如何根据来自不同数据框的列中的条目对数据框应用 Pandas 过滤器（无连接）

Question

例如，我有一个数据框 (df_1)，其中一列包含一些文本数据。第二个数据框 (df_2) 包含一些数字。如何检查文本是否包含第二个数据框中的数字？df_1                       Note0  The code to this is 10031  The code to this is 1004df_2   Code_Number0         10061         1003所以我想检查 df_1 [Note] 中的条目是否包含 df_2 [Code_Number] 中的条目我尝试使用以下代码：df_1[df_1['Note'].str.contains(df_2['Code_Number'])]并且我知道我不能使用连接，因为我没有加入的密钥。应用过滤后我正在寻找的最终结果是：   Note              0  The code to this is 1003    

Answer 1

试试这个，看看它是否涵盖了您的用例：使用itertools 的产品和基于条件的过滤器获取两列的交叉笛卡尔：

from itertools import product

m = [ left for left, right

      in product(df.Note,df1.Code_Number) 

      if str(right) in left]

pd.DataFrame(m,columns=['Note'])

               Note

0   The code to this is 1003

Answer 2

做这个：

df_1.loc[df_1['Note'].apply(lambda x: any(str(number) in x for number in df_2['Code_Number']))]

Answer 3

Firstly, you have to create 1 column in your df1 where the notes are with a list of numbers that are present in the Notes and then Compare the List column of numbers with the List column of the df2 where the numbers are present(both should be in list format)

#Extract Numbers from Notes

a_string = "0abcadda1 11 def 23 10007"

numbers = [int(word) for word in a_string.split() if word.isdigit()]

print(numbers)

list_test = "103,23"

#Finding common element from both lists the list

L1 = [2,3,4]

L2 = [1,2]

[i for i in L1 if i in L2]

S1 = set(L1)

S2 = set(L2)

print(S1.intersection(S2))

#If you want to find out the common element

def common_data(list1, list2):

    result = False

    # traverse in the 1st list 

    for x in list1:

        # traverse in the 2nd list 

        for y in list2:

            # if one common 

            if x == y:

                result = True

                return result

    return result

# driver code 

a = [1, 2, 3, 4, 5]

b = [5, 6, 7, 8, 9]

print(common_data(a, b))

a = [1, 2, 3, 4, 5]

b = [6, 7, 8, 9]

print(common_data(a, b))