃圾箱的视图：
+------+------+-------+-------+--------+
| | 1-10 | 11-25 | 25-50 | 51-100 |
+------+------+-------+-------+--------+
| john | 1 | 1 | 1 | 1 |
| jane | 1 | 1 | 1 | 1 |
+------+------+-------+-------+--------+
I tried:
我试过：
bins = [1, 10, 25, 50, 100]
groups = df.groupby(pd.cut(df.views, bins))
groups.username.count()
But it only gives aggregate counts and not counts by user. How can I get bin counts by user?
但它只提供聚合计数而不是用户计数。如何按用户获取垃圾箱计数？
The aggregate counts (using my real data) looks like this:
聚合计数（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
采纳答案by Alex Riley
You could group by both the bins andusername, compute the group sizes and then use unstack():
您可以按 bin和用户名分组，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
