如何对两个不同的 pandas 列中的字符串进行部分匹配检查？

Question

I have two dataframes, one with 300 names and one with 2000. I want to check if all of the words in each of the 300 names are contained in the 2000 in any iteration. For example:

Name 1: Mark, Alex, Smith,

Name 2: Mark, Joseph, Smith, Alex, the, first

Dataframe 1

Name 1
'Mark', 'Alex', 'Smith'

Dataframe 2

Name 2
'Mark', 'Joseph', 'Alex', 'Smith', 'the', First'

As you can see, the column in dataframe 2 contains all of the words from column in dataframe 1, but additional words in the name too.

My query should match here, because Name 2 contains all of the words from name 1 even though it is not an exact match. Each of the names is split into individual words in each cell.

Ideally, I would run a function across dataframe 2 which contains 2,000 names and see if any of those names have contain all of the words from dataframe 1.

Edit: Someone kindly pointed out in the comments that what I am trying to say, is can I find if Name 1 is a subset of Name 2.

Answer 1

Assuming that each of your dataframes have a column with list of strings:

>>> df1 = pd.DataFrame({
        "Name 1": [['Mark', 'Alex', 'Smith'], ['S1', 'S2', 'S3']],
    })
>>> df2 = pd.DataFrame({
        "Name 2": [['Mark', 'Joseph', 'Alex', 'Smith', 'the', 'First'], ['S3', 'S4', 'S5']],
    })

You could merge both dataframes first:

>>> df = pd.merge(df1, df2, left_index=True, right_index=True)
>>> print(df)
                Name 1                                   Name 2
0  [Mark, Alex, Smith]  [Mark, Joseph, Alex, Smith, the, First]
1         [S1, S2, S3]                             [S3, S4, S5]

And now apply this function to identify if the subset condition is True :

>>> df = df.apply(lambda row: set(row["Name 1"]).issubset(set(row["Name 2"])), axis=1)
>>> df
0     True
1    False
dtype: bool