将 bin 应用于 groupby 的 pandas value_counts 产生不正确的结果

Question

我不明白为什么 value_counts 给了我错误的答案。这是一个小例子：

In [81]: d=pd.DataFrame([[0,0],[1,100],[0,100],[2,0],[3,100],[4,100],[4,100],[4,100],[1,100],[3,100]],columns=['key','score'])

In [82]: d
Out[82]:
   key  score
0    0      0
1    1    100
2    0    100
3    2      0
4    3    100
5    4    100
6    4    100
7    4    100
8    1    100
9    3    100

In [83]: g=d.groupby('key')['score']
In [84]: g.value_counts(bins=[0, 20, 40, 60, 80, 100])
Out[84]:
key  score
0    (-0.001, 20.0]    1
     (20.0, 40.0]      1
     (40.0, 60.0]      0
     (60.0, 80.0]      0
     (80.0, 100.0]     0
1    (20.0, 40.0]      2
     (-0.001, 20.0]    0
     (40.0, 60.0]      0
     (60.0, 80.0]      0
     (80.0, 100.0]     0
2    (-0.001, 20.0]    1
     (20.0, 40.0]      0
     (40.0, 60.0]      0
     (60.0, 80.0]      0
     (80.0, 100.0]     0
3    (20.0, 40.0]      2
     (-0.001, 20.0]    0
     (40.0, 60.0]      0
     (60.0, 80.0]      0
     (80.0, 100.0]     0
4    (20.0, 40.0]      3
     (-0.001, 20.0]    0
     (40.0, 60.0]      0
     (60.0, 80.0]      0
     (80.0, 100.0]     0
Name: score, dtype: int64

这些数据中出现的唯一值是 0 和 100。但是 value_counts 告诉我范围 (20.0,40.0] 的值最多，而 (80.0,100.0] 没有。

当然，我的真实数据有更多的值、不同的键等，但这说明了我所看到的问题。

为什么？

Answer 1

这是保持索引完整性的另一种方法。

d.groupby('key')['score'].apply(pd.Series.value_counts, bins=[0,20,40,60,80,100])

输出：

key                
0    (80.0, 100.0]     1
     (-0.001, 20.0]    1
     (60.0, 80.0]      0
     (40.0, 60.0]      0
     (20.0, 40.0]      0
1    (80.0, 100.0]     2
     (60.0, 80.0]      0
     (40.0, 60.0]      0
     (20.0, 40.0]      0
     (-0.001, 20.0]    0
2    (-0.001, 20.0]    1
     (80.0, 100.0]     0
     (60.0, 80.0]      0
     (40.0, 60.0]      0
     (20.0, 40.0]      0
3    (80.0, 100.0]     2
     (60.0, 80.0]      0
     (40.0, 60.0]      0
     (20.0, 40.0]      0
     (-0.001, 20.0]    0
4    (80.0, 100.0]     3
     (60.0, 80.0]      0
     (40.0, 60.0]      0
     (20.0, 40.0]      0
     (-0.001, 20.0]    0
Name: score, dtype: int64