python - 在某些条件下查找 pandas 的连续值

Question

我试图找到连续的零值，并被这个问题困扰了几个小时。

我有一个像这样的数据框:

Day  |  ID  |  Values
-------------------
1    |  aa  |    0
1    |  aa  |    0
1    |  aa  |    0
1    |  aa  |    0
1    |  aa  |    2.5
1    |  aa  |    2.3
1    |  aa  |    0
1    |  aa  |    0
1    |  aa  |    0
2    |  aa  |    0
2    |  aa  |    0
2    |  aa  |    2.3
2    |  aa  |    0
1    |  bb  |    0
1    |  bb  |    0
1    |  bb  |    0
1    |  bb  |    0
1    |  bb  |    3.5

我想找到连续的零值，如下所示:

Day  |  ID  |  Values   | consec_zeros
--------------------------------------
1    |  aa  |    0      |      0
1    |  aa  |    0      |      1
1    |  aa  |    0      |      2
1    |  aa  |    0      |      3
1    |  aa  |    2.5    |      4      # --> there were 4 of consecutive 0s 
1    |  aa  |    2.3    |      0      # 2.5 just destroy consecutive values
1    |  aa  |    0      |      0
1    |  aa  |    0      |      1
1    |  aa  |    0      |      2      
2    |  aa  |    0      |      0      # no 0s before this of Day 2
2    |  aa  |    0      |      1
2    |  aa  |    2.3    |      2
2    |  aa  |    0      |      0
1    |  bb  |    0      |      0     # --> no 0s before this in ID 'bb'
1    |  bb  |    0      |      1
1    |  bb  |    0      |      2
1    |  bb  |    0      |      3
1    |  bb  |    3.5    |      4

我尝试做的是:

g = df['Values'].ne(df['Values'].shift(1)).cumsum()
counts = df.groupby(['ID','Day',g])['Values'].transform('size')
df['consec_zeros'] = np.where(df['Values'].eq(0), counts, 0)

由于我是新手，请帮助并指出我做错了什么。

提前谢谢

Answer 1

这是主要问题，通过 GroupBy.cumcount 通过第一个非零值添加下一个计数器值，但也将其用于脱粒，在我的解决方案中添加了 1 来计数器以区分计数器中的第一个值:

g = df['Values'].ne(df['Values'].shift(1)).cumsum()
counts = df.groupby(['ID','Day',g])['Values'].cumcount() + 1
df['consec_zeros'] = np.where(df['Values'].eq(0), counts, 0)

#replace 0 to `NaN`s
a = df['consec_zeros'].mask(df['consec_zeros'].eq(0))
#add 1 to forward filling missing values by limit 1 per groups
df['consec_zeros'] = (np.where(a.isna(), 
                               a.groupby([df['ID'],df['Day']]).ffill(limit=1) + 1, 
                               df['consec_zeros']) - 1)
df['consec_zeros'] = df['consec_zeros'].fillna(0).astype(int)
print (df)
    Day  ID  Values  consec_zeros
0     1  aa     0.0             0
1     1  aa     0.0             1
2     1  aa     0.0             2
3     1  aa     0.0             3
4     1  aa     2.5             4
5     1  aa     2.3             0
6     1  aa     0.0             0
7     1  aa     0.0             1
8     1  aa     0.0             2
9     2  aa     0.0             0
10    2  aa     0.0             1
11    2  aa     2.3             2
12    2  aa     0.0             0
13    1  bb     0.0             0
14    1  bb     0.0             1
15    1  bb     0.0             2
16    1  bb     0.0             3
17    1  bb     3.5             4