检查pandas数据框是否为其他数据框的子集 [英] Check if pandas dataframe is subset of other dataframe

问题描述

我有两个Python Pandas数据框A，B，它们具有相同的列(显然具有不同的数据).我要检查A是B的子集，即A的所有行都包含在B中.

I have two Python Pandas dataframes A, B, with the same columns (obviously with different data). I want to check A is a subset of B, that is, all rows of A are contained in B.

任何想法怎么做?

推荐答案

方法 DataFrame.merge(another_DF) 默认情况下在列的交集上合并(使用两个DF中具有相同名称的所有列)并使用how='inner'-因此我们希望inner join(如果两个DF都不重复):

Method DataFrame.merge(another_DF) merges on the intersection of the columns by default (uses all columns with same names from both DFs) and uses how='inner' - so we expect to have the same # of rows after inner join (if neither of DFs has duplicates):

len(A.merge(B)) == len(A)

如果其中一个DF重复行，则PS将无法正常工作-有关此类情况，请参见下文

PS it will NOT work properly if one of DFs have duplicated rows - see below for such cases

演示:

In [128]: A
Out[128]:
   A  B  C
0  1  2  3
1  4  5  6

In [129]: B
Out[129]:
   A  B  C
0  4  5  6
1  1  2  3
2  9  8  7

In [130]: len(A.merge(B)) == len(A)
Out[130]: True

---

对于包含重复项的数据集，我们可以删除重复项并使用相同的方法:

---

for data sets containing duplicates, we can remove duplicates and use the same method:

In [136]: A
Out[136]:
   A  B  C
0  1  2  3
1  4  5  6
2  1  2  3

In [137]: B
Out[137]:
   A  B  C
0  4  5  6
1  1  2  3
2  9  8  7
3  4  5  6

In [138]: A.merge(B).drop_duplicates()
Out[138]:
   A  B  C
0  1  2  3
2  4  5  6

In [139]: len(A.merge(B).drop_duplicates()) == len(A.drop_duplicates())
Out[139]: True

这篇关于检查pandas数据框是否为其他数据框的子集的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！