如何根据与序列相关的约束过滤行? [英] How to filter rows based on the sequence-related constraint?

问题描述

我有以下数据框:

df = 
    ID   TYPE   VD_0   VD_1   VD_2   VD_3
    1    ABC    V1234  456    123    564
    2    DBC    456    A45    123    564
    3    ABD    456    V1234  456    123
    4    ABD    123    V1234  SSW    123

以下是VD_0，VD_1，VD_2和VD_3的值的列表:

There is the following list of values of VD_0, VD_1, VD_2 and VD_3:

myList = [V1234,456,A45]

我只想获取df中的那些行，这些行在VD_0，VD_1，VD_2和VD_3列中的myList中具有2个连续出现的值.

I want to get only those rows in df that have 2 sequencial occurances of values from myList in columns VD_0, VD_1, VD_2 and VD_3.

结果是这样的:

result = 
    ID   TYPE   VD_0   VD_1   VD_2   VD_3
    1    ABC    V1234  456    123    564
    2    DBC    456    A45    123    564
    3    ABD    456    V1234  456    123

例如，在具有ID 1的行中，VD_0和VD_1的值分别等于V1234和456，并且这两个值都属于myList.相同的逻辑适用于具有ID 2(456，A45)和3(456，V1234)的行.

For example, in row with ID 1 the values of VD_0 and VD_1 are equal to V1234 and 456, correspondingly, and both of these values belong to myList. The same logic is applied to rows with ID 2 (456,A45) and 3 (456,V1234).

我该怎么办?

推荐答案

我同意MaxU答案的开头，但是结尾应该更容易IIUC.您想要的过滤器应从列表中获得2个连续匹配项.您可以说，如果您将isin结果的逐行总和至少为2，则将它们乘以2和2的总和就可以得到这个答案.这称为沿轴= 1的2周期滚动窗口总和.然后，您取每一行的最大值，并且匹配项的值大于或等于2:

I agree with the beginning of MaxU's answer, yet, the end should be easier IIUC. The filter you want should get 2 consecutive matches from your list. You can get this answer by saying you want the row by row sum of isin result being at least a value of 2 if you sum them two by two. This is called a 2-period rolling window sum along axis=1. Then you take the max value of each row and the matches have a value greater or equal then 2:

subset = df.filter(like='VD_')

df[subset.isin(myList).rolling(2, axis=1).sum().max(axis=1)>=2]
Out[26]: 
   ID TYPE   VD_0   VD_1 VD_2  VD_3
0   1  ABC  V1234    456  123   564
1   2  DBC    456    A45  123   564
2   3  ABD    456  V1234  456   123

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