为什么.str.contains（）在这里找不到部分匹配项？ （熊猫数据框）

Question

Pandas dataframe "df1" has a column ("Receiver") with string values.

df1
    Receiver
44  BANK
106 restaurant
149 Tax office
63  house
55  car insurance

I want to go through each row of that column, check if they match with values (mostly one- or two-word search terms) in another dataframe ("df2") and return the matching column's title on the correct rows. I'm trying to do it with the following function:

df1.Receiver.apply(lambda x:
                               ''.join([i for i in df2.columns 
                               if df2.loc[:,i].str.contains(x).any()]) 
                               )

Problem: However, this only works for values in df1's "Receiver" column that consist of just one word (so "BANK", "restaurant" and "house" work in this case).

Values with two or more words do not work ("Tax office" and "car insurance" in this case).

Isn't str.contains() supposed to find also partial matches? How can I find partial matches also for values in the "Receiver" column that have two or more words?

edit: here's how df2 looks like, it has different categories as column titles, and then each column has the search terms as values

df2
    Banks    Restaurants   Car           House
0   BANK     restaurant    car           house
1   bank     mcdonalds     
2            Subway                 

Here is the whole problem in a single image, the output can be seen on the right, and categories "Car" and "Tax office" are not found because the receivers "car insurance" and "Tax office" (receiver column in df1) are only partial matches with the search terms "car" and "Tax" (values in df2's columns "Car" and "Tax office".

Answer 1

Instead of iterating your dataframe rows, you can iterate columns of df2 and use regex with pd.Series.str.contains :

df1 = pd.DataFrame({'Receiver': ['BANK', 'restaurant house', 'Tax office', 'mcdonalds car']})

df1['Receiver_new'] = ''
for col in df2:
    values = '|'.join(df2[col].dropna())
    bool_series = df1['Receiver'].str.contains(values)
    df1.loc[bool_series, 'Receiver_new'] += f'{col}|'

print(df1)

#            Receiver        Receiver_new
# 0              BANK              Banks|
# 1  restaurant house  Restaurants|House|
# 2        Tax office                    
# 3     mcdonalds car    Restaurants|Car|